SFS Wave 1 - Codebook

Meta-Data

Information / Read Me

If there are any questions about the data set or requests to share data, please direct them to: Menzner@em.uni-frankfurt.de.

Information about randomized display orders

This survey includes many randomizations - both in explicitly designed experiments and in order to avoid and detect ordering effects. In each section of the following overview, first descriptive statistics will be presented for the contextual variables followed by a table-style overview of randomization variables. These include:

Variables starting with “io_” denote the displayed item order within a larger answer matrix underneath a single question.
Variables starting with “qo_” denote the displayed question order within a question block.
Variables starting with “bo_” denote the displayed block order within the overall survey flow.
Additional contextual randomizations (e.g. within question phrasing) are explained explicitly within their respective section.

Note, that generally the presented descriptive data is the average over all randomizations. For some select, relevant cases, we also present the descriptive data for the singular randomization conditions.

General Items

Variable

Label

Stats / Values

Freqs (% of Valid)

Graph

Valid

attentioncheck [labelled, factor]

Attention Check
Placed in the 'Populism' battery

1. Failed

2. Passed

333	(	8.0%	)
3836	(	92.0%	)

4169 (87.4%)

duration [labelled, numeric]

Survey Duration (in seconds)

Mean (sd) : 2025.1 (3345.8)

min ≤ med ≤ max:

19 ≤ 1551 ≤ 99262

IQR (CV) : 1162.2 (1.7)

2617 distinct values

4772 (100.0%)

start denotes date and time the respondent started the survey
end denotes date and time the respondent finished the survey

SFS Variables

Descriptive Overview

Variable

Label

Stats / Values

Freqs (% of Valid)

Graph

Valid

sfs [labelled, factor]

Subjective Freedom Of Speech
Now it is about freedom of speech. How free or unfree do do you feel to say what you really think [about ...]?

1. Unfree

2. R. Unfree

3. R. Free

4. Free

329	(	6.9%	)
840	(	17.7%	)
1607	(	33.8%	)
1980	(	41.6%	)

4756 (99.7%)

sfs_problem [labelled, factor]

Subjective Freedom Of Speech - Problem
And how much does this bother you? It bothers me ...
Filter: sfs == 1 | sfs == 2

1. Not at all

2. Somewhat

3. Very

59	(	5.1%	)
436	(	37.5%	)
669	(	57.5%	)

1164 (24.4%)

sfs_family [labelled, factor]

Subjective Freedom Of Speech - Context (Family)
Where do you feel more or less free to say what you really think [about ...]? How free do you feel in your family?

1. Unfree

2. R. Unfree

3. R. Free

4. Free

128	(	2.7%	)
303	(	6.4%	)
1131	(	24.0%	)
3151	(	66.9%	)

4713 (98.8%)

sfs_friends [labelled, factor]

Subjective Freedom Of Speech - Context (Friends)
Where do you feel more or less free to say what you really think [about ...]? How free do you feel in your circle of friends?

1. Unfree

2. R. Unfree

3. R. Free

4. Free

104	(	2.2%	)
312	(	6.6%	)
1455	(	30.9%	)
2842	(	60.3%	)

4713 (98.8%)

sfs_neighbor [labelled, factor]

Subjective Freedom Of Speech - Context (Neighbors)
Where do you feel more or less free to say what you really think [about ...]? How free do you feel in your neigbourhood?

1. Unfree

2. R. Unfree

3. R. Free

4. Free

266	(	5.6%	)
915	(	19.4%	)
1889	(	40.1%	)
1643	(	34.9%	)

4713 (98.8%)

sfs_internet [labelled, factor]

Subjective Freedom Of Speech - Context (Internet)
Where do you feel more or less free to say what you really think [about ...]? How free do you feel in the internet and social media?

1. Unfree

2. R. Unfree

3. R. Free

4. Free

616	(	13.1%	)
1093	(	23.2%	)
1641	(	34.8%	)
1363	(	28.9%	)

4713 (98.8%)

sfs_work [labelled, factor]

Subjective Freedom Of Speech - Context (Work)
Where do you feel more or less free to say what you really think [about ...]? How free do you feel at your place of work or apprenticeship?

1. Unfree

2. R. Unfree

3. R. Free

4. Free

526	(	11.2%	)
1044	(	22.2%	)
1702	(	36.1%	)
1441	(	30.6%	)

4713 (98.8%)

sfs_stranger [labelled, factor]

Subjective Freedom Of Speech - Context (Strangers)
Where do you feel more or less free to say what you really think [about ...]? How free do you feel opposite unknown people?

1. Unfree

2. R. Unfree

3. R. Free

4. Free

613	(	13.0%	)
1320	(	28.0%	)
1658	(	35.2%	)
1122	(	23.8%	)

4713 (98.8%)

sfs_left [labelled, numeric]

Subjective Freedom of Speech: Die Linke
Now it's about the parties' role regarding the topic free speech. To what extent do the following parties promote or restrict freedom of speech in Germany?
Die Linke
-5 = Restricts Free Speech; 5 = Promotes Free Speech

Mean (sd) : 0 (2.8)

min ≤ med ≤ max:

-5 ≤ 0 ≤ 5

IQR (CV) : 4 (-65.1)

11 distinct values

4541 (95.2%)

sfs_green [labelled, numeric]

Subjective Freedom of Speech: B'90/Grünen
Now it's about the parties' role regarding the topic free speech. To what extent do the following parties promote or restrict freedom of speech in Germany?
B90/Grünen
-5 = Restricts Free Speech; 5 = Promotes Free Speech

Mean (sd) : 0.1 (3.2)

min ≤ med ≤ max:

-5 ≤ 0 ≤ 5

IQR (CV) : 6 (31.6)

11 distinct values

4541 (95.2%)

sfs_spd [labelled, numeric]

Subjective Freedom of Speech: SPD
Now it's about the parties' role regarding the topic free speech. To what extent do the following parties promote or restrict freedom of speech in Germany?
SPD
-5 = Restricts Free Speech; 5 = Promotes Free Speech

Mean (sd) : 0.6 (2.8)

min ≤ med ≤ max:

-5 ≤ 1 ≤ 5

IQR (CV) : 4 (4.9)

11 distinct values

4541 (95.2%)

sfs_cdu [labelled, numeric]

Subjective Freedom of Speech: CDU
Now it's about the parties' role regarding the topic free speech. To what extent do the following parties promote or restrict freedom of speech in Germany?
CDU
-5 = Restricts Free Speech; 5 = Promotes Free Speech

Mean (sd) : 0.4 (2.7)

min ≤ med ≤ max:

-5 ≤ 1 ≤ 5

IQR (CV) : 3 (7)

11 distinct values

4541 (95.2%)

sfs_csu [labelled, numeric]

Subjective Freedom of Speech: CSU
Now it's about the parties' role regarding the topic free speech. To what extent do the following parties promote or restrict freedom of speech in Germany?
CSU
-5 = Restricts Free Speech; 5 = Promotes Free Speech

Mean (sd) : 0.1 (2.7)

min ≤ med ≤ max:

-5 ≤ 0 ≤ 5

IQR (CV) : 4 (26.8)

11 distinct values

4541 (95.2%)

sfs_fdp [labelled, numeric]

Subjective Freedom of Speech: FDP
Now it's about the parties' role regarding the topic free speech. To what extent do the following parties promote or restrict freedom of speech in Germany?
FDP
-5 = Restricts Free Speech; 5 = Promotes Free Speech

Mean (sd) : 0.4 (2.6)

min ≤ med ≤ max:

-5 ≤ 1 ≤ 5

IQR (CV) : 3 (6.5)

11 distinct values

4541 (95.2%)

sfs_afd [labelled, numeric]

Subjective Freedom of Speech: AfD
Now it's about the parties' role regarding the topic free speech. To what extent do the following parties promote or restrict freedom of speech in Germany?
AfD
-5 = Restricts Free Speech; 5 = Promotes Free Speech

Mean (sd) : -1.2 (3.3)

min ≤ med ≤ max:

-5 ≤ -2 ≤ 5

IQR (CV) : 5 (-2.7)

11 distinct values

4541 (95.2%)

sfs_ger_public [labelled, numeric]

Subjective Freedom of Speech: Germany (Public)
How free can people in Germany voice their opinions without fear of their co-citizens?

Mean (sd) : 1.4 (2.7)

min ≤ med ≤ max:

-5 ≤ 2 ≤ 5

IQR (CV) : 3 (2)

11 distinct values

4093 (85.8%)

sfs_ger_state [labelled, numeric]

Subjective Freedom of Speech: Germany (State)
How free can people in Germany voice their opinions without fear of the state?

Mean (sd) : 1.8 (2.8)

min ≤ med ≤ max:

-5 ≤ 3 ≤ 5

IQR (CV) : 4 (1.6)

11 distinct values

4093 (85.8%)

sfs_gdr_public [labelled, numeric]

Subjective Freedom of Speech: GDR (Public)
How free could people in the GDR voice their opinions without fear of their co-citizens?

Mean (sd) : -2.3 (2.8)

min ≤ med ≤ max:

-5 ≤ -3 ≤ 5

IQR (CV) : 4 (-1.2)

11 distinct values

4097 (85.9%)

sfs_gdr_state [labelled, numeric]

Subjective Freedom of Speech: GDR (State)
How free could people in the GDR voice their opinions without fear of the state?

Mean (sd) : -2.7 (2.8)

min ≤ med ≤ max:

-5 ≤ -4 ≤ 5

IQR (CV) : 4 (-1)

11 distinct values

4096 (85.8%)

sfs_ns_public [labelled, numeric]

Subjective Freedom of Speech: National Socialism (Public)
How free could people under national socialism voice their opinions without fear of their co-citizens?

Mean (sd) : -2.7 (2.7)

min ≤ med ≤ max:

-5 ≤ -4 ≤ 5

IQR (CV) : 4 (-1)

11 distinct values

4104 (86.0%)

sfs_ns_state [labelled, numeric]

Subjective Freedom of Speech: National Socialism (State)
How free can people under national socialim voice their opinions without fear of the state?

Mean (sd) : -3 (2.8)

min ≤ med ≤ max:

-5 ≤ -5 ≤ 5

IQR (CV) : 3 (-0.9)

11 distinct values

4103 (86.0%)

Randomization Variables

Variables	Meaning
	SFS SOCIAL CONTEXTS
io_sfs_family	Placement of ‘sfs_family’ in ‘SFS Social Context’ question matrix
io_sfs_friends	Placement of ‘sfs_friends’ in ‘SFS Social Context’ question matrix
io_sfs_neighbor	Placement of ‘sfs_neighbor’ in ‘SFS Social Context’ question matrix
io_sfs_internet	Placement of ‘sfs_internet’ in ‘SFS Social Context’ question matrix
io_sfs_work	Placement of ‘sfs_work’ in ‘SFS Social Context’ question matrix
io_sfs_stranger	Placement of ‘sfs_stranger’ in ‘SFS Social Context’ question matrix
	SANCTION VARIABLES
io_sancdisprob_disagreement	Placement of ‘sancdisprob_disagreement’ in ‘Sanction Probability: Discursive’ question matrix
io_sancdisprob_insulting	Placement of ‘sancdisprob_insulting’ in ‘Sanction Probability: Discursive’ question matrix
io_sancdisprob_justifying	Placement of ‘sancdisprob_justifying’ in ‘Sanction Probability: Discursive’ question matrix
io_sancdisprob_hurting	Placement of ‘sancdisprob_hurting’ in ‘Sanction Probability: Discursive’ question matrix
io_sancdisprob_misunderstood	Placement of ‘sancdisprob_misunderstood’ in ‘Sanction Probability: Discursive’ question matrix

io_sancdisexp_disagreement	Placement of ‘sancdisexp_disagreement’ in ‘Sanction Experience: Discursive’ question matrix
io_sancdisexp_insulting	Placement of ‘sancdisexp_insulting’ in ‘Sanction Experience: Discursive’ question matrix
io_sancdisexp_justifying	Placement of ‘sancdisexp_justifying’ in ‘Sanction Experience: Discursive’ question matrix
io_sancdisexp_hurting	Placement of ‘sancdisexp_hurting’ in ‘Sanction Experience: Discursive’ question matrix
io_sancdisexp_misunderstood	Placement of ‘sancdisexp_misunderstood’ in ‘Sanction Experience: Discursive’ question matrix

io_sancsocprob_radical	Placement of ‘sancsocprob_radical’ in ‘Sanction Probability: Social’ question matrix
io_sancsocprob_online	Placement of ‘sancsocprob_online’ in ‘Sanction Probability: Social’ question matrix
io_sancsocprob_falsepraise	Placement of ‘sancsocprob_falsepraise’ in ‘Sanction Probability: Social’ question matrix
io_sancsocprob_wronggroup	Placement of ‘sancsocprob_wronggroup’ in ‘Sanction Probability: Social’ question matrix

io_sancsocexp_radical	Placement of ‘sancsocexp_radical’ in ‘Sanction Experience: Social’ question matrix
io_sancsocexp_online	Placement of ‘sancsocexp_online’ in ‘Sanction Experience: Social’ question matrix
io_sancsocexp_falsepraise	Placement of ‘sancsocexp_falsepraise’ in ‘Sanction Experience: Social’ question matrix
io_sancsocexp_wronggroup	Placement of ‘sancsocexp_wronggroup’ in ‘Sanction Experience: Social’ question matrix

io_sancclaprob_friends	Placement of ‘sancclaprob_friends’ in ‘Sanction Probability: Classical’ question matrix
io_sancclaprob_job	Placement of ‘sancclaprob_job’ in ‘Sanction Probability: Classical’ question matrix
io_sancclaprob_law	Placement of ‘sancclaprob_law’ in ‘Sanction Probability: Classical’ question matrix
io_sancclaprob_harm	Placement of ‘sancclaprob_harm’ in ‘Sanction Probability: Classical’ question matrix

io_sancclaexp_friends	Placement of ‘sancclaexp_friends’ in ‘Sanction Experience: Classical’ question matrix
io_sancclaexp_job	Placement of ‘sancclaexp_job’ in ‘Sanction Experience: Classical’ question matrix
io_sancclaexp_law	Placement of ‘sancclaexp_law’ in ‘Sanction Experience: Classical’ question matrix
io_sancclaexp_harm	Placement of ‘sancclaexp_harm’ in ‘Sanction Experience: Classical’ question matrix

bo_sancdis	Placement of ‘Discursive Sanctions’ block in ‘Sanctions’ module
bo_sancsoc	Placement of ‘Social Sanctions’ block in ‘Sanctions’ module
bo_sanccla	Placement of ‘Classical Sanctions’ block in ‘Sanctions’ module

qo_prob	Order of ‘probablity’ and ‘experience’ items throughout sanction evaluations: ‘Probability’
qo_exp	Order of ‘probablity’ and ‘experience’ items throughout sanction evaluations: ‘Experience’
	SANCTIONERS VARIABLES
io_sanctdir_family	Placement of ‘sanctdir_family’ in ‘Sanctioners: Direct’ question matrix
io_sanctdir_friends	Placement of ‘sanctdir_friends’ in ‘Sanctioners: Direct’ question matrix
io_sanctdir_neighbor	Placement of ‘sanctdir_neighbor’ in ‘Sanctioners: Direct’ question matrix
io_sanctdir_boss	Placement of ‘sanctdir_boss’ in ‘Sanctioners: Direct’ question matrix
io_sanctdir_colleagues	Placement of ‘sanctdir_colleagues’ in ‘Sanctioners: Direct’ question matrix

io_sancteli_politics	Placement of ‘sancteli_politics’ in ‘Sanctioners: Elites’ question matrix
io_sancteli_media	Placement of ‘sancteli_media’ in ‘Sanctioners: Elites’ question matrix
io_sancteli_elites	Placement of ‘sancteli_elites’ in ‘Sanctioners: Elites’ question matrix

io_sancton_smcompany	Placement of ‘sancton_smcompany’ in ‘Sanctioners: Social Media’ question matrix
io_sancton_smusers	Placement of ‘sancton_smusers’ in ‘Sanctioners: Social Media’ question matrix
io_sancton_smregulation	Placement of ‘sancton_smregulation’ in ‘Sanctioners: Social Media’ question matrix

io_sanctpol_activists	Placement of ‘sanctpol_activists’ in ‘Sanctioners: Political’ question matrix
io_sanctpol_left	Placement of ‘sanctpol_left’ in ‘Sanctioners: Political’ question matrix
io_sanctpol_right	Placement of ‘sanctpol_right’ in ‘Sanctioners: Political’ question matrix

qo_sanctdir	Placement of ‘Sanctioners: Direct’ question matrix in survey block order
qo_sancteli	Placement of ‘Sanctioners: Elites’ question matrix in survey block order
qo_sancton	Placement of ‘Sanctioners: Social Media’ question matrix in survey block order
qo_sanctpol	Placement of ‘Sanctioners: Political’ question matrix in survey block order
	PARTY INFLUENCE ON SFS
io_sfs_left	Placement of ‘sfs_left’ in ‘Party SFS’ question matrix
io_sfs_green	Placement of ‘sfs_green’ in ‘Party SFS’ question matrix
io_sfs_spd	Placement of ‘sfs_spd’ in ‘Party SFS’ question matrix
io_sfs_cdu	Placement of ‘sfs_cdu’ in ‘Party SFS’ question matrix
io_sfs_csu	Placement of ‘sfs_csu’ in ‘Party SFS’ question matrix
io_sfs_fdp	Placement of ‘sfs_fdp’ in ‘Party SFS’ question matrix
io_sfs_afd	Placement of ‘sfs_afd’ in ‘Party SFS’ question matrix
	SFS IN GERMANY: EVALUATIONS
bo_sfs_countries_ger	Placement of evaluations of ‘Germany’ in country evaluation block
bo_sfs_countries_gdr	Placement of evaluations of ‘GDR’ in country evaluation block
bo_sfs_countries_ns	Placement of evaluations of ‘National Socialism’ in country evaluation block

qo_sfs_countries_public	Order of evaluating ‘public’ and ‘state’ restrictions throughout country evaluations : ‘Public’
qo_sfs_countries_state	Order of evaluating ‘public’ and ‘state’ restrictions throughout country evaluations : ‘State’

Descriptive Overview split by SFS Issues

Group: sfs_issue = Baseline

Variable

Label

Stats / Values

Freqs (% of Valid)

Graph

Valid

sfs [labelled, factor]

Subjective Freedom Of Speech
Now it is about freedom of speech. How free or unfree do do you feel to say what you really think [about ...]?

1. Unfree

2. R. Unfree

3. R. Free

4. Free

65	(	5.3%	)
187	(	15.2%	)
483	(	39.4%	)
492	(	40.1%	)

1227 (99.8%)

sfs_problem [labelled, factor]

Subjective Freedom Of Speech - Problem
And how much does this bother you? It bothers me ...
Filter: sfs == 1 | sfs == 2

1. Not at all

2. Somewhat

3. Very

8	(	3.2%	)
71	(	28.2%	)
173	(	68.7%	)

252 (20.5%)

sfs_family [labelled, factor]

Subjective Freedom Of Speech - Context (Family)
Where do you feel more or less free to say what you really think [about ...]? How free do you feel in your family?

1. Unfree

2. R. Unfree

3. R. Free

4. Free

45	(	3.7%	)
85	(	7.0%	)
272	(	22.4%	)
814	(	66.9%	)

1216 (98.9%)

sfs_friends [labelled, factor]

Subjective Freedom Of Speech - Context (Friends)
Where do you feel more or less free to say what you really think [about ...]? How free do you feel in your circle of friends?

1. Unfree

2. R. Unfree

3. R. Free

4. Free

19	(	1.6%	)
64	(	5.3%	)
389	(	32.0%	)
744	(	61.2%	)

1216 (98.9%)

sfs_neighbor [labelled, factor]

Subjective Freedom Of Speech - Context (Neighbors)
Where do you feel more or less free to say what you really think [about ...]? How free do you feel in your neigbourhood?

1. Unfree

2. R. Unfree

3. R. Free

4. Free

62	(	5.1%	)
261	(	21.5%	)
554	(	45.6%	)
339	(	27.9%	)

1216 (98.9%)

sfs_internet [labelled, factor]

Subjective Freedom Of Speech - Context (Internet)
Where do you feel more or less free to say what you really think [about ...]? How free do you feel in the internet and social media?

1. Unfree

2. R. Unfree

3. R. Free

4. Free

158	(	13.0%	)
269	(	22.1%	)
463	(	38.1%	)
326	(	26.8%	)

1216 (98.9%)

sfs_work [labelled, factor]

Subjective Freedom Of Speech - Context (Work)
Where do you feel more or less free to say what you really think [about ...]? How free do you feel at your place of work or apprenticeship?

1. Unfree

2. R. Unfree

3. R. Free

4. Free

136	(	11.2%	)
297	(	24.4%	)
472	(	38.8%	)
311	(	25.6%	)

1216 (98.9%)

sfs_stranger [labelled, factor]

Subjective Freedom Of Speech - Context (Strangers)
Where do you feel more or less free to say what you really think [about ...]? How free do you feel opposite unknown people?

1. Unfree

2. R. Unfree

3. R. Free

4. Free

139	(	11.4%	)
382	(	31.4%	)
474	(	39.0%	)
221	(	18.2%	)

1216 (98.9%)

sfs_left [labelled, numeric]

Mean (sd) : 0 (2.8)

min ≤ med ≤ max:

-5 ≤ 0 ≤ 5

IQR (CV) : 4 (-74.7)

11 distinct values

1171 (95.3%)

sfs_green [labelled, numeric]

Mean (sd) : 0.1 (3.2)

min ≤ med ≤ max:

-5 ≤ 0 ≤ 5

IQR (CV) : 6 (43.1)

11 distinct values

1171 (95.3%)

sfs_spd [labelled, numeric]

Mean (sd) : 0.6 (2.8)

min ≤ med ≤ max:

-5 ≤ 1 ≤ 5

IQR (CV) : 4 (4.7)

11 distinct values

1171 (95.3%)

sfs_cdu [labelled, numeric]

Mean (sd) : 0.4 (2.7)

min ≤ med ≤ max:

-5 ≤ 1 ≤ 5

IQR (CV) : 4 (7.6)

11 distinct values

1171 (95.3%)

sfs_csu [labelled, numeric]

Mean (sd) : 0.1 (2.7)

min ≤ med ≤ max:

-5 ≤ 0 ≤ 5

IQR (CV) : 4 (26.8)

11 distinct values

1171 (95.3%)

sfs_fdp [labelled, numeric]

Mean (sd) : 0.4 (2.6)

min ≤ med ≤ max:

-5 ≤ 1 ≤ 5

IQR (CV) : 3 (6)

11 distinct values

1171 (95.3%)

sfs_afd [labelled, numeric]

Mean (sd) : -1.3 (3.3)

min ≤ med ≤ max:

-5 ≤ -2 ≤ 5

IQR (CV) : 5 (-2.6)

11 distinct values

1171 (95.3%)

sfs_ger_public [labelled, numeric]

Subjective Freedom of Speech: Germany (Public)
How free can people in Germany voice their opinions without fear of their co-citizens?

Mean (sd) : 1.3 (2.6)

min ≤ med ≤ max:

-5 ≤ 2 ≤ 5

IQR (CV) : 4 (2)

11 distinct values

1053 (85.7%)

sfs_ger_state [labelled, numeric]

Subjective Freedom of Speech: Germany (State)
How free can people in Germany voice their opinions without fear of the state?

Mean (sd) : 1.7 (2.8)

min ≤ med ≤ max:

-5 ≤ 2 ≤ 5

IQR (CV) : 4 (1.6)

11 distinct values

1054 (85.8%)

sfs_gdr_public [labelled, numeric]

Subjective Freedom of Speech: GDR (Public)
How free could people in the GDR voice their opinions without fear of their co-citizens?

Mean (sd) : -2.2 (2.8)

min ≤ med ≤ max:

-5 ≤ -3 ≤ 5

IQR (CV) : 5 (-1.3)

11 distinct values

1056 (85.9%)

sfs_gdr_state [labelled, numeric]

Subjective Freedom of Speech: GDR (State)
How free could people in the GDR voice their opinions without fear of the state?

Mean (sd) : -2.6 (2.9)

min ≤ med ≤ max:

-5 ≤ -4 ≤ 5

IQR (CV) : 4 (-1.1)

11 distinct values

1055 (85.8%)

sfs_ns_public [labelled, numeric]

Subjective Freedom of Speech: National Socialism (Public)
How free could people under national socialism voice their opinions without fear of their co-citizens?

Mean (sd) : -2.7 (2.8)

min ≤ med ≤ max:

-5 ≤ -4 ≤ 5

IQR (CV) : 4 (-1)

11 distinct values

1057 (86.0%)

sfs_ns_state [labelled, numeric]

Subjective Freedom of Speech: National Socialism (State)
How free can people under national socialim voice their opinions without fear of the state?

Mean (sd) : -3 (2.7)

min ≤ med ≤ max:

-5 ≤ -4 ≤ 5

IQR (CV) : 3 (-0.9)

11 distinct values

1058 (86.1%)

Group: sfs_issue = Climate

Variable

Label

Stats / Values

Freqs (% of Valid)

Graph

Valid

sfs [labelled, factor]

Subjective Freedom Of Speech
Now it is about freedom of speech. How free or unfree do do you feel to say what you really think [about ...]?

1. Unfree

2. R. Unfree

3. R. Free

4. Free

53	(	4.6%	)
172	(	15.0%	)
356	(	31.1%	)
563	(	49.2%	)

1144 (99.7%)

sfs_problem [labelled, factor]

Subjective Freedom Of Speech - Problem
And how much does this bother you? It bothers me ...
Filter: sfs == 1 | sfs == 2

1. Not at all

2. Somewhat

3. Very

14	(	6.3%	)
107	(	48.2%	)
101	(	45.5%	)

222 (19.3%)

sfs_family [labelled, factor]

Subjective Freedom Of Speech - Context (Family)
Where do you feel more or less free to say what you really think [about ...]? How free do you feel in your family?

1. Unfree

2. R. Unfree

3. R. Free

4. Free

25	(	2.2%	)
66	(	5.8%	)
270	(	23.9%	)
768	(	68.0%	)

1129 (98.3%)

sfs_friends [labelled, factor]

Subjective Freedom Of Speech - Context (Friends)
Where do you feel more or less free to say what you really think [about ...]? How free do you feel in your circle of friends?

1. Unfree

2. R. Unfree

3. R. Free

4. Free

29	(	2.6%	)
79	(	7.0%	)
322	(	28.5%	)
699	(	61.9%	)

1129 (98.3%)

sfs_neighbor [labelled, factor]

Subjective Freedom Of Speech - Context (Neighbors)
Where do you feel more or less free to say what you really think [about ...]? How free do you feel in your neigbourhood?

1. Unfree

2. R. Unfree

3. R. Free

4. Free

41	(	3.6%	)
170	(	15.1%	)
417	(	36.9%	)
501	(	44.4%	)

1129 (98.3%)

sfs_internet [labelled, factor]

Subjective Freedom Of Speech - Context (Internet)
Where do you feel more or less free to say what you really think [about ...]? How free do you feel in the internet and social media?

1. Unfree

2. R. Unfree

3. R. Free

4. Free

112	(	9.9%	)
208	(	18.4%	)
384	(	34.0%	)
425	(	37.6%	)

1129 (98.3%)

sfs_work [labelled, factor]

Subjective Freedom Of Speech - Context (Work)
Where do you feel more or less free to say what you really think [about ...]? How free do you feel at your place of work or apprenticeship?

1. Unfree

2. R. Unfree

3. R. Free

4. Free

81	(	7.2%	)
190	(	16.8%	)
397	(	35.2%	)
461	(	40.8%	)

1129 (98.3%)

sfs_stranger [labelled, factor]

Subjective Freedom Of Speech - Context (Strangers)
Where do you feel more or less free to say what you really think [about ...]? How free do you feel opposite unknown people?

1. Unfree

2. R. Unfree

3. R. Free

4. Free

110	(	9.7%	)
245	(	21.7%	)
408	(	36.1%	)
366	(	32.4%	)

1129 (98.3%)

sfs_left [labelled, numeric]

Mean (sd) : 0 (2.7)

min ≤ med ≤ max:

-5 ≤ 0 ≤ 5

IQR (CV) : 4 (-56.8)

11 distinct values

1090 (94.9%)

sfs_green [labelled, numeric]

Mean (sd) : 0.2 (3.2)

min ≤ med ≤ max:

-5 ≤ 0 ≤ 5

IQR (CV) : 5 (14.1)

11 distinct values

1090 (94.9%)

sfs_spd [labelled, numeric]

Mean (sd) : 0.6 (2.8)

min ≤ med ≤ max:

-5 ≤ 1 ≤ 5

IQR (CV) : 4 (4.4)

11 distinct values

1090 (94.9%)

sfs_cdu [labelled, numeric]

Mean (sd) : 0.5 (2.7)

min ≤ med ≤ max:

-5 ≤ 1 ≤ 5

IQR (CV) : 3 (5.2)

11 distinct values

1090 (94.9%)

sfs_csu [labelled, numeric]

Mean (sd) : 0.2 (2.6)

min ≤ med ≤ max:

-5 ≤ 0 ≤ 5

IQR (CV) : 3 (11)

11 distinct values

1090 (94.9%)

sfs_fdp [labelled, numeric]

Mean (sd) : 0.4 (2.6)

min ≤ med ≤ max:

-5 ≤ 0 ≤ 5

IQR (CV) : 3 (6.3)

11 distinct values

1090 (94.9%)

sfs_afd [labelled, numeric]

Mean (sd) : -1.4 (3.3)

min ≤ med ≤ max:

-5 ≤ -2 ≤ 5

IQR (CV) : 5 (-2.4)

11 distinct values

1090 (94.9%)

sfs_ger_public [labelled, numeric]

Subjective Freedom of Speech: Germany (Public)
How free can people in Germany voice their opinions without fear of their co-citizens?

Mean (sd) : 1.4 (2.7)

min ≤ med ≤ max:

-5 ≤ 2 ≤ 5

IQR (CV) : 3 (1.8)

11 distinct values

969 (84.4%)

sfs_ger_state [labelled, numeric]

Subjective Freedom of Speech: Germany (State)
How free can people in Germany voice their opinions without fear of the state?

Mean (sd) : 1.9 (2.8)

min ≤ med ≤ max:

-5 ≤ 3 ≤ 5

IQR (CV) : 4 (1.5)

11 distinct values

968 (84.3%)

sfs_gdr_public [labelled, numeric]

Subjective Freedom of Speech: GDR (Public)
How free could people in the GDR voice their opinions without fear of their co-citizens?

Mean (sd) : -2.5 (2.7)

min ≤ med ≤ max:

-5 ≤ -3 ≤ 5

IQR (CV) : 4 (-1.1)

11 distinct values

967 (84.2%)

sfs_gdr_state [labelled, numeric]

Subjective Freedom of Speech: GDR (State)
How free could people in the GDR voice their opinions without fear of the state?

Mean (sd) : -2.9 (2.7)

min ≤ med ≤ max:

-5 ≤ -4 ≤ 5

IQR (CV) : 3 (-0.9)

11 distinct values

968 (84.3%)

sfs_ns_public [labelled, numeric]

Subjective Freedom of Speech: National Socialism (Public)
How free could people under national socialism voice their opinions without fear of their co-citizens?

Mean (sd) : -2.9 (2.6)

min ≤ med ≤ max:

-5 ≤ -4 ≤ 5

IQR (CV) : 3 (-0.9)

11 distinct values

971 (84.6%)

sfs_ns_state [labelled, numeric]

Subjective Freedom of Speech: National Socialism (State)
How free can people under national socialim voice their opinions without fear of the state?

Mean (sd) : -3.1 (2.8)

min ≤ med ≤ max:

-5 ≤ -5 ≤ 5

IQR (CV) : 3 (-0.9)

11 distinct values

972 (84.7%)

Group: sfs_issue = Government

Variable

Label

Stats / Values

Freqs (% of Valid)

Graph

Valid

sfs [labelled, factor]

Subjective Freedom Of Speech
Now it is about freedom of speech. How free or unfree do do you feel to say what you really think [about ...]?

1. Unfree

2. R. Unfree

3. R. Free

4. Free

94	(	7.9%	)
207	(	17.3%	)
390	(	32.6%	)
504	(	42.2%	)

1195 (99.6%)

sfs_problem [labelled, factor]

Subjective Freedom Of Speech - Problem
And how much does this bother you? It bothers me ...
Filter: sfs == 1 | sfs == 2

1. Not at all

2. Somewhat

3. Very

14	(	4.7%	)
90	(	30.0%	)
196	(	65.3%	)

300 (25.0%)

sfs_family [labelled, factor]

Subjective Freedom Of Speech - Context (Family)
Where do you feel more or less free to say what you really think [about ...]? How free do you feel in your family?

1. Unfree

2. R. Unfree

3. R. Free

4. Free

31	(	2.6%	)
69	(	5.8%	)
270	(	22.8%	)
816	(	68.8%	)

1186 (98.8%)

sfs_friends [labelled, factor]

Subjective Freedom Of Speech - Context (Friends)
Where do you feel more or less free to say what you really think [about ...]? How free do you feel in your circle of friends?

1. Unfree

2. R. Unfree

3. R. Free

4. Free

27	(	2.3%	)
73	(	6.2%	)
333	(	28.1%	)
753	(	63.5%	)

1186 (98.8%)

sfs_neighbor [labelled, factor]

Subjective Freedom Of Speech - Context (Neighbors)
Where do you feel more or less free to say what you really think [about ...]? How free do you feel in your neigbourhood?

1. Unfree

2. R. Unfree

3. R. Free

4. Free

73	(	6.2%	)
219	(	18.5%	)
453	(	38.2%	)
441	(	37.2%	)

1186 (98.8%)

sfs_internet [labelled, factor]

Subjective Freedom Of Speech - Context (Internet)
Where do you feel more or less free to say what you really think [about ...]? How free do you feel in the internet and social media?

1. Unfree

2. R. Unfree

3. R. Free

4. Free

141	(	11.9%	)
303	(	25.5%	)
415	(	35.0%	)
327	(	27.6%	)

1186 (98.8%)

sfs_work [labelled, factor]

Subjective Freedom Of Speech - Context (Work)
Where do you feel more or less free to say what you really think [about ...]? How free do you feel at your place of work or apprenticeship?

1. Unfree

2. R. Unfree

3. R. Free

4. Free

149	(	12.6%	)
259	(	21.8%	)
409	(	34.5%	)
369	(	31.1%	)

1186 (98.8%)

sfs_stranger [labelled, factor]

Subjective Freedom Of Speech - Context (Strangers)
Where do you feel more or less free to say what you really think [about ...]? How free do you feel opposite unknown people?

1. Unfree

2. R. Unfree

3. R. Free

4. Free

155	(	13.1%	)
338	(	28.5%	)
403	(	34.0%	)
290	(	24.5%	)

1186 (98.8%)

sfs_left [labelled, numeric]

Mean (sd) : -0.1 (2.8)

min ≤ med ≤ max:

-5 ≤ 0 ≤ 5

IQR (CV) : 4 (-24.5)

11 distinct values

1139 (94.9%)

sfs_green [labelled, numeric]

Mean (sd) : 0 (3.2)

min ≤ med ≤ max:

-5 ≤ 0 ≤ 5

IQR (CV) : 6 (217)

11 distinct values

1139 (94.9%)

sfs_spd [labelled, numeric]

Mean (sd) : 0.6 (2.9)

min ≤ med ≤ max:

-5 ≤ 1 ≤ 5

IQR (CV) : 4 (5.1)

11 distinct values

1139 (94.9%)

sfs_cdu [labelled, numeric]

Mean (sd) : 0.4 (2.8)

min ≤ med ≤ max:

-5 ≤ 1 ≤ 5

IQR (CV) : 3 (7.2)

11 distinct values

1139 (94.9%)

sfs_csu [labelled, numeric]

Mean (sd) : 0.2 (2.7)

min ≤ med ≤ max:

-5 ≤ 0 ≤ 5

IQR (CV) : 4 (16)

11 distinct values

1139 (94.9%)

sfs_fdp [labelled, numeric]

Mean (sd) : 0.4 (2.7)

min ≤ med ≤ max:

-5 ≤ 1 ≤ 5

IQR (CV) : 3 (7.2)

11 distinct values

1139 (94.9%)

sfs_afd [labelled, numeric]

Mean (sd) : -1.1 (3.3)

min ≤ med ≤ max:

-5 ≤ -2 ≤ 5

IQR (CV) : 6 (-3)

11 distinct values

1139 (94.9%)

sfs_ger_public [labelled, numeric]

Subjective Freedom of Speech: Germany (Public)
How free can people in Germany voice their opinions without fear of their co-citizens?

Mean (sd) : 1.4 (2.7)

min ≤ med ≤ max:

-5 ≤ 2 ≤ 5

IQR (CV) : 4 (2)

11 distinct values

1024 (85.3%)

sfs_ger_state [labelled, numeric]

Subjective Freedom of Speech: Germany (State)
How free can people in Germany voice their opinions without fear of the state?

Mean (sd) : 1.8 (2.9)

min ≤ med ≤ max:

-5 ≤ 3 ≤ 5

IQR (CV) : 4 (1.6)

11 distinct values

1023 (85.2%)

sfs_gdr_public [labelled, numeric]

Subjective Freedom of Speech: GDR (Public)
How free could people in the GDR voice their opinions without fear of their co-citizens?

Mean (sd) : -2.3 (2.7)

min ≤ med ≤ max:

-5 ≤ -3 ≤ 5

IQR (CV) : 4 (-1.2)

11 distinct values

1027 (85.6%)

sfs_gdr_state [labelled, numeric]

Subjective Freedom of Speech: GDR (State)
How free could people in the GDR voice their opinions without fear of the state?

Mean (sd) : -2.8 (2.8)

min ≤ med ≤ max:

-5 ≤ -4 ≤ 5

IQR (CV) : 3 (-1)

11 distinct values

1027 (85.6%)

sfs_ns_public [labelled, numeric]

Subjective Freedom of Speech: National Socialism (Public)
How free could people under national socialism voice their opinions without fear of their co-citizens?

Mean (sd) : -2.7 (2.7)

min ≤ med ≤ max:

-5 ≤ -4 ≤ 5

IQR (CV) : 3.5 (-1)

11 distinct values

1027 (85.6%)

sfs_ns_state [labelled, numeric]

Subjective Freedom of Speech: National Socialism (State)
How free can people under national socialim voice their opinions without fear of the state?

Mean (sd) : -3 (2.8)

min ≤ med ≤ max:

-5 ≤ -5 ≤ 5

IQR (CV) : 3 (-0.9)

11 distinct values

1026 (85.5%)

Group: sfs_issue = Immigration

Variable

Label

Stats / Values

Freqs (% of Valid)

Graph

Valid

sfs [labelled, factor]

Subjective Freedom Of Speech
Now it is about freedom of speech. How free or unfree do do you feel to say what you really think [about ...]?

1. Unfree

2. R. Unfree

3. R. Free

4. Free

117	(	9.8%	)
274	(	23.0%	)
378	(	31.8%	)
421	(	35.4%	)

1190 (99.6%)

sfs_problem [labelled, factor]

Subjective Freedom Of Speech - Problem
And how much does this bother you? It bothers me ...
Filter: sfs == 1 | sfs == 2

1. Not at all

2. Somewhat

3. Very

23	(	5.9%	)
168	(	43.1%	)
199	(	51.0%	)

390 (32.6%)

sfs_family [labelled, factor]

Subjective Freedom Of Speech - Context (Family)
Where do you feel more or less free to say what you really think [about ...]? How free do you feel in your family?

1. Unfree

2. R. Unfree

3. R. Free

4. Free

27	(	2.3%	)
83	(	7.0%	)
319	(	27.0%	)
753	(	63.7%	)

1182 (98.9%)

sfs_friends [labelled, factor]

Subjective Freedom Of Speech - Context (Friends)
Where do you feel more or less free to say what you really think [about ...]? How free do you feel in your circle of friends?

1. Unfree

2. R. Unfree

3. R. Free

4. Free

29	(	2.5%	)
96	(	8.1%	)
411	(	34.8%	)
646	(	54.7%	)

1182 (98.9%)

sfs_neighbor [labelled, factor]

Subjective Freedom Of Speech - Context (Neighbors)
Where do you feel more or less free to say what you really think [about ...]? How free do you feel in your neigbourhood?

1. Unfree

2. R. Unfree

3. R. Free

4. Free

90	(	7.6%	)
265	(	22.4%	)
465	(	39.3%	)
362	(	30.6%	)

1182 (98.9%)

sfs_internet [labelled, factor]

Subjective Freedom Of Speech - Context (Internet)
Where do you feel more or less free to say what you really think [about ...]? How free do you feel in the internet and social media?

1. Unfree

2. R. Unfree

3. R. Free

4. Free

205	(	17.3%	)
313	(	26.5%	)
379	(	32.1%	)
285	(	24.1%	)

1182 (98.9%)

sfs_work [labelled, factor]

Subjective Freedom Of Speech - Context (Work)
Where do you feel more or less free to say what you really think [about ...]? How free do you feel at your place of work or apprenticeship?

1. Unfree

2. R. Unfree

3. R. Free

4. Free

160	(	13.5%	)
298	(	25.2%	)
424	(	35.9%	)
300	(	25.4%	)

1182 (98.9%)

sfs_stranger [labelled, factor]

Subjective Freedom Of Speech - Context (Strangers)
Where do you feel more or less free to say what you really think [about ...]? How free do you feel opposite unknown people?

1. Unfree

2. R. Unfree

3. R. Free

4. Free

209	(	17.7%	)
355	(	30.0%	)
373	(	31.6%	)
245	(	20.7%	)

1182 (98.9%)

sfs_left [labelled, numeric]

Mean (sd) : 0 (2.8)

min ≤ med ≤ max:

-5 ≤ 0 ≤ 5

IQR (CV) : 4 (100.4)

11 distinct values

1141 (95.5%)

sfs_green [labelled, numeric]

Mean (sd) : 0.1 (3.2)

min ≤ med ≤ max:

-5 ≤ 0 ≤ 5

IQR (CV) : 5 (32.6)

11 distinct values

1141 (95.5%)

sfs_spd [labelled, numeric]

Mean (sd) : 0.5 (2.9)

min ≤ med ≤ max:

-5 ≤ 1 ≤ 5

IQR (CV) : 4 (5.3)

11 distinct values

1141 (95.5%)

sfs_cdu [labelled, numeric]

Mean (sd) : 0.3 (2.7)

min ≤ med ≤ max:

-5 ≤ 0 ≤ 5

IQR (CV) : 4 (9)

11 distinct values

1141 (95.5%)

sfs_csu [labelled, numeric]

Mean (sd) : -0.1 (2.7)

min ≤ med ≤ max:

-5 ≤ 0 ≤ 5

IQR (CV) : 4 (-26.6)

11 distinct values

1141 (95.5%)

sfs_fdp [labelled, numeric]

Mean (sd) : 0.4 (2.6)

min ≤ med ≤ max:

-5 ≤ 1 ≤ 5

IQR (CV) : 3 (6.8)

11 distinct values

1141 (95.5%)

sfs_afd [labelled, numeric]

Mean (sd) : -1.2 (3.4)

min ≤ med ≤ max:

-5 ≤ -2 ≤ 5

IQR (CV) : 6 (-2.7)

11 distinct values

1141 (95.5%)

sfs_ger_public [labelled, numeric]

Subjective Freedom of Speech: Germany (Public)
How free can people in Germany voice their opinions without fear of their co-citizens?

Mean (sd) : 1.3 (2.7)

min ≤ med ≤ max:

-5 ≤ 2 ≤ 5

IQR (CV) : 4 (2.1)

11 distinct values

1047 (87.6%)

sfs_ger_state [labelled, numeric]

Subjective Freedom of Speech: Germany (State)
How free can people in Germany voice their opinions without fear of the state?

Mean (sd) : 1.7 (2.8)

min ≤ med ≤ max:

-5 ≤ 3 ≤ 5

IQR (CV) : 4 (1.7)

11 distinct values

1048 (87.7%)

sfs_gdr_public [labelled, numeric]

Subjective Freedom of Speech: GDR (Public)
How free could people in the GDR voice their opinions without fear of their co-citizens?

Mean (sd) : -2.3 (2.8)

min ≤ med ≤ max:

-5 ≤ -3 ≤ 5

IQR (CV) : 5 (-1.2)

11 distinct values

1047 (87.6%)

sfs_gdr_state [labelled, numeric]

Subjective Freedom of Speech: GDR (State)
How free could people in the GDR voice their opinions without fear of the state?

Mean (sd) : -2.7 (2.8)

min ≤ med ≤ max:

-5 ≤ -4 ≤ 5

IQR (CV) : 4 (-1)

11 distinct values

1046 (87.5%)

sfs_ns_public [labelled, numeric]

Subjective Freedom of Speech: National Socialism (Public)
How free could people under national socialism voice their opinions without fear of their co-citizens?

Mean (sd) : -2.7 (2.8)

min ≤ med ≤ max:

-5 ≤ -4 ≤ 5

IQR (CV) : 4 (-1)

11 distinct values

1049 (87.8%)

sfs_ns_state [labelled, numeric]

Subjective Freedom of Speech: National Socialism (State)
How free can people under national socialim voice their opinions without fear of the state?

Mean (sd) : -3 (2.8)

min ≤ med ≤ max:

-5 ≤ -5 ≤ 5

IQR (CV) : 3 (-0.9)

11 distinct values

1047 (87.6%)

Sanctions

Variable

Label

Stats / Values

Freqs (% of Valid)

Graph

Valid

sancdisprob_disagreement [labelled, factor]

Sanction Probability: Contradicting (Discursive)
If you say today what you really think [about ...] – how likely is it that others contradict you ?

1. V. Unlikely

2. R. Unlikely

3. R. Likely

4. V. Likely

494	(	10.6%	)
1328	(	28.6%	)
2160	(	46.5%	)
660	(	14.2%	)

4642 (97.3%)

sancdisprob_insulting [labelled, factor]

Sanction Probability: Insulting (Discursive)
If you say today what you really think [about ...] – how likely is it that others feel wrongfully insulted ?

1. V. Unlikely

2. R. Unlikely

3. R. Likely

4. V. Likely

1087	(	23.4%	)
1793	(	38.6%	)
1384	(	29.8%	)
378	(	8.1%	)

4642 (97.3%)

sancdisprob_justifying [labelled, factor]

Sanction Probability: Justifying (Discursive)
If you say today what you really think [about ...] – how likely is it that you need to justify yourself ?

1. V. Unlikely

2. R. Unlikely

3. R. Likely

4. V. Likely

685	(	14.8%	)
1416	(	30.5%	)
1841	(	39.7%	)
700	(	15.1%	)

4642 (97.3%)

sancdisprob_hurting [labelled, factor]

Sanction Probability: Hurting (Discursive)
If you say today what you really think [about ...] – how likely is it that you hurt other people emotionally ?

1. V. Unlikely

2. R. Unlikely

3. R. Likely

4. V. Likely

1299	(	28.0%	)
2003	(	43.1%	)
1079	(	23.2%	)
261	(	5.6%	)

4642 (97.3%)

sancdisprob_misunderstood [labelled, factor]

Sanction Probability: Misunderstanding(Discursive)
If you say today what you really think [about ...] – how likely is it that you are misunderstood ?

1. V. Unlikely

2. R. Unlikely

3. R. Likely

4. V. Likely

724	(	15.6%	)
1585	(	34.1%	)
1786	(	38.5%	)
547	(	11.8%	)

4642 (97.3%)

sancdisexp_disagreement [labelled, factor]

Sanction Experience: Contradicting (Discursive)
How often have you yourself experienced the following things in the past after saying what you really think [about ...]?
Others contradicted me

1. Never

2. Once

3. Regularly

925	(	19.9%	)
2906	(	62.6%	)
814	(	17.5%	)

4645 (97.3%)

sancdisexp_insulting [labelled, factor]

Sanction Experience: Insulting (Discursive)
How often have you yourself experienced the following things in the past after saying what you really think [about ...]?
Others felt wrongfully insulted

1. Never

2. Once

3. Regularly

2259	(	48.6%	)
2026	(	43.6%	)
360	(	7.8%	)

4645 (97.3%)

sancdisexp_justifying [labelled, factor]

Sanction Experience: Justifying (Discursive)
How often have you yourself experienced the following things in the past after saying what you really think [about ...]?
I had to justify myself

1. Never

2. Once

3. Regularly

1390	(	29.9%	)
2531	(	54.5%	)
724	(	15.6%	)

4645 (97.3%)

sancdisexp_hurting [labelled, factor]

Sanction Experience: Hurting (Discursive)
How often have you yourself experienced the following things in the past after saying what you really think [about ...]?
I have hurt people emotionally

1. Never

2. Once

3. Regularly

2766	(	59.5%	)
1630	(	35.1%	)
249	(	5.4%	)

4645 (97.3%)

sancdisexp_misunderstood [labelled, factor]

Sanction Experience: Misunderstanding (Discursive)
How often have you yourself experienced the following things in the past after saying what you really think [about ...]?
I was misunderstood

1. Never

2. Once

3. Regularly

1331	(	28.7%	)
2671	(	57.5%	)
643	(	13.8%	)

4645 (97.3%)

sancsocprob_radical [labelled, factor]

Sanction Probability: Radical (Social)
If you say today what you really think [about ...] – how likely is it that others call you extreme or radical ?

1. V. Unlikely

2. R. Unlikely

3. R. Likely

4. V. Likely

1985	(	42.8%	)
1316	(	28.3%	)
927	(	20.0%	)
414	(	8.9%	)

4642 (97.3%)

sancsocprob_online [labelled, factor]

Sanction Probability: Online (Social)
If you say today what you really think [about ...] – how likely is it that you get personally attacked on social media (e.g. Facebook, Twitter) ?

1. V. Unlikely

2. R. Unlikely

3. R. Likely

4. V. Likely

1875	(	40.4%	)
1230	(	26.5%	)
1079	(	23.2%	)
458	(	9.9%	)

4642 (97.3%)

sancsocprob_falsepraise [labelled, factor]

Sanction Probability: False Praise (Social)
If you say today what you really think [about ...] – how likely is it that you are applauded by the wrong political side ?

1. V. Unlikely

2. R. Unlikely

3. R. Likely

4. V. Likely

1940	(	41.8%	)
1631	(	35.1%	)
841	(	18.1%	)
230	(	5.0%	)

4642 (97.3%)

sancsocprob_wronggroup [labelled, factor]

Sanction Probability: Wrong Group (Social)
If you say today what you really think [about ...] – how likely is it that others will associate you with a group you do not belong to ?

1. V. Unlikely

2. R. Unlikely

3. R. Likely

4. V. Likely

1572	(	33.9%	)
1473	(	31.7%	)
1155	(	24.9%	)
442	(	9.5%	)

4642 (97.3%)

sancsocexp_radical [labelled, factor]

Sanction Experience: Radical (Social)
How often have you yourself experienced the following things in the past after saying what you really think [about ...]?
Others called me extreme or radical

1. Never

2. Once

3. Regularly

3302	(	71.1%	)
1069	(	23.0%	)
272	(	5.9%	)

4643 (97.3%)

sancsocexp_online [labelled, factor]

Sanction Experience: Online (Social)
How often have you yourself experienced the following things in the past after saying what you really think [about ...]?
I was personally attacked on social media (e.g. Facebook, Twitter)

1. Never

2. Once

3. Regularly

3363	(	72.4%	)
1022	(	22.0%	)
258	(	5.6%	)

4643 (97.3%)

sancsocexp_falsepraise [labelled, factor]

Sanction Experience: False Praise (Social)
How often have you yourself experienced the following things in the past after saying what you really think [about ...]?
I was applauded by the wrong political side

1. Never

2. Once

3. Regularly

3694	(	79.6%	)
786	(	16.9%	)
163	(	3.5%	)

4643 (97.3%)

sancsocexp_wronggroup [labelled, factor]

Sanction Experience: Wrong Group (Social)
How often have you yourself experienced the following things in the past after saying what you really think [about ...]?
Others associated me with a group I do not belong to

1. Never

2. Once

3. Regularly

2775	(	59.8%	)
1537	(	33.1%	)
331	(	7.1%	)

4643 (97.3%)

sancclaprob_friends [labelled, factor]

Sanction Probability: Friends (Classical)
If you say today what you really think [about ...] – how likely is it that your friend will turn away from you ?

1. V. Unlikely

2. R. Unlikely

3. R. Likely

4. V. Likely

2361	(	50.9%	)
1537	(	33.1%	)
593	(	12.8%	)
147	(	3.2%	)

4638 (97.2%)

sancclaprob_job [labelled, factor]

Sanction Probability: Job (Classical)
If you say today what you really think [about ...] – how likely is it that it will hurt you professionally ?

1. V. Unlikely

2. R. Unlikely

3. R. Likely

4. V. Likely

2271	(	49.0%	)
1344	(	29.0%	)
747	(	16.1%	)
276	(	6.0%	)

4638 (97.2%)

sancclaprob_law [labelled, factor]

Sanction Probability: Law (Classical)
If you say today what you really think [about ...] – how likely is it that you get legal trouble ?

1. V. Unlikely

2. R. Unlikely

3. R. Likely

4. V. Likely

2394	(	51.6%	)
1357	(	29.3%	)
656	(	14.1%	)
231	(	5.0%	)

4638 (97.2%)

sancclaprob_harm [labelled, factor]

Sanction Probability: Harm (Classical)
If you say today what you really think [about ...] – how likely is it that you get physically attacked ?

1. V. Unlikely

2. R. Unlikely

3. R. Likely

4. V. Likely

2270	(	48.9%	)
1503	(	32.4%	)
673	(	14.5%	)
192	(	4.1%	)

4638 (97.2%)

sancclaexp_friends [labelled, factor]

Sanction Experience: Friends (Classical)
How often have you yourself experienced the following things in the past after saying what you really think [about ...]?
Friends have turned away from me

1. Never

2. Once

3. Regularly

3394	(	73.1%	)
1060	(	22.8%	)
187	(	4.0%	)

4641 (97.3%)

sancclaexp_job [labelled, factor]

Sanction Experience: Job (Classical)
How often have you yourself experienced the following things in the past after saying what you really think [about ...]?
It has hurt me professionally

1. Never

2. Once

3. Regularly

3743	(	80.7%	)
756	(	16.3%	)
142	(	3.1%	)

4641 (97.3%)

sancclaexp_law [labelled, factor]

Sanction Experience: Law (Classical)
How often have you yourself experienced the following things in the past after saying what you really think [about ...]?
I got legal troubles

1. Never

2. Once

3. Regularly

3991	(	86.0%	)
509	(	11.0%	)
141	(	3.0%	)

4641 (97.3%)

sancclaexp_harm [labelled, factor]

Sanction Experience: Harm (Classical)
How often have you yourself experienced the following things in the past after saying what you really think [about ...]?
I got physically attacked

1. Never

2. Once

3. Regularly

3857	(	83.1%	)
651	(	14.0%	)
133	(	2.9%	)

4641 (97.3%)

sanctdir_family [labelled, factor]

Sanctioners: Family (Direct)
Please indicate now to what extent you feel restricted in saying what you really think [about ...] by the following groups.
By your family

1. Not Restriced

2. R. Not Restricted

3. R. Restricted

4. Restricted

2993	(	65.3%	)
996	(	21.7%	)
450	(	9.8%	)
142	(	3.1%	)

4581 (96.0%)

sanctdir_friends [labelled, factor]

Sanctioners: Friends (Direct)
Please indicate now to what extent you feel restricted in saying what you really think [about ...] by the following groups.
By your friends

1. Not Restriced

2. R. Not Restricted

3. R. Restricted

4. Restricted

2905	(	63.4%	)
1171	(	25.6%	)
396	(	8.6%	)
109	(	2.4%	)

4581 (96.0%)

sanctdir_neighbor [labelled, factor]

Sanctioners: Neighbors (Direct)
Please indicate now to what extent you feel restricted in saying what you really think [about ...] by the following groups.
By your neighbors

1. Not Restriced

2. R. Not Restricted

3. R. Restricted

4. Restricted

2386	(	52.1%	)
1331	(	29.1%	)
696	(	15.2%	)
168	(	3.7%	)

4581 (96.0%)

sanctdir_boss [labelled, factor]

Sanctioners: Employer (Direct)
Please indicate now to what extent you feel restricted in saying what you really think [about ...] by the following groups.
By your employer/instructor

1. Not Restriced

2. R. Not Restricted

3. R. Restricted

4. Restricted

2321	(	50.7%	)
1163	(	25.4%	)
803	(	17.5%	)
294	(	6.4%	)

4581 (96.0%)

sanctdir_colleagues [labelled, factor]

Sanctioners: Colleagues (Direct)
Please indicate now to what extent you feel restricted in saying what you really think [about ...] by the following groups.
By your colleagues

1. Not Restriced

2. R. Not Restricted

3. R. Restricted

4. Restricted

2414	(	52.7%	)
1316	(	28.7%	)
667	(	14.6%	)
184	(	4.0%	)

4581 (96.0%)

sancteli_politics [labelled, factor]

Sanctioners: Politics (Elites)
Please indicate now to what extent you feel restricted in saying what you really think [about ...] by the following groups.
By politics

1. Not Restriced

2. R. Not Restricted

3. R. Restricted

4. Restricted

1532	(	33.5%	)
1066	(	23.3%	)
1172	(	25.6%	)
803	(	17.6%	)

4573 (95.8%)

sancteli_media [labelled, factor]

Sanctioners: Media (Elites)
Please indicate now to what extent you feel restricted in saying what you really think [about ...] by the following groups.
By the media

1. Not Restriced

2. R. Not Restricted

3. R. Restricted

4. Restricted

1721	(	37.6%	)
1193	(	26.1%	)
1052	(	23.0%	)
607	(	13.3%	)

4573 (95.8%)

sancteli_elites [labelled, factor]

Sanctioners: Elites (Elites)
Please indicate now to what extent you feel restricted in saying what you really think [about ...] by the following groups.
By the elite

1. Not Restriced

2. R. Not Restricted

3. R. Restricted

4. Restricted

1742	(	38.1%	)
1182	(	25.8%	)
1061	(	23.2%	)
588	(	12.9%	)

4573 (95.8%)

sancton_smcompany [labelled, factor]

Sanctioners: Operators (Online)
Please indicate now to what extent you feel restricted in saying what you really think [about ...] by the following groups.
By operators of social media sites (e.g. Facebook, Twitter)

1. Not Restriced

2. R. Not Restricted

3. R. Restricted

4. Restricted

2012	(	44.0%	)
1293	(	28.3%	)
855	(	18.7%	)
416	(	9.1%	)

4576 (95.9%)

sancton_smusers [labelled, factor]

Sanctioners: Users (Online)
Please indicate now to what extent you feel restricted in saying what you really think [about ...] by the following groups.
By other people on social media sites

1. Not Restriced

2. R. Not Restricted

3. R. Restricted

4. Restricted

1893	(	41.4%	)
1323	(	28.9%	)
996	(	21.8%	)
364	(	8.0%	)

4576 (95.9%)

sancton_smregulation [labelled, factor]

Sanctioners: State (Online)
Please indicate now to what extent you feel restricted in saying what you really think [about ...] by the following groups.
By state restrictions on social media sites

1. Not Restriced

2. R. Not Restricted

3. R. Restricted

4. Restricted

1913	(	41.8%	)
1222	(	26.7%	)
938	(	20.5%	)
503	(	11.0%	)

4576 (95.9%)

sanctpol_activists [labelled, factor]

Sanctioners: Activists (Political)
Please indicate now to what extent you feel restricted in saying what you really think [about ...] by the following groups.
By activists

1. Not Restriced

2. R. Not Restricted

3. R. Restricted

4. Restricted

1646	(	36.0%	)
1254	(	27.4%	)
1103	(	24.1%	)
570	(	12.5%	)

4573 (95.8%)

sanctpol_left [labelled, factor]

Sanctioners: Left (Political)
Please indicate now to what extent you feel restricted in saying what you really think [about ...] by the following groups.
By politically left individuals

1. Not Restriced

2. R. Not Restricted

3. R. Restricted

4. Restricted

1797	(	39.3%	)
1308	(	28.6%	)
944	(	20.6%	)
524	(	11.5%	)

4573 (95.8%)

sanctpol_right [labelled, factor]

Sanctioners: Right (Political)
Please indicate now to what extent you feel restricted in saying what you really think [about ...] by the following groups.
By politically right individuals

1. Not Restriced

2. R. Not Restricted

3. R. Restricted

4. Restricted

1637	(	35.8%	)
1242	(	27.2%	)
1102	(	24.1%	)
592	(	12.9%	)

4573 (95.8%)

(Self-)Censorship

Descriptive Overview

Variable

Label

Stats / Values

Freqs (% of Valid)

Graph

Valid

censself_hurting [labelled, factor]

Self-Censorship: Hurting
To what extent do you agree to the following statements?
Generally, I don’t voice my opinion when I think I could hurt others

1. Don't Agree

2. R. Don't Agree

3. Partially

4. R. Agree

5. Agree

433	(	10.0%	)
777	(	18.0%	)
1569	(	36.3%	)
1151	(	26.6%	)
395	(	9.1%	)

4325 (90.6%)

censself_majority [labelled, factor]

Self-Censorship: Majority
To what extent do you agree to the following statements?
I rather remain silent than publicly voicing an opinion that most do not share

1. Don't Agree

2. R. Don't Agree

3. Partially

4. R. Agree

5. Agree

597	(	13.8%	)
999	(	23.1%	)
1477	(	34.2%	)
881	(	20.4%	)
371	(	8.6%	)

4325 (90.6%)

censself_correcting [labelled, factor]

Self-Censorship: Correcting
To what extent do you agree to the following statements?
There are many times I thought others around me were wrong, but I did not let them know

1. Don't Agree

2. R. Don't Agree

3. Partially

4. R. Agree

5. Agree

390	(	9.0%	)
926	(	21.4%	)
1703	(	39.4%	)
987	(	22.8%	)
319	(	7.4%	)

4325 (90.6%)

censself_agreement [labelled, factor]

Self-Censorship: Agreement
To what extent do you agree to the following statements?
If I do not share other opinions, I rather agree to them than to fight about it

1. Don't Agree

2. R. Don't Agree

3. Partially

4. R. Agree

5. Agree

948	(	21.9%	)
1489	(	34.4%	)
1296	(	30.0%	)
465	(	10.8%	)
127	(	2.9%	)

4325 (90.6%)

censself_disagreement [labelled, factor]

Self-Censorship: Disagreement
To what extent do you agree to the following statements?
It is easy for me to voice my opinion in front of others who I think won’t agree with me
Item reversed in post-coding

1. Agree

2. R. Agree

3. Partially

4. R. Don't Agree

5. Don't Agree

527	(	12.2%	)
1267	(	29.3%	)
1549	(	35.8%	)
717	(	16.6%	)
265	(	6.1%	)

4325 (90.6%)

censoth_democracy [labelled, factor]

Censoring Others: Democracy To what extent do you agree to the following statements?
I have the desire to contradict people who say things that endanger our democracy

1. Don't Agree

2. R. Don't Agree

3. Partially

4. R. Agree

5. Agree

352	(	8.1%	)
484	(	11.2%	)
1340	(	31.0%	)
1355	(	31.3%	)
794	(	18.4%	)

4325 (90.6%)

censoth_silencing [labelled, factor]

Censoring Others: Silencing To what extent do you agree to the following statements?
Sometimes, certain viewpoints need to be silenced even in democracies

1. Don't Agree

2. R. Don't Agree

3. Partially

4. R. Agree

5. Agree

893	(	20.6%	)
925	(	21.4%	)
1506	(	34.8%	)
704	(	16.3%	)
297	(	6.9%	)

4325 (90.6%)

censoth_unacceptable [labelled, factor]

Censoring Others: Unacceptable To what extent do you agree to the following statements?
We cannot allow people who say inacceptable things to be heard

1. Don't Agree

2. R. Don't Agree

3. Partially

4. R. Agree

5. Agree

595	(	13.8%	)
771	(	17.8%	)
1526	(	35.3%	)
958	(	22.2%	)
475	(	11.0%	)

4325 (90.6%)

censoth_duty [labelled, factor]

Censoring Others: Duty To what extent do you agree to the following statements?
As citizen I have the duty to silence people with illegitimate political opinions

1. Don't Agree

2. R. Don't Agree

3. Partially

4. R. Agree

5. Agree

1457	(	33.7%	)
1164	(	26.9%	)
1162	(	26.9%	)
407	(	9.4%	)
135	(	3.1%	)

4325 (90.6%)

censoth_inform [labelled, factor]

Censoring Others: Inform To what extent do you agree to the following statements?
If people do not know that their opinion is hurtful for democracy, I have to tell them

1. Don't Agree

2. R. Don't Agree

3. Partially

4. R. Agree

5. Agree

442	(	10.2%	)
579	(	13.4%	)
1523	(	35.2%	)
1279	(	29.6%	)
502	(	11.6%	)

4325 (90.6%)

censself_mean [labelled, numeric]

Self-Censorship: Mean
Mean Score of the five 'Self-Censorship' items

Mean (sd) : 2.8 (0.7)

min ≤ med ≤ max:

1 ≤ 2.8 ≤ 5

IQR (CV) : 0.8 (0.3)

21 distinct values

4325 (90.6%)

censoth_mean [labelled, numeric]

Censoring Others: Mean
Mean Score of the five ‘Censoring Others’ items

Mean (sd) : 2.9 (0.8)

min ≤ med ≤ max:

1 ≤ 3 ≤ 5

IQR (CV) : 1 (0.3)

21 distinct values

4325 (90.6%)

Randomization Variables

Variables	Meaning
io_censself_hurting	Placement of ‘censself_hurting’ in ‘Self-Censorship’ question matrix
io_censself_majority	Placement of ‘censself_majority’ in ‘Self-Censorship’ question matrix
io_censself_correcting	Placement of ‘censself_correcting’ in ‘Self-Censorship’ question matrix
io_censself_agreement	Placement of ‘censself_agreement’ in ‘Self-Censorship’ question matrix
io_censself_disagreement	Placement of ‘censself_disagreement’ in ‘Self-Censorship’ question matrix
io_censoth_democracy	Placement of ‘censoth_democracy’ in ‘Willingness to Censor Others’ question matrix
io_censoth_silencing	Placement of ‘censoth_silencing’ in ‘Willingness to Censor Others’ question matrix
io_censoth_unacceptable	Placement of ‘censoth_unacceptable’ in ‘Willingness to Censor Others’ question matrix
io_censoth_duty	Placement of ‘censoth_duty’ in ‘Willingness to Censor Others’ question matrix
io_censoth_inform	Placement of ‘censoth_inform’ in ‘Willingness to Censor Others’ question matrix
qo_censself	Placement of ‘Self-Censorship’ question matrix in ‘Censorship’ module
qo_censoth	Placement of ‘Willingness to Censor Others’ question matrix in ‘Censorship’ module

De-Platforming

Descriptive Overview

Variable

Label

Stats / Values

Freqs (% of Valid)

Graph

Valid

deplat_advertising [labelled, factor]

De-Platforming: Advertising
How acceptable do you think it is to participate in the following actions to protest against a [controversial speaker / extreme right-wing speaker / extreme left-wing speaker / political opponent]?
Removing advertising for an event or talk of a [...]

1. Not Acceptable

2. R. Not Acceptable

3. Partially

4. R. Acceptable

5. Acceptable

1286	(	29.8%	)
1000	(	23.2%	)
1060	(	24.6%	)
591	(	13.7%	)
373	(	8.7%	)

4310 (90.3%)

deplat_electionposter [labelled, factor]

De-Platforming: Election Poster
How acceptable do you think it is to participate in the following actions to protest against a [controversial speaker / extreme right-wing speaker / extreme left-wing speaker / political opponent]?
Removing election posters a [...]
Not asked for 'controversial speaker' randomization

1. Not Acceptable

2. R. Not Acceptable

3. Partially

4. R. Acceptable

5. Acceptable

1172	(	36.5%	)
724	(	22.5%	)
666	(	20.7%	)
381	(	11.9%	)
269	(	8.4%	)

3212 (67.3%)

deplat_entering [labelled, factor]

De-Platforming: Entrance
How acceptable do you think it is to participate in the following actions to protest against a [controversial speaker / extreme right-wing speaker / extreme left-wing speaker / political opponent]?
Preventing other people from entering an event by a [...]

1. Not Acceptable

2. R. Not Acceptable

3. Partially

4. R. Acceptable

5. Acceptable

1723	(	40.0%	)
1085	(	25.2%	)
980	(	22.7%	)
341	(	7.9%	)
181	(	4.2%	)

4310 (90.3%)

deplat_screaming [labelled, factor]

De-Platforming: Screaming
How acceptable do you think it is to participate in the following actions to protest against a [controversial speaker / extreme right-wing speaker / extreme left-wing speaker / political opponent]?
Screaming down a [...] or preventing him to speak

1. Not Acceptable

2. R. Not Acceptable

3. Partially

4. R. Acceptable

5. Acceptable

1500	(	34.8%	)
1086	(	25.2%	)
1052	(	24.4%	)
449	(	10.4%	)
223	(	5.2%	)

4310 (90.3%)

deplat_violence [labelled, factor]

De-Platforming: Violence
How acceptable do you think it is to participate in the following actions to protest against a [controversial speaker / extreme right-wing speaker / extreme left-wing speaker / political opponent]?
Exercising physical violence to prevent a talk or event by a [...]

1. Not Acceptable

2. R. Not Acceptable

3. Partially

4. R. Acceptable

5. Acceptable

2845	(	66.0%	)
581	(	13.5%	)
553	(	12.8%	)
231	(	5.4%	)
100	(	2.3%	)

4310 (90.3%)

deplat_online [labelled, factor]

De-Platforming: Online
How acceptable do you think it is to participate in the following actions to protest against a [controversial speaker / extreme right-wing speaker / extreme left-wing speaker / political opponent]?
Reporting comments or posts of a [...] to site operators online

1. Not Acceptable

2. R. Not Acceptable

3. Partially

4. R. Acceptable

5. Acceptable

801	(	18.6%	)
641	(	14.9%	)
1230	(	28.5%	)
857	(	19.9%	)
781	(	18.1%	)

4310 (90.3%)

deplat_work [labelled, factor]

De-Platforming: Work
How acceptable do you think it is to participate in the following actions to protest against a [controversial speaker / extreme right-wing speaker / extreme left-wing speaker / political opponent]?
Reporting a [...] to his employer

1. Not Acceptable

2. R. Not Acceptable

3. Partially

4. R. Acceptable

5. Acceptable

1663	(	38.6%	)
1078	(	25.0%	)
964	(	22.4%	)
407	(	9.4%	)
198	(	4.6%	)

4310 (90.3%)

deplat_partners [labelled, factor]

De-Platforming: Partnerships
How acceptable do you think it is to participate in the following actions to protest against a [controversial speaker / extreme right-wing speaker / extreme left-wing speaker / political opponent]?
Demanding that companies do not cooperate with a [...]

1. Not Acceptable

2. R. Not Acceptable

3. Partially

4. R. Acceptable

5. Acceptable

1141	(	26.5%	)
851	(	19.7%	)
1185	(	27.5%	)
724	(	16.8%	)
409	(	9.5%	)

4310 (90.3%)

deplat_mean [labelled, numeric]

De-Platforming: Mean
Mean Score of the ‘De-Platforming’ items

Mean (sd) : 2.3 (0.9)

min ≤ med ≤ max:

1 ≤ 2.2 ≤ 5

IQR (CV) : 1.5 (0.4)

33 distinct values

3212 (67.3%)

Randomization Variables

Note: When evaluating the item order randomizations, consider that item “deplat_electionposter” was not asked for those who received the ‘controversial speaker’ as a randomized target of the de-platforming measures.

Variables	Meaning
deplat_target	Randomized Target of De-Platforming Measures
io_deplat_advertising	Placement of ‘deplat_advertising’ in ‘De-Platforming’ question matrix
io_deplat_electionposter	Placement of ‘deplat_electionposter’ in ‘De-Platforming’ question matrix
io_deplat_entering	Placement of ‘deplat_entering’ in ‘De-Platforming’ question matrix
io_deplat_screaming	Placement of ‘deplat_screaming’ in ‘De-Platforming’ question matrix
io_deplat_violence	Placement of ‘deplat_violence’ in ‘De-Platforming’ question matrix
io_deplat_online	Placement of ‘deplat_online’ in ‘De-Platforming’ question matrix
io_deplat_work	Placement of ‘deplat_work’ in ‘De-Platforming’ question matrix
io_deplat_partners	Placement of ‘deplat_partners’ in ‘De-Platforming’ question matrix

Descriptive Overview split by De-Platforming Target

Group: deplat_target = Controversial

Variable

Label

Stats / Values

Freqs (% of Valid)

Graph

Valid

deplat_advertising [labelled, factor]

1. Not Acceptable

2. R. Not Acceptable

3. Partially

4. R. Acceptable

5. Acceptable

296	(	27.0%	)
261	(	23.8%	)
304	(	27.7%	)
168	(	15.3%	)
69	(	6.3%	)

1098 (90.1%)

deplat_electionposter [labelled, factor]

1. Not Acceptable

2. R. Not Acceptable

3. Partially

4. R. Acceptable

5. Acceptable

All NA's

0 (0.0%)

deplat_entering [labelled, factor]

1. Not Acceptable

2. R. Not Acceptable

3. Partially

4. R. Acceptable

5. Acceptable

415	(	37.8%	)
278	(	25.3%	)
273	(	24.9%	)
98	(	8.9%	)
34	(	3.1%	)

1098 (90.1%)

deplat_screaming [labelled, factor]

1. Not Acceptable

2. R. Not Acceptable

3. Partially

4. R. Acceptable

5. Acceptable

382	(	34.8%	)
274	(	25.0%	)
288	(	26.2%	)
113	(	10.3%	)
41	(	3.7%	)

1098 (90.1%)

deplat_violence [labelled, factor]

1. Not Acceptable

2. R. Not Acceptable

3. Partially

4. R. Acceptable

5. Acceptable

698	(	63.6%	)
164	(	14.9%	)
148	(	13.5%	)
64	(	5.8%	)
24	(	2.2%	)

1098 (90.1%)

deplat_online [labelled, factor]

1. Not Acceptable

2. R. Not Acceptable

3. Partially

4. R. Acceptable

5. Acceptable

177	(	16.1%	)
172	(	15.7%	)
339	(	30.9%	)
222	(	20.2%	)
188	(	17.1%	)

1098 (90.1%)

deplat_work [labelled, factor]

1. Not Acceptable

2. R. Not Acceptable

3. Partially

4. R. Acceptable

5. Acceptable

397	(	36.2%	)
299	(	27.2%	)
274	(	25.0%	)
92	(	8.4%	)
36	(	3.3%	)

1098 (90.1%)

deplat_partners [labelled, factor]

1. Not Acceptable

2. R. Not Acceptable

3. Partially

4. R. Acceptable

5. Acceptable

257	(	23.4%	)
216	(	19.7%	)
349	(	31.8%	)
200	(	18.2%	)
76	(	6.9%	)

1098 (90.1%)

deplat_mean [labelled, numeric]

De-Platforming: Mean
Mean Score of the ‘De-Platforming’ items

All NA's

0 (0.0%)

Group: deplat_target = Extreme Left

Variable

Label

Stats / Values

Freqs (% of Valid)

Graph

Valid

deplat_advertising [labelled, factor]

1. Not Acceptable

2. R. Not Acceptable

3. Partially

4. R. Acceptable

5. Acceptable

314	(	28.7%	)
270	(	24.7%	)
291	(	26.6%	)
129	(	11.8%	)
91	(	8.3%	)

1095 (89.7%)

deplat_electionposter [labelled, factor]

1. Not Acceptable

2. R. Not Acceptable

3. Partially

4. R. Acceptable

5. Acceptable

371	(	33.9%	)
276	(	25.2%	)
240	(	21.9%	)
125	(	11.4%	)
83	(	7.6%	)

1095 (89.7%)

deplat_entering [labelled, factor]

1. Not Acceptable

2. R. Not Acceptable

3. Partially

4. R. Acceptable

5. Acceptable

437	(	39.9%	)
293	(	26.8%	)
240	(	21.9%	)
79	(	7.2%	)
46	(	4.2%	)

1095 (89.7%)

deplat_screaming [labelled, factor]

1. Not Acceptable

2. R. Not Acceptable

3. Partially

4. R. Acceptable

5. Acceptable

354	(	32.3%	)
306	(	27.9%	)
265	(	24.2%	)
107	(	9.8%	)
63	(	5.8%	)

1095 (89.7%)

deplat_violence [labelled, factor]

1. Not Acceptable

2. R. Not Acceptable

3. Partially

4. R. Acceptable

5. Acceptable

695	(	63.5%	)
147	(	13.4%	)
155	(	14.2%	)
68	(	6.2%	)
30	(	2.7%	)

1095 (89.7%)

deplat_online [labelled, factor]

1. Not Acceptable

2. R. Not Acceptable

3. Partially

4. R. Acceptable

5. Acceptable

208	(	19.0%	)
169	(	15.4%	)
335	(	30.6%	)
219	(	20.0%	)
164	(	15.0%	)

1095 (89.7%)

deplat_work [labelled, factor]

1. Not Acceptable

2. R. Not Acceptable

3. Partially

4. R. Acceptable

5. Acceptable

414	(	37.8%	)
290	(	26.5%	)
249	(	22.7%	)
97	(	8.9%	)
45	(	4.1%	)

1095 (89.7%)

deplat_partners [labelled, factor]

1. Not Acceptable

2. R. Not Acceptable

3. Partially

4. R. Acceptable

5. Acceptable

306	(	27.9%	)
240	(	21.9%	)
300	(	27.4%	)
169	(	15.4%	)
80	(	7.3%	)

1095 (89.7%)

deplat_mean [labelled, numeric]

De-Platforming: Mean
Mean Score of the ‘De-Platforming’ items

Mean (sd) : 2.3 (0.9)

min ≤ med ≤ max:

1 ≤ 2.2 ≤ 5

IQR (CV) : 1.4 (0.4)

33 distinct values

1095 (89.7%)

Group: deplat_target = Extreme Right

Variable

Label

Stats / Values

Freqs (% of Valid)

Graph

Valid

deplat_advertising [labelled, factor]

1. Not Acceptable

2. R. Not Acceptable

3. Partially

4. R. Acceptable

5. Acceptable

211	(	20.7%	)
195	(	19.2%	)
245	(	24.1%	)
195	(	19.2%	)
172	(	16.9%	)

1018 (90.9%)

deplat_electionposter [labelled, factor]

1. Not Acceptable

2. R. Not Acceptable

3. Partially

4. R. Acceptable

5. Acceptable

271	(	26.6%	)
205	(	20.1%	)
238	(	23.4%	)
157	(	15.4%	)
147	(	14.4%	)

1018 (90.9%)

deplat_entering [labelled, factor]

1. Not Acceptable

2. R. Not Acceptable

3. Partially

4. R. Acceptable

5. Acceptable

328	(	32.2%	)
251	(	24.7%	)
266	(	26.1%	)
96	(	9.4%	)
77	(	7.6%	)

1018 (90.9%)

deplat_screaming [labelled, factor]

1. Not Acceptable

2. R. Not Acceptable

3. Partially

4. R. Acceptable

5. Acceptable

274	(	26.9%	)
231	(	22.7%	)
276	(	27.1%	)
144	(	14.1%	)
93	(	9.1%	)

1018 (90.9%)

deplat_violence [labelled, factor]

1. Not Acceptable

2. R. Not Acceptable

3. Partially

4. R. Acceptable

5. Acceptable

663	(	65.1%	)
168	(	16.5%	)
121	(	11.9%	)
47	(	4.6%	)
19	(	1.9%	)

1018 (90.9%)

deplat_online [labelled, factor]

1. Not Acceptable

2. R. Not Acceptable

3. Partially

4. R. Acceptable

5. Acceptable

145	(	14.2%	)
91	(	8.9%	)
223	(	21.9%	)
225	(	22.1%	)
334	(	32.8%	)

1018 (90.9%)

deplat_work [labelled, factor]

1. Not Acceptable

2. R. Not Acceptable

3. Partially

4. R. Acceptable

5. Acceptable

277	(	27.2%	)
241	(	23.7%	)
252	(	24.8%	)
156	(	15.3%	)
92	(	9.0%	)

1018 (90.9%)

deplat_partners [labelled, factor]

1. Not Acceptable

2. R. Not Acceptable

3. Partially

4. R. Acceptable

5. Acceptable

192	(	18.9%	)
141	(	13.9%	)
256	(	25.1%	)
215	(	21.1%	)
214	(	21.0%	)

1018 (90.9%)

deplat_mean [labelled, numeric]

De-Platforming: Mean
Mean Score of the ‘De-Platforming’ items

Mean (sd) : 2.7 (0.9)

min ≤ med ≤ max:

1 ≤ 2.8 ≤ 5

IQR (CV) : 1.2 (0.4)

32 distinct values

1018 (90.9%)

Group: deplat_target = Political Opponent

Variable

Label

Stats / Values

Freqs (% of Valid)

Graph

Valid

deplat_advertising [labelled, factor]

1. Not Acceptable

2. R. Not Acceptable

3. Partially

4. R. Acceptable

5. Acceptable

465	(	42.3%	)
274	(	24.9%	)
220	(	20.0%	)
99	(	9.0%	)
41	(	3.7%	)

1099 (90.7%)

deplat_electionposter [labelled, factor]

1. Not Acceptable

2. R. Not Acceptable

3. Partially

4. R. Acceptable

5. Acceptable

530	(	48.2%	)
243	(	22.1%	)
188	(	17.1%	)
99	(	9.0%	)
39	(	3.5%	)

1099 (90.7%)

deplat_entering [labelled, factor]

1. Not Acceptable

2. R. Not Acceptable

3. Partially

4. R. Acceptable

5. Acceptable

543	(	49.4%	)
263	(	23.9%	)
201	(	18.3%	)
68	(	6.2%	)
24	(	2.2%	)

1099 (90.7%)

deplat_screaming [labelled, factor]

1. Not Acceptable

2. R. Not Acceptable

3. Partially

4. R. Acceptable

5. Acceptable

490	(	44.6%	)
275	(	25.0%	)
223	(	20.3%	)
85	(	7.7%	)
26	(	2.4%	)

1099 (90.7%)

deplat_violence [labelled, factor]

1. Not Acceptable

2. R. Not Acceptable

3. Partially

4. R. Acceptable

5. Acceptable

789	(	71.8%	)
102	(	9.3%	)
129	(	11.7%	)
52	(	4.7%	)
27	(	2.5%	)

1099 (90.7%)

deplat_online [labelled, factor]

1. Not Acceptable

2. R. Not Acceptable

3. Partially

4. R. Acceptable

5. Acceptable

271	(	24.7%	)
209	(	19.0%	)
333	(	30.3%	)
191	(	17.4%	)
95	(	8.6%	)

1099 (90.7%)

deplat_work [labelled, factor]

1. Not Acceptable

2. R. Not Acceptable

3. Partially

4. R. Acceptable

5. Acceptable

575	(	52.3%	)
248	(	22.6%	)
189	(	17.2%	)
62	(	5.6%	)
25	(	2.3%	)

1099 (90.7%)

deplat_partners [labelled, factor]

1. Not Acceptable

2. R. Not Acceptable

3. Partially

4. R. Acceptable

5. Acceptable

386	(	35.1%	)
254	(	23.1%	)
280	(	25.5%	)
140	(	12.7%	)
39	(	3.5%	)

1099 (90.7%)

deplat_mean [labelled, numeric]

De-Platforming: Mean
Mean Score of the ‘De-Platforming’ items

Mean (sd) : 2 (0.9)

min ≤ med ≤ max:

1 ≤ 1.9 ≤ 5

IQR (CV) : 1.5 (0.4)

32 distinct values

1099 (90.7%)

Conjoint Experiment: Allowed to say

Variables

Note: There were ten randomized conjoint statements to which support was surveyed binary (with ave. agreement around 60 %). The variables for all ten iterations follow the same logic as the one presented below (replacing “1” with the numbers “2” to “10”).

Example Statement with randomization variable labels in brackets: Ein männlicher [Female] Politiker [Speaker ID], der regelmäßg [Frequency] Homosexuelle [Target ID & Targetgroup] im Internet [Context] bedroht [Content], sollte eine Geldstrafe zahlen müssen [Response], wenn diese Gruppe sich beleidigt fühlt [Reaction].

Variables	Meaning
	OUTCOME VARIABLES
conj1	Agreement with the statement
	RANDOMIZED ATTRIBUTES
conj1_speakerfemale	Whether speaker is female or not
conj1_speakerid	The speaker’s social identity
conj1_targetgroup	Whether the target is a group or a singular person
conj1_targetsex	If a singular person, the target’s sex
conj1_targetid	The target’s social identity
conj1_context	In which social context the situation is placed
conj1_response	Which sanction the speaker should face
conj1_frequency	How often the situation occurs
conj1_content	What the speaker effectively says
conj1_reaction	How the target reacts

Conservatism, Socialism, Liberalism

Descriptive Overview

Variable

Label

Stats / Values

Freqs (% of Valid)

Graph

Valid

cons_maintain [labelled, factor]

Conservatism
To what extent do you agree or disagree with the following statements
The state should mostly focus on the preservation of the common culture and traditions

1. Don't Agree

2. R. Don't Agree

3. Partially

4. R. Agree

5. Agree

257	(	5.8%	)
589	(	13.4%	)
1472	(	33.5%	)
1272	(	28.9%	)
806	(	18.3%	)

4396 (92.1%)

cons_together [labelled, factor]

Conservatism
To what extent do you agree or disagree with the following statements
Above all out common culture holds the country together

1. Don't Agree

2. R. Don't Agree

3. Partially

4. R. Agree

5. Agree

293	(	6.7%	)
629	(	14.3%	)
1454	(	33.1%	)
1210	(	27.5%	)
810	(	18.4%	)

4396 (92.1%)

cons_important [labelled, factor]

Conservatism
To what extent do you agree or disagree with the following statements
It's not important for me to confirm with common values and traditions
Item reversed in post-coding

1. Agree

2. R. Agree

3. Partially

4. R. Don't Agree

5. Don't Agree

573	(	13.0%	)
910	(	20.7%	)
1260	(	28.7%	)
868	(	19.7%	)
785	(	17.9%	)

4396 (92.1%)

cons_mean [labelled, numeric]

Conservatism: Mean
Mean Score of the three 'Conservatism' items

Mean (sd) : 3.3 (0.8)

min ≤ med ≤ max:

1 ≤ 3.3 ≤ 5

IQR (CV) : 1 (0.2)

13 distinct values

4396 (92.1%)

soc_equality [labelled, factor]

Socialism
To what extent do you agree or disagree with the following statements
It is fair when all groups in society receive equal standing

1. Don't Agree

2. R. Don't Agree

3. Partially

4. R. Agree

5. Agree

236	(	5.4%	)
430	(	9.8%	)
1162	(	26.4%	)
1211	(	27.5%	)
1359	(	30.9%	)

4398 (92.2%)

soc_empathy [labelled, factor]

Socialism
To what extent do you agree or disagree with the following statements
It is not important to me to show empathy with those who have it hard
Item reversed in post-coding

1. Agree

2. R. Agree

3. Partially

4. R. Don't Agree

5. Don't Agree

551	(	12.5%	)
911	(	20.7%	)
1075	(	24.4%	)
856	(	19.5%	)
1005	(	22.9%	)

4398 (92.2%)

soc_income [labelled, factor]

Socialism
To what extent do you agree or disagree with the following statements
Most differences in income are unfair, because all people are equal

1. Don't Agree

2. R. Don't Agree

3. Partially

4. R. Agree

5. Agree

431	(	9.8%	)
732	(	16.6%	)
1300	(	29.6%	)
1035	(	23.5%	)
900	(	20.5%	)

4398 (92.2%)

soc_mean [labelled, numeric]

Socialism: Mean
Mean Score of the three 'Socialism' items

Mean (sd) : 3.4 (0.8)

min ≤ med ≤ max:

1 ≤ 3.3 ≤ 5

IQR (CV) : 1 (0.2)

13 distinct values

4398 (92.2%)

lib_protection [labelled, factor]

Liberalism
To what extent do you agree or disagree with the following statements
It is the government's task to try to rescue people from themselves
Item reversed in post-coding

1. Agree

2. R. Agree

3. Partially

4. R. Don't Agree

5. Don't Agree

358	(	8.1%	)
910	(	20.7%	)
1820	(	41.4%	)
781	(	17.8%	)
526	(	12.0%	)

4395 (92.1%)

lib_interference [labelled, factor]

Liberalism
To what extent do you agree or disagree with the following statements
The government should stop telling people how to live their life

1. Don't Agree

2. R. Don't Agree

3. Partially

4. R. Agree

5. Agree

218	(	5.0%	)
454	(	10.3%	)
1335	(	30.4%	)
1107	(	25.2%	)
1281	(	29.1%	)

4395 (92.1%)

lib_intervention [labelled, factor]

Liberalism
To what extent do you agree or disagree with the following statements
The government interferes way too much with our everyday life

1. Don't Agree

2. R. Don't Agree

3. Partially

4. R. Agree

5. Agree

318	(	7.2%	)
804	(	18.3%	)
1342	(	30.5%	)
969	(	22.0%	)
962	(	21.9%	)

4395 (92.1%)

lib_mean [labelled, numeric]

Liberalism: Mean
Mean Score of the three 'Liberalism' items

Mean (sd) : 3.3 (0.8)

min ≤ med ≤ max:

1 ≤ 3.3 ≤ 5

IQR (CV) : 1.3 (0.2)

13 distinct values

4395 (92.1%)

Randomization Variables

Variables	Meaning
io_cons_maintain	Placement of ‘cons_maintain’ in ‘Conservatism’ question matrix
io_cons_together	Placement of ‘cons_together’ in ‘Conservatism’ question matrix
io_cons_important	Placement of ‘cons_important’ in ‘Conservatism’ question matrix
io_soc_equality	Placement of ‘soc_equality’ in ‘Socialism’ question matrix
io_soc_empathy	Placement of ‘soc_empathy’ in ‘Socialism’ question matrix
io_soc_income	Placement of ‘soc_income’ in ‘Socialism’ question matrix
io_lib_protection	Placement of ‘lib_protection’ in ‘Liberalism’ question matrix
io_lib_interference	Placement of ‘lib_interference’ in ‘Liberalism’ question matrix
io_lib_intervention	Placement of ‘lib_intervention’ in ‘Liberalism’ question matrix
qo_cons	Placement of ‘Conservatism’ question matrix in survey block order
qo_soc	Placement of ‘Socialism’ question matrix in survey block order
qo_lib	Placement of ‘Liberalism’ question matrix in survey block order

Political Variables

Descriptive Overview

Variable

Label

Stats / Values

Freqs (% of Valid)

Graph

Valid

polint [labelled, factor]

Political Interest
Generally speaking: How strongly are you interested in politics?

1. Not at all

2. Less Strongly

3. Medium

4. Strongly

5. Very Strongly

190	(	4.5%	)
458	(	10.8%	)
1412	(	33.4%	)
1435	(	34.0%	)
730	(	17.3%	)

4225 (88.5%)

efficacy_understanding [labelled, factor]

Political Efficacy: Understanding
Now it is about your judgement of political questions. You can more or less agree to the following statements. To what extent do you agree with the singular statements?
I can understand and assess important political questions well

1. Don't Agree

2. R. Don't Agree

3. R. Agree

4. Agree

160	(	3.8%	)
735	(	17.4%	)
2330	(	55.2%	)
997	(	23.6%	)

4222 (88.5%)

efficacy_talking [labelled, factor]

Political Efficacy: Talking
Now it is about your judgement of political questions. You can more or less agree to the following statements. To what extent do you agree with the singular statements?
I trust myself to actively participate in a conversation about political questions

1. Don't Agree

2. R. Don't Agree

3. R. Agree

4. Agree

309	(	7.3%	)
931	(	22.1%	)
1962	(	46.5%	)
1020	(	24.2%	)

4222 (88.5%)

efficacy_complexity [labelled, factor]

Political Efficacy: Complexity
Now it is about your judgement of political questions. You can more or less agree to the following statements. To what extent do you agree with the singular statements?
Complex political questions are often hard for me to understand
Item reversed in post-coding

1. Agree

2. R. Agree

3. R. Don't Agree

4. Don't Agree

379	(	9.0%	)
1344	(	31.8%	)
1708	(	40.5%	)
791	(	18.7%	)

4222 (88.5%)

efficacy_mean [labelled, numeric]

Political Efficacy: Mean
Mean Score of the three ‘Political Efficacy’ items

Mean (sd) : 2.9 (0.7)

min ≤ med ≤ max:

1 ≤ 3 ≤ 4

IQR (CV) : 1 (0.2)

10 distinct values

4222 (88.5%)

ego_lr [labelled, numeric]

Ego Position: Left-Right
In politics people often talk about 'left' and 'right'. Where would you locate yourself on a scale in which 0 stands for left and 10 stands for right?
0 = Left; 10 = Right

Mean (sd) : 4.8 (2)

min ≤ med ≤ max:

0 ≤ 5 ≤ 10

IQR (CV) : 3 (0.4)

11 distinct values

3691 (77.3%)

ego_imm [labelled, numeric]

Ego Position: Immigration
And what is your opinion towards the topic of immigration?
0 = Make immigration easier; 10 = Make immigration more difficult

Mean (sd) : 5.6 (3)

min ≤ med ≤ max:

0 ≤ 5 ≤ 10

IQR (CV) : 5 (0.5)

11 distinct values

4197 (88.0%)

ego_tax [labelled, numeric]

Ego Position: Tax & Welfare
And what is your opinion towards the topic of taxes and social benefits?
0 = More Taxes and Social Benefits; 10 = Less Taxes and Social Benefits

Mean (sd) : 5.5 (2.6)

min ≤ med ≤ max:

0 ≤ 5 ≤ 10

IQR (CV) : 3 (0.5)

11 distinct values

4200 (88.0%)

ego_clim [labelled, numeric]

Ego Position: Climate Change
And what is your opinion towards the topic of fighting against climate change?
0 = Politics should do more against climate change; 10 = Politics should do less against climate change

Mean (sd) : 3.1 (2.7)

min ≤ med ≤ max:

0 ≤ 3 ≤ 10

IQR (CV) : 4 (0.9)

11 distinct values

4199 (88.0%)

Randomization Variables

Variables	Meaning
io_efficacy_understanding	Placement of ‘efficacy_understanding’ in ‘Internal Efficacy’ question matrix
io_efficacy_talking	Placement of ‘efficacy_talking’ in ‘Internal Efficacy’ question matrix
io_efficacy_complexity	Placement of ‘efficacy_complexity’ in ‘Internal Efficacy’ question matrix
io_ego_clim	Placement of ‘ego_clim’ in ‘Political Positions’ block
io_ego_tax	Placement of ‘ego_tax’ in ‘Political Positions’ block
io_ego_cimm	Placement of ‘ego_imm’ in ‘Political Positions’ block

Racism, Sexism

Descriptive Overview

Variable

Label

Stats / Values

Freqs (% of Valid)

Graph

Valid

prejudice_type [factor]

1. Racism

2. Sexism

2430	(	50.9%	)
2342	(	49.1%	)

4772 (100.0%)

prejudice_meaning [labelled, factor]

Prejudice: Meaning
Imagine you are talking to a good acquaintance. In the conversation, your acquaintance voices the opinions below. Please tell me, whether you would agree to the singular opinions of your acquaintance or not.
To know whether a statement is [ prejudice type ], I need to know how the statement was meant

1. Don't Agree

2. R. Don't Agree

3. Partially

4. R. Agree

5. Agree

289	(	6.8%	)
507	(	12.0%	)
1147	(	27.0%	)
1422	(	33.5%	)
877	(	20.7%	)

4242 (88.9%)

prejudice_reaction [labelled, factor]

Prejudice: Reaction
Imagine you are talking to a good acquaintance. In the conversation, your acquaintance voices the opinions below. Please tell me, whether you would agree to the singular opinions of your acquaintance or not.
To know whether a statement is [ prejudice type ], I need to whether someone feels hurt by it

1. Don't Agree

2. R. Don't Agree

3. Partially

4. R. Agree

5. Agree

739	(	17.4%	)
995	(	23.5%	)
1207	(	28.5%	)
913	(	21.5%	)
388	(	9.1%	)

4242 (88.9%)

prejudice_society [labelled, factor]

Prejudice: Society
Imagine you are talking to a good acquaintance. In the conversation, your acquaintance voices the opinions below. Please tell me, whether you would agree to the singular opinions of your acquaintance or not.
We live in a [ prejudice type ] society

1. Don't Agree

2. R. Don't Agree

3. Partially

4. R. Agree

5. Agree

346	(	8.2%	)
634	(	14.9%	)
1589	(	37.5%	)
1180	(	27.8%	)
493	(	11.6%	)

4242 (88.9%)

prejudice_words [labelled, factor]

Prejudice: Words
Imagine you are talking to a good acquaintance. In the conversation, your acquaintance voices the opinions below. Please tell me, whether you would agree to the singular opinions of your acquaintance or not.
[ Prejudice type ] words are just as hurtful as [ prejudice type ] actions

1. Don't Agree

2. R. Don't Agree

3. Partially

4. R. Agree

5. Agree

238	(	5.6%	)
426	(	10.0%	)
1042	(	24.6%	)
1279	(	30.2%	)
1257	(	29.6%	)

4242 (88.9%)

racism_open_intelligence [labelled, factor]

Open Racism: Intelligence
To what extent do you agree or disagree with the following statements?
All ethnic groups are equally intelligent
Item reversed in post-coding

1. Agree

2. R. Agree

3. Partially

4. R. Don't Agree

5. Don't Agree

1241	(	29.2%	)
925	(	21.8%	)
1165	(	27.4%	)
514	(	12.1%	)
401	(	9.4%	)

4246 (89.0%)

racism_open_better [labelled, factor]

Open Racism: Superiority
To what extent do you agree or disagree with the following statements?
Some cultures are just better than others

1. Don't Agree

2. R. Don't Agree

3. Partially

4. R. Agree

5. Agree

1413	(	33.3%	)
729	(	17.2%	)
1164	(	27.4%	)
626	(	14.7%	)
314	(	7.4%	)

4246 (89.0%)

racism_open_industrious [labelled, factor]

Open Racism: Industrious
To what extent do you agree or disagree with the following statements?
By nature, certain ethnic groups are less industrious than others

1. Don't Agree

2. R. Don't Agree

3. Partially

4. R. Agree

5. Agree

1229	(	28.9%	)
794	(	18.7%	)
1127	(	26.5%	)
728	(	17.1%	)
368	(	8.7%	)

4246 (89.0%)

racism_meaning [labelled, factor]

Racism: Meaning
Imagine you are talking to a good acquaintance. In the conversation, your acquaintance voices the opinions below. Please tell me, whether you would agree to the singular opinions of your acquaintance or not.
To know whether a statement is racists, I need to know how the statement was meant

1. Don't Agree

2. R. Don't Agree

3. Partially

4. R. Agree

5. Agree

133	(	6.2%	)
237	(	11.0%	)
570	(	26.4%	)
743	(	34.4%	)
478	(	22.1%	)

2161 (45.3%)

racism_reaction [labelled, factor]

Racism: Reaction
Imagine you are talking to a good acquaintance. In the conversation, your acquaintance voices the opinions below. Please tell me, whether you would agree to the singular opinions of your acquaintance or not.
To know whether a statement is racists, I need to whether someone feels hurt by it

1. Don't Agree

2. R. Don't Agree

3. Partially

4. R. Agree

5. Agree

396	(	18.3%	)
498	(	23.0%	)
616	(	28.5%	)
446	(	20.6%	)
205	(	9.5%	)

2161 (45.3%)

racism_society [labelled, factor]

Racism: Society
Imagine you are talking to a good acquaintance. In the conversation, your acquaintance voices the opinions below. Please tell me, whether you would agree to the singular opinions of your acquaintance or not.
We live in a racist society

1. Don't Agree

2. R. Don't Agree

3. Partially

4. R. Agree

5. Agree

197	(	9.1%	)
353	(	16.3%	)
833	(	38.5%	)
565	(	26.1%	)
213	(	9.9%	)

2161 (45.3%)

racism_words [labelled, factor]

Racism: Words
Imagine you are talking to a good acquaintance. In the conversation, your acquaintance voices the opinions below. Please tell me, whether you would agree to the singular opinions of your acquaintance or not.
Racist words are just as hurtful as racist actions

1. Don't Agree

2. R. Don't Agree

3. Partially

4. R. Agree

5. Agree

90	(	4.2%	)
157	(	7.3%	)
504	(	23.3%	)
642	(	29.7%	)
768	(	35.5%	)

2161 (45.3%)

racism_open_mean [labelled, numeric]

Open Racism: Mean
Mean Score of the three ‘Open Racism’ items

Mean (sd) : 2.5 (1)

min ≤ med ≤ max:

1 ≤ 2.7 ≤ 5

IQR (CV) : 1.7 (0.4)

13 distinct values

4246 (89.0%)

sexism_meaning [labelled, factor]

Sexism: Meaning
Imagine you are talking to a good acquaintance. In the conversation, your acquaintance voices the opinions below. Please tell me, whether you would agree to the singular opinions of your acquaintance or not.
To know whether a statement is sexist, I need to know how the statement was meant

1. Don't Agree

2. R. Don't Agree

3. Partially

4. R. Agree

5. Agree

156	(	7.5%	)
270	(	13.0%	)
577	(	27.7%	)
679	(	32.6%	)
399	(	19.2%	)

2081 (43.6%)

sexism_reaction [labelled, factor]

Sexism: Reaction
Imagine you are talking to a good acquaintance. In the conversation, your acquaintance voices the opinions below. Please tell me, whether you would agree to the singular opinions of your acquaintance or not.
To know whether a statement is sexist, I need to whether someone feels hurt by it

1. Don't Agree

2. R. Don't Agree

3. Partially

4. R. Agree

5. Agree

343	(	16.5%	)
497	(	23.9%	)
591	(	28.4%	)
467	(	22.4%	)
183	(	8.8%	)

2081 (43.6%)

sexism_society [labelled, factor]

Sexism: Society
Imagine you are talking to a good acquaintance. In the conversation, your acquaintance voices the opinions below. Please tell me, whether you would agree to the singular opinions of your acquaintance or not.
We live in a sexist society

1. Don't Agree

2. R. Don't Agree

3. Partially

4. R. Agree

5. Agree

149	(	7.2%	)
281	(	13.5%	)
756	(	36.3%	)
615	(	29.6%	)
280	(	13.5%	)

2081 (43.6%)

sexism_words [labelled, factor]

Sexism: Words
Imagine you are talking to a good acquaintance. In the conversation, your acquaintance voices the opinions below. Please tell me, whether you would agree to the singular opinions of your acquaintance or not.
Sexist words are just as hurtful as sexist actions

1. Don't Agree

2. R. Don't Agree

3. Partially

4. R. Agree

5. Agree

148	(	7.1%	)
269	(	12.9%	)
538	(	25.9%	)
637	(	30.6%	)
489	(	23.5%	)

2081 (43.6%)

Randomization Variables

Variables	Meaning
prejudice_type	Randomized Prejudice Type
io_racism_open_intelligence	Placement of ‘racism_open_intelligence’ in ‘Open Racism’ question matrix
io_racism_open_better	Placement of ‘racism_open_better’ in ‘Open Racism’ question matrix
io_racism_open_industrious	Placement of ‘racism_open_industrious’ in ‘Open Racism’ question matrix
io_racism_meaning	Placement of ‘racism_meaning’ in ‘Racism’ question matrix
io_racism_reaction	Placement of ‘racism_reaction’ in ‘Racism’ question matrix
io_racism_society	Placement of ‘racism_society’ in ‘Racism’ question matrix
io_racism_words	Placement of ‘racism_words’ in ‘Racism’ question matrix
io_sexism_meaning	Placement of ‘sexism_meaning’ in ‘Sexism’ question matrix
io_sexism_reaction	Placement of ‘sexism_reaction’ in ‘Sexism’ question matrix
io_sexism_society	Placement of ‘sexism_society’ in ‘Sexism’ question matrix
io_sexism_words	Placement of ‘sexism_words’ in ‘Sexism’ question matrix
io_prejudice_meaning	Variable displaying either sexism or racism items’ order depending on prejudice type
io_prejudice_reaction	Variable displaying either sexism or racism items’ order depending on prejudice type
io_prejudice_society	Variable displaying either sexism or racism items’ order depending on prejudice type
io_prejudice_words	Variable displaying either sexism or racism items’ order depending on prejudice type

Populism, Authoritarianism, Pluralism

Descriptive Overview

Variable

Label

Stats / Values

Freqs (% of Valid)

Graph

Valid

pop_peoplepower [labelled, factor]

Populism: Power to the People
To what extent do you agree or disagree with the following statements?
The public and not politicians should make the most important political decisions

1. Don't Agree

2. R. Don't Agree

3. Partially

4. R. Agree

5. Agree

213	(	5.1%	)
612	(	14.7%	)
1397	(	33.5%	)
1129	(	27.1%	)
818	(	19.6%	)

4169 (87.4%)

pop_elitediff [labelled, factor]

Populism: Elite Differences
To what extent do you agree or disagree with the following statements?
The differences between the people and the so-called elites are much bigger than the differences within the people

1. Don't Agree

2. R. Don't Agree

3. Partially

4. R. Agree

5. Agree

181	(	4.3%	)
385	(	9.2%	)
1109	(	26.6%	)
1355	(	32.5%	)
1139	(	27.3%	)

4169 (87.4%)

pop_goodbad [labelled, factor]

Populism: Manichaean Worldview
To what extent do you agree or disagree with the following statements?
At its core politics is a fight between good and evil

1. Don't Agree

2. R. Don't Agree

3. Partially

4. R. Agree

5. Agree

532	(	12.8%	)
895	(	21.5%	)
1479	(	35.5%	)
871	(	20.9%	)
392	(	9.4%	)

4169 (87.4%)

pop_homogen [labelled, factor]

Populism: Public Homogeneity
To what extent do you agree or disagree with the following statements?
Ordinary People share a good and honest character

1. Don't Agree

2. R. Don't Agree

3. Partially

4. R. Agree

5. Agree

227	(	5.4%	)
466	(	11.2%	)
1628	(	39.1%	)
1263	(	30.3%	)
585	(	14.0%	)

4169 (87.4%)

pop_mean [labelled, numeric]

Populism: Mean
Mean Score of the four ‘Populism’ items

Mean (sd) : 3.3 (0.8)

min ≤ med ≤ max:

1 ≤ 3.2 ≤ 5

IQR (CV) : 0.8 (0.2)

17 distinct values

4169 (87.4%)

aut_right_deviant [labelled, factor]

Right Authoritarianism: Deviants
To what extent do you agree or disagree with the following statements?
Anyone who endangers stability in Germany should feel strongly that he is undesired in society

1. Don't Agree

2. R. Don't Agree

3. Partially

4. R. Agree

5. Agree

210	(	5.0%	)
484	(	11.6%	)
1325	(	31.8%	)
1298	(	31.1%	)
850	(	20.4%	)

4167 (87.3%)

aut_left_deviant [labelled, factor]

Left Authoritarianism: Deviants
To what extent do you agree or disagree with the following statements?
Anyone who hinders societal progress should feel strongly that he is undesired in society

1. Don't Agree

2. R. Don't Agree

3. Partially

4. R. Agree

5. Agree

365	(	8.8%	)
760	(	18.2%	)
1570	(	37.7%	)
1008	(	24.2%	)
464	(	11.1%	)

4167 (87.3%)

aut_right_sub [labelled, factor]

Right Authoritarianism: Subordination
To what extent do you agree or disagree with the following statements?
We need strong leaders to live safe in society

1. Don't Agree

2. R. Don't Agree

3. Partially

4. R. Agree

5. Agree

244	(	5.9%	)
381	(	9.1%	)
1210	(	29.0%	)
1404	(	33.7%	)
928	(	22.3%	)

4167 (87.3%)

aut_left_sub [labelled, factor]

Left Authoritarianism: Subordination
To what extent do you agree or disagree with the following statements?
We need strong leaders to eradicate prejudice and intolerance in society

1. Don't Agree

2. R. Don't Agree

3. Partially

4. R. Agree

5. Agree

314	(	7.5%	)
450	(	10.8%	)
1327	(	31.8%	)
1327	(	31.8%	)
749	(	18.0%	)

4167 (87.3%)

aut_mean [labelled, numeric]

Authoritarianism: Mean
Mean Score of the four ‘Authoritarianism’ items

Mean (sd) : 3.4 (0.8)

min ≤ med ≤ max:

1 ≤ 3.5 ≤ 5

IQR (CV) : 1 (0.2)

17 distinct values

4167 (87.3%)

aut_left_mean [labelled, numeric]

Left Authoritarianism: Mean
Mean Score of the two ‘Left Authoritarianism’ items

Mean (sd) : 3.3 (0.9)

min ≤ med ≤ max:

1 ≤ 3.5 ≤ 5

IQR (CV) : 1 (0.3)

9 distinct values

4167 (87.3%)

aut_right_mean [labelled, numeric]

Right Authoritarianism: Mean
Mean Score of the two ‘Right Authoritarianism’ items

Mean (sd) : 3.5 (0.9)

min ≤ med ≤ max:

1 ≤ 3.5 ≤ 5

IQR (CV) : 1 (0.3)

9 distinct values

4167 (87.3%)

plu_compromise [labelled, factor]

Pluralism: Compromise
To what extent do you agree or disagree with the following statements?
In a democracy it is important to make compromises between different point of views

1. Don't Agree

2. R. Don't Agree

3. Partially

4. R. Agree

5. Agree

52	(	1.2%	)
161	(	3.9%	)
863	(	20.7%	)
1647	(	39.5%	)
1444	(	34.7%	)

4167 (87.3%)

plu_dispute [labelled, factor]

Pluralism: Dispute
To what extent do you agree or disagree with the following statements?
The political contest between different interest groups harms the common good
Item reversed in post-coding

1. Agree

2. R. Agree

3. Partially

4. R. Don't Agree

5. Don't Agree

547	(	13.1%	)
971	(	23.3%	)
1357	(	32.6%	)
841	(	20.2%	)
451	(	10.8%	)

4167 (87.3%)

plu_parties [labelled, factor]

Pluralism: Parties
To what extent do you agree or disagree with the following statements?
For a functioning democracy you need parties with different positions

1. Don't Agree

2. R. Don't Agree

3. Partially

4. R. Agree

5. Agree

73	(	1.8%	)
193	(	4.6%	)
942	(	22.6%	)
1569	(	37.7%	)
1390	(	33.4%	)

4167 (87.3%)

plu_mean [labelled, numeric]

Pluralism: Mean
Mean Score of the four ‘Pluralism’ items

Mean (sd) : 3.6 (0.7)

min ≤ med ≤ max:

1 ≤ 3.7 ≤ 5

IQR (CV) : 1 (0.2)

13 distinct values

4167 (87.3%)

Randomization Variables

Variables	Meaning
io_pop_peoplepower	Placement of ‘pop_peoplepower’ in ‘Populism’ question matrix
io_pop_elitediff	Placement of ‘pop_elitediff’ in ‘Populism’ question matrix
io_pop_goodbad	Placement of ‘pop_goodbad’ in ‘Populism’ question matrix
io_pop_homogen	Placement of ‘pop_homogen’ in ‘Populism’ question matrix
io_attentioncheck	Placement of ‘attentioncheck’ in ‘Populism’ question matrix
io_aut_right_deviant	Placement of ‘aut_right_deviant’ in ‘Authoritarianism’ question matrix
io_aut_left_deviant	Placement of ‘aut_left_deviant’ in ‘Authoritarianism’ question matrix
io_aut_right_sub	Placement of ‘aut_right_sub’ in ‘Authoritarianism’ question matrix
io_aut_left_sub	Placement of ‘aut_left_sub’ in ‘Authoritarianism’ question matrix
io_plu_compromise	Placement of ‘plu_compromise’ in ‘Pluralism’ question matrix
io_plu_dispute	Placement of ‘plu_dispute’ in ‘Pluralism’ question matrix
io_plu_parties	Placement of ‘plu_parties’ in ‘Pluralism’ question matrix

qo_pop	Placement of ‘Populism’ question matrix in ‘Pop-Aut-Plu’ block
qo_aut	Placement of ‘Authoritarianism’ question matrix in ‘Pop-Aut-Plu’ block
qo_plu	Placement of ‘Pluralism’ question matrix in ‘Pop-Aut-Plu’ block

Vote Choice, Partisanship

Descriptive Overview

Variable

Label

Stats / Values

Freqs (% of Valid)

Graph

Valid

scalo_left [labelled, numeric]

Scalometer: Die Linke
What do you think in general about the singular political parties? Please rate the following parties on a scale from -5 (you don’t think anything of this party) to +5 (you think a lot of this party).
Die Linke

Mean (sd) : -1.1 (3)

min ≤ med ≤ max:

-5 ≤ -1 ≤ 5

IQR (CV) : 5 (-2.6)

11 distinct values

4235 (88.7%)

scalo_greens [labelled, numeric]

Scalometer: Die Grünen
What do you think in general about the singular political parties? Please rate the following parties on a scale from -5 (you don’t think anything of this party) to +5 (you think a lot of this party).
B90/Die Grünen

Mean (sd) : -0.6 (3.4)

min ≤ med ≤ max:

-5 ≤ 0 ≤ 5

IQR (CV) : 6 (-5.8)

11 distinct values

4235 (88.7%)

scalo_spd [labelled, numeric]

Scalometer: SPD
What do you think in general about the singular political parties? Please rate the following parties on a scale from -5 (you don’t think anything of this party) to +5 (you think a lot of this party).
SPD

Mean (sd) : 0.1 (3.1)

min ≤ med ≤ max:

-5 ≤ 1 ≤ 5

IQR (CV) : 4 (53.7)

11 distinct values

4235 (88.7%)

scalo_cdu [labelled, numeric]

Scalometer: CDU
What do you think in general about the singular political parties? Please rate the following parties on a scale from -5 (you don’t think anything of this party) to +5 (you think a lot of this party).
CDU

Mean (sd) : -0.1 (3)

min ≤ med ≤ max:

-5 ≤ 0 ≤ 5

IQR (CV) : 4 (-24.7)

11 distinct values

4235 (88.7%)

scalo_csu [labelled, numeric]

Scalometer: CSU
What do you think in general about the singular political parties? Please rate the following parties on a scale from -5 (you don’t think anything of this party) to +5 (you think a lot of this party).
CSU

Mean (sd) : -0.5 (2.9)

min ≤ med ≤ max:

-5 ≤ 0 ≤ 5

IQR (CV) : 5 (-5.5)

11 distinct values

4235 (88.7%)

scalo_fdp [labelled, numeric]

Scalometer: FDP
What do you think in general about the singular political parties? Please rate the following parties on a scale from -5 (you don’t think anything of this party) to +5 (you think a lot of this party).
FDP

Mean (sd) : -0.7 (2.8)

min ≤ med ≤ max:

-5 ≤ -1 ≤ 5

IQR (CV) : 4 (-3.9)

11 distinct values

4235 (88.7%)

scalo_afd [labelled, numeric]

Scalometer: AfD
What do you think in general about the singular political parties? Please rate the following parties on a scale from -5 (you don’t think anything of this party) to +5 (you think a lot of this party).
AfD

Mean (sd) : -2.5 (3.3)

min ≤ med ≤ max:

-5 ≤ -5 ≤ 5

IQR (CV) : 5 (-1.3)

11 distinct values

4235 (88.7%)

scalo_other [labelled, numeric]

Scalometer: Other
What do you think in general about the singular political parties? Please rate the following parties on a scale from -5 (you don’t think anything of this party) to +5 (you think a lot of this party).
[Pasted from vote_other]
Filter: vote == Other

Mean (sd) : 3.6 (1.6)

min ≤ med ≤ max:

-2 ≤ 4 ≤ 5

IQR (CV) : 2 (0.4)

-2	:	1	(	0.6%	)
-1	:	2	(	1.1%	)
0	:	8	(	4.5%	)
1	:	7	(	3.9%	)
2	:	23	(	12.9%	)
3	:	30	(	16.9%	)
4	:	30	(	16.9%	)
5	:	77	(	43.3%	)

178 (3.7%)

vote [labelled, factor]

Vote Intention
Which party would you vote for, if the general election was next Sunday?

1. Left

2. Greens

3. SPD

4. Union

5. FDP

6. AfD

7. Other

8. Unclear

9. Ineligible

332	(	8.8%	)
624	(	16.5%	)
695	(	18.4%	)
799	(	21.1%	)
301	(	8.0%	)
495	(	13.1%	)
181	(	4.8%	)
305	(	8.1%	)
46	(	1.2%	)

3778 (79.2%)

vote_other [labelled, character]

Vote Intention: Other
Which party would you vote for, if the general election was next Sunday?
Filter: vote == Other

1. Die Partei

2. Freie Wähler

3. Tierschutzpartei

4. Piraten

5. Tierschutz

6. Volt

7. Graue Panther

8. Bayernpartei

9. Die Basis

10. freie wähler

[ 80 others ]

23	(	12.7%	)
23	(	12.7%	)
13	(	7.2%	)
9	(	5.0%	)
6	(	3.3%	)
5	(	2.8%	)
4	(	2.2%	)
3	(	1.7%	)
3	(	1.7%	)
3	(	1.7%	)
89	(	49.2%	)

181 (3.8%)

pid [labelled, factor]

Positive Partisan Identification
In Germany, many people lean towards a specific party for a longer time even though they might vote for other parties from time to time. How about yourself: Do you, generally speaking, lean towards a specific party?

1. Left

2. Greens

3. SPD

4. CDU

5. CSU

6. FDP

7. AfD

8. Other

9. None

326	(	7.7%	)
526	(	12.4%	)
670	(	15.8%	)
619	(	14.6%	)
175	(	4.1%	)
280	(	6.6%	)
405	(	9.6%	)
92	(	2.2%	)
1138	(	26.9%	)

4231 (88.7%)

pid_other [labelled, character]

Positive Partisan Identification: Other
In Germany, many people lean towards a specific party for a longer time even though they might vote for other parties from time to time. How about yourself: Do you, generally speaking, lean towards a specific party?
Filter: pid == Other

1. Freie Wähler

2. Tierschutzpartei

3. Die Partei

4. Piraten

5. Volt

6. NPD

7. tierschutzpartei

8. Tierschutz

9. die Basis

10. Die Basis

[ 37 others ]

11	(	12.0%	)
9	(	9.8%	)
6	(	6.5%	)
5	(	5.4%	)
5	(	5.4%	)
4	(	4.3%	)
4	(	4.3%	)
3	(	3.3%	)
2	(	2.2%	)
2	(	2.2%	)
41	(	44.6%	)

92 (1.9%)

nid [labelled, factor]

Negative Partisan Identification
Sometimes people also feel antipathy towards a specific party. How about yourself: Is there a certain party towards which you, generally speaking, feel antipathy?

1. Left

2. Greens

3. SPD

4. CDU

5. CSU

6. FDP

7. AfD

8. Other

9. None

236	(	5.6%	)
842	(	19.9%	)
133	(	3.1%	)
172	(	4.1%	)
69	(	1.6%	)
109	(	2.6%	)
2241	(	53.0%	)
20	(	0.5%	)
409	(	9.7%	)

4231 (88.7%)

nid_other [labelled, character]

Negative Partisan Identification: Other
Sometimes people also feel antipathy towards a specific party. How about yourself: Is there a certain party towards which you, generally speaking, feel antipathy?,
Filter: nid == Other

1. NPD

2. alle

3. allen

4. freie wähler

5. AFD

6. Allen

7. allen Parteien

8. fast allen - Parteiendemo

9. Ganz klar, wenn mehrere P

10. Ich bin fast allen Partei

[ 4 others ]

4	(	20.0%	)
2	(	10.0%	)
2	(	10.0%	)
2	(	10.0%	)
1	(	5.0%	)
1	(	5.0%	)
1	(	5.0%	)
1	(	5.0%	)
1	(	5.0%	)
1	(	5.0%	)
4	(	20.0%	)

20 (0.4%)

aff_pos_criticism [labelled, factor]

Affective Positive Partisanship: Criticism
Please indicate how much you agree to the following statements
When people insult [partisan in-group], I feel personally insulted
Filter: pid != None

1. Don't Agree

2. R. Don't Agree

3. Partially

4. R. Agree

5. Agree

770	(	25.1%	)
905	(	29.6%	)
810	(	26.5%	)
369	(	12.1%	)
208	(	6.8%	)

3062 (64.2%)

aff_pos_positive [labelled, factor]

Affective Positive Partisanship: Positive Feeling
Please indicate how much you agree to the following statements
When people speak positively about [partisan in-group], this gives me a good feeling
Filter: pid != None

1. Don't Agree

2. R. Don't Agree

3. Partially

4. R. Agree

5. Agree

109	(	3.6%	)
199	(	6.5%	)
989	(	32.3%	)
1057	(	34.5%	)
708	(	23.1%	)

3062 (64.2%)

aff_pos_similar [labelled, factor]

Affective Positive Partisanship: Similarity
Please indicate how much you agree to the following statements
Normally, people who support [partisan in-group] are very similar to me
Filter: pid != None

1. Don't Agree

2. R. Don't Agree

3. Partially

4. R. Agree

5. Agree

81	(	2.6%	)
223	(	7.3%	)
1084	(	35.4%	)
1102	(	36.0%	)
572	(	18.7%	)

3062 (64.2%)

aff_neg_criticism [labelled, factor]

Affective Negative Partisanship: Criticism
Please indicate how much you agree to the following statements
When someone criticizes [partisan out-group], this gives me a good feeling
Filter: nid != None

1. Don't Agree

2. R. Don't Agree

3. Partially

4. R. Agree

5. Agree

237	(	6.3%	)
298	(	7.9%	)
965	(	25.5%	)
970	(	25.6%	)
1315	(	34.7%	)

3785 (79.3%)

aff_neg_different [labelled, factor]

Affective Negative Partisanship: Differences
Please indicate how much you agree to the following statements
Normally, people who support [partisan out-group] are very different from me
Filter: nid != None

1. Don't Agree

2. R. Don't Agree

3. Partially

4. R. Agree

5. Agree

132	(	3.5%	)
219	(	5.8%	)
735	(	19.4%	)
1013	(	26.8%	)
1686	(	44.5%	)

3785 (79.3%)

aff_neg_anti [labelled, factor]

Affective Negative Partisanship: Being Anti
Please indicate how much you agree to the following statements
It is important for me to be Anti-[partisan out-group]
Filter: nid != None

1. Don't Agree

2. R. Don't Agree

3. Partially

4. R. Agree

5. Agree

319	(	8.4%	)
368	(	9.7%	)
748	(	19.8%	)
858	(	22.7%	)
1492	(	39.4%	)

3785 (79.3%)

aff_neg_damaging [labelled, factor]

Affective Negative Partisanship: Damaging
Please indicate how much you agree to the following statements
The one who votes for [partisan out-group] harms Germany
Filter: nid != None

1. Don't Agree

2. R. Don't Agree

3. Partially

4. R. Agree

5. Agree

124	(	3.3%	)
168	(	4.4%	)
594	(	15.7%	)
913	(	24.1%	)
1986	(	52.5%	)

3785 (79.3%)

aff_neg_democracy [labelled, factor]

Affective Negative Partisanship: Democracy
Please indicate how much you agree to the following statements
I think [partisan out-group] poses a threat for democracy
Filter: nid != None

1. Don't Agree

2. R. Don't Agree

3. Partially

4. R. Agree

5. Agree

156	(	4.1%	)
186	(	4.9%	)
542	(	14.3%	)
891	(	23.5%	)
2010	(	53.1%	)

3785 (79.3%)

affass_pos_informed [labelled, numeric]

Affective Positive Partisanship: Associations (Informed)
When you think about [partisan in-group] and its voters: Use the sliders below, to tell us how you would describe the average voter.
-5 = Uninformed; 0 = Neither; 5 = Informed
Filter: pid != None

Mean (sd) : 2.2 (2.1)

min ≤ med ≤ max:

-5 ≤ 2 ≤ 5

IQR (CV) : 3 (0.9)

11 distinct values

3050 (63.9%)

affass_pos_honest [labelled, numeric]

Affective Positive Partisanship: Associations (Honesty)
When you think about [partisan in-group] and its voters: Use the sliders below, to tell us how you would describe the average voter.
-5 = Dishonest; 0 = Neither; 5 = Honest
Filter: pid != None

Mean (sd) : 1.9 (2)

min ≤ med ≤ max:

-5 ≤ 2 ≤ 5

IQR (CV) : 3 (1)

11 distinct values

3050 (63.9%)

affass_pos_good [labelled, numeric]

Affective Positive Partisanship: Associations (Good)
When you think about [partisan in-group] and its voters: Use the sliders below, to tell us how you would describe the average voter.
-5 = Bad; 0 = Good; 5 = Informed
Filter: pid != None

Mean (sd) : 1.8 (2.2)

min ≤ med ≤ max:

-5 ≤ 2 ≤ 5

IQR (CV) : 3 (1.3)

11 distinct values

3050 (63.9%)

affass_pos_selfless [labelled, numeric]

Affective Positive Partisanship: Associations (Selflessness)
When you think about [partisan in-group] and its voters: Use the sliders below, to tell us how you would describe the average voter.
-5 = Egoistic; 0 = Neither; 5 = Selfless
Filter: pid != None

Mean (sd) : 1.2 (2)

min ≤ med ≤ max:

-5 ≤ 1 ≤ 5

IQR (CV) : 3 (1.8)

11 distinct values

3050 (63.9%)

affass_pos_intelligent [labelled, numeric]

Affective Positive Partisanship: Associations (Intelligence)
When you think about [partisan in-group] and its voters: Use the sliders below, to tell us how you would describe the average voter.
-5 = Stupid; 0 = Neither; 5 = Intelligent
Filter: pid != None

Mean (sd) : 2 (2.1)

min ≤ med ≤ max:

-5 ≤ 2 ≤ 5

IQR (CV) : 4 (1.1)

11 distinct values

3050 (63.9%)

affass_pos_sympathetic [labelled, numeric]

Affective Positive Partisanship: Associations (Pleasent)
When you think about [partisan in-group] and its voters: Use the sliders below, to tell us how you would describe the average voter.
-5 = Unpleasent; 0 = Neither; 5 = Pleasent
Filter: pid != None

Mean (sd) : 2.2 (2)

min ≤ med ≤ max:

-5 ≤ 2 ≤ 5

IQR (CV) : 3 (0.9)

11 distinct values

3050 (63.9%)

affass_pos_tolerant [labelled, numeric]

Affective Positive Partisanship: Associations (Tolerance)
When you think about [partisan in-group] and its voters: Use the sliders below, to tell us how you would describe the average voter.
-5 = Intolerant; 0 = Neither; 5 = Tolerant
Filter: pid != None

Mean (sd) : 1.9 (2.1)

min ≤ med ≤ max:

-5 ≤ 2 ≤ 5

IQR (CV) : 3 (1.1)

11 distinct values

3050 (63.9%)

affass_neg_informed [labelled, numeric]

Affective Negative Partisanship: Associations (Informed)
When you think about [partisan out-group] and its voters: Use the sliders below, to tell us how you would describe the average voter.
-5 = Uninformed; 0 = Neither; 5 = Informed
Filter: nid != None

Mean (sd) : -1.7 (2.6)

min ≤ med ≤ max:

-5 ≤ -2 ≤ 5

IQR (CV) : 4 (-1.5)

11 distinct values

3778 (79.2%)

affass_neg_honest [labelled, numeric]

Affective Negative Partisanship: Associations (Honesty)
When you think about [partisan out -group] and its voters: Use the sliders below, to tell us how you would describe the average voter.
-5 = Dishonest; 0 = Neither; 5 = Honest
Filter: nid != None

Mean (sd) : -1.3 (2.5)

min ≤ med ≤ max:

-5 ≤ -1 ≤ 5

IQR (CV) : 3 (-1.9)

11 distinct values

3778 (79.2%)

affass_neg_good [labelled, numeric]

Affective Negative Partisanship: Associations (Good)
When you think about [partisan out-group] and its voters: Use the sliders below, to tell us how you would describe the average voter.
-5 = Bad; 0 = Good; 5 = Informed
Filter: nid != None

Mean (sd) : -1.2 (2.3)

min ≤ med ≤ max:

-5 ≤ -1 ≤ 5

IQR (CV) : 3 (-1.9)

11 distinct values

3778 (79.2%)

affass_neg_selfless [labelled, numeric]

Affective Negative Partisanship: Associations (Selflessness)
When you think about [partisan out-group] and its voters: Use the sliders below, to tell us how you would describe the average voter.
-5 = Egoistic; 0 = Neither; 5 = Selfless
Filter: nid != None

Mean (sd) : -2 (2.5)

min ≤ med ≤ max:

-5 ≤ -2 ≤ 5

IQR (CV) : 4 (-1.3)

11 distinct values

3778 (79.2%)

affass_neg_intelligent [labelled, numeric]

Affective Negative Partisanship: Associations (Intelligence)
When you think about [partisan out-group] and its voters: Use the sliders below, to tell us how you would describe the average voter.
-5 = Stupid; 0 = Neither; 5 = Intelligent
Filter: nid != None

Mean (sd) : -1.4 (2.5)

min ≤ med ≤ max:

-5 ≤ -1 ≤ 5

IQR (CV) : 4 (-1.8)

11 distinct values

3778 (79.2%)

affass_neg_sympathetic [labelled, numeric]

Affective Negative Partisanship: Associations (Pleasent)
When you think about [partisan out-group] and its voters: Use the sliders below, to tell us how you would describe the average voter.
-5 = Unpleasent; 0 = Neither; 5 = Pleasent
Filter: nid != None

Mean (sd) : -2.3 (2.6)

min ≤ med ≤ max:

-5 ≤ -3 ≤ 5

IQR (CV) : 5 (-1.1)

11 distinct values

3778 (79.2%)

affass_neg_tolerant [labelled, numeric]

Affective Negative Partisanship: Associations (Tolerance)
When you think about [partisan out-group] and its voters: Use the sliders below, to tell us how you would describe the average voter.
-5 = Intolerant; 0 = Neither; 5 = Tolerant
Filter: nid != None

Mean (sd) : -2.5 (2.6)

min ≤ med ≤ max:

-5 ≤ -3 ≤ 5

IQR (CV) : 4 (-1.1)

11 distinct values

3778 (79.2%)

aff_pos_mean [labelled, numeric]

Affective Positive Partisanship: Mean
Mean Score of the three ‘Affective Positive Partisanship’ items

Mean (sd) : 3.2 (0.8)

min ≤ med ≤ max:

1 ≤ 3.3 ≤ 5

IQR (CV) : 1 (0.3)

13 distinct values

3062 (64.2%)

aff_neg_mean_orig [labelled, numeric]

Affective Negative Partisanship: Mean (Original)
Mean Score of the three ‘Affective Negative Partisanship’ items based on Areal (2022)

Mean (sd) : 3.8 (1)

min ≤ med ≤ max:

1 ≤ 4 ≤ 5

IQR (CV) : 1.3 (0.3)

13 distinct values

3785 (79.3%)

aff_neg_mean_full [labelled, numeric]

Affective Negative Partisanship: Mean (Full)
Mean Score of all five ‘Affective Negative Partisanship’ items

Mean (sd) : 4 (0.9)

min ≤ med ≤ max:

1 ≤ 4.2 ≤ 5

IQR (CV) : 1.4 (0.2)

21 distinct values

3785 (79.3%)

Randomization Variables

Variables	Meaning
	VOTE INTENTION
io_vote_left	Placement of Party ‘Left’ in ‘Vote Intention’ answering matrix
io_vote_greens	Placement of Party ‘Greens’ in ‘Vote Intention’ answering matrix
io_vote_spd	Placement of Party ‘SPD’ in ‘Vote Intention’ answering matrix
io_vote_union	Placement of Party ‘Union’ in ‘Vote Intention’ answering matrix
io_vote_fdp	Placement of Party ‘FDP’ in ‘Vote Intention’ answering matrix
io_vote_afd	Placement of Party ‘AfD’ in ‘Vote Intention’ answering matrix
	SCALOMETER RATINGS
io_scalo_left	Placement of Party ‘Left’ in ‘Scalometer’ question matrix
io_scalo_greens	Placement of Party ‘Greens’ in ‘Scalometer’ question matrix
io_scalo_spd	Placement of Party ‘SPD’ in ‘Scalometer’ question matrix
io_scalo_cdu	Placement of Party ‘CDU’ in ‘Scalometer’ question matrix
io_scalo_csu	Placement of Party ‘CSU’ in ‘Scalometer’ question matrix
io_scalo_fdp	Placement of Party ‘FDP’ in ‘Scalometer’ question matrix
io_scalo_afd	Placement of Party ‘AfD’ in ‘Scalometer’ question matrix
io_scalo_other	Placement of Party ‘Other’ in ‘Scalometer’ question matrix (If vote choice was ‘Other’)
	POSITIVE & NEGATIVE PARTISAN IDs
io_pid_left	Placement of Party ‘Left’ in ‘Positive Partisanship’ answering matrix
io_pid_greens	Placement of Party ‘Greens’ in ‘Positive Partisanship’ answering matrix
io_pid_spd	Placement of Party ‘SPD’ in ‘Positive Partisanship’ answering matrix
io_pid_cdu	Placement of Party ‘CDU’ in ‘Positive Partisanship’ answering matrix
io_pid_csu	Placement of Party ‘CSU’ in ‘Positive Partisanship’ answering matrix
io_pid_fdp	Placement of Party ‘FDP’ in ‘Positive Partisanship’ answering matrix
io_pid_afd	Placement of Party ‘AfD’ in ‘Positive Partisanship’ answering matrix
io_nid_left	Placement of Party ‘Left’ in ‘Negative Partisanship’ answering matrix
io_nid_greens	Placement of Party ‘Greens’ in ‘Negative Partisanship’ answering matrix
io_nid_spd	Placement of Party ‘SPD’ in ‘Negative Partisanship’ answering matrix
io_nid_cdu	Placement of Party ‘CDU’ in ‘Negative Partisanship’ answering matrix
io_nid_csu	Placement of Party ‘CSU’ in ‘Negative Partisanship’ answering matrix
io_nid_fdp	Placement of Party ‘FDP’ in ‘Negative Partisanship’ answering matrix
io_nid_afd	Placement of Party ‘AfD’ in ‘Negative Partisanship’ answering matrix
	AFFECTIVE POLARIZATION SCALES
io_aff_pos_criticism	Placement of ‘aff_pos_criticism’ in ‘Positive Affective Partisanship’ question matrix
io_aff_pos_positive	Placement of ‘aff_pos_positive’ in ‘Positive Affective Partisanship’ question matrix
io_aff_pos_similar	Placement of ‘aff_pos_similar’ in ‘Positive Affective Partisanship’ question matrix
io_aff_neg_criticism	Placement of ‘aff_neg_criticism’ in ‘Negative Affective Partisanship’ question matrix
io_aff_neg_different	Placement of ‘aff_neg_different’ in ‘Negative Affective Partisanship’ question matrix
io_aff_neg_anti	Placement of ‘aff_neg_anti’ in ‘Negative Affective Partisanship’ question matrix
io_aff_neg_damaging	Placement of ‘aff_neg_damaging’ in ‘Negative Affective Partisanship’ question matrix
io_aff_neg_democracy	Placement of ‘aff_neg_democracy’ in ‘Negative Affective Partisanship’ question matrix

qo_aff_pos	Placement of ‘Positive Affective Partisanship’ question matrix in ‘Affective Partisanship’ block
qo_aff_neg	Placement of ‘Negative Affective Partisanship’ question matrix in ‘Affective Partisanship’ block
	AFFECTIVE ASSOCIATIONS
io_affass_pos_intelligent	Placement of ‘affass_pos_intelligent’ in ‘Positive Affective Associations’ question matrix
io_affass_pos_sympathetic	Placement of ‘affass_pos_sympathetic’ in ‘Positive Affective Associations’ question matrix
io_affass_pos_tolerant	Placement of ‘affass_pos_tolerant’ in ‘Positive Affective Associations’ question matrix
io_affass_pos_informed	Placement of ‘affass_pos_informed’ in ‘Positive Affective Associations’ question matrix
io_affass_pos_honest	Placement of ‘affass_pos_honest’ in ‘Positive Affective Associations’ question matrix
io_affass_pos_good	Placement of ‘affass_pos_good’ in ‘Positive Affective Associations’ question matrix
io_affass_pos_selfless	Placement of ‘affass_pos_selfless’ in ‘Positive Affective Associations’ question matrix
io_affass_neg_intelligent	Placement of ‘affass_neg_intelligent’ in ‘Negative Affective Associations’ question matrix
io_affass_neg_sympathetic	Placement of ‘affass_neg_sympathetic’ in ‘Negative Affective Associations’ question matrix
io_affass_neg_tolerant	Placement of ‘affass_neg_tolerant’ in ‘Negative Affective Associations’ question matrix
io_affass_neg_informed	Placement of ‘affass_neg_informed’ in ‘Negative Affective Associations’ question matrix
io_affass_neg_honest	Placement of ‘affass_neg_honest’ in ‘Negative Affective Associations’ question matrix
io_affass_neg_good	Placement of ‘affass_neg_good’ in ‘Negative Affective Associations’ question matrix
io_affass_neg_selfless	Placement of ‘affass_neg_selfless’ in ‘Negative Affective Associations’ question matrix

qo_affass_pos	Placement of ‘Positive Affective Associations’ question matrix in ‘Affective Associations’ block
qo_affass_neg	Placement of ‘Negative Affective Associations’ question matrix in ‘Affective Associations’ block

Anchoring Vignettes

Descriptive Overview

Variable

Label

Stats / Values

Freqs (% of Valid)

Graph

Valid

anchor1 [labelled, factor]

Anchor Vignette I
Next we will describe to you some people. We want to know your opinion on how free each respective person can say what she really thinks.

Person F. mostly has completely different political opinions compared to her close friends. Nevertheless, person F. feels comfortable to talk to them about societal topics because she feels respected in her opinion.

What do you think: How free can person F. say what she really thinks?

1. Unfree

2. R. Unfree

3. R. Free

4. Free

127	(	2.9%	)
524	(	12.0%	)
1614	(	37.1%	)
2087	(	48.0%	)

4352 (91.2%)

anchor2 [labelled, factor]

Anchor Vignette II
Next we will describe to you some people. We want to know your opinion on how free each respective person can say what she really thinks.

Person P. disagrees with the politics of the government. She does not think that the government would punish anyone for voicing critical opinions. Therefore, she voices her opinions to most topics without any regard to who listens.

What do you think: How free can person P. say what she really thinks?

1. Unfree

2. R. Unfree

3. R. Free

4. Free

193	(	4.4%	)
797	(	18.3%	)
1694	(	38.9%	)
1673	(	38.4%	)

4357 (91.3%)

anchor3 [labelled, factor]

Anchor Vignette III
Next we will describe to you some people. We want to know your opinion on how free each respective person can say what she really thinks.

Person K. has political views that do not match those of the government. She knows people that have been strongly insulted for having diverging opinions. Sometimes she criticizes politicians’ decisions in the internet and demands changes. However, she takes care never to use her real name.

What do you think: How free can person K. say what she really thinks?

1. Unfree

2. R. Unfree

3. R. Free

4. Free

581	(	13.3%	)
1686	(	38.7%	)
1465	(	33.6%	)
627	(	14.4%	)

4359 (91.3%)

anchor4 [labelled, factor]

Anchor Vignette IV
Next we will describe to you some people. We want to know your opinion on how free each respective person can say what she really thinks.

Person S. disagrees with many political measures of the government. She has hears that people have occasionally lost their job because the spoke out against the current politics. In talks to colleagues she tries to avoid political topics or keeps her own, critical opinions for herself.

What do you think: How free can person S. say what she really thinks?

1. Unfree

2. R. Unfree

3. R. Free

4. Free

1277	(	29.3%	)
1842	(	42.2%	)
809	(	18.5%	)
435	(	10.0%	)

4363 (91.4%)

anchor5 [labelled, factor]

Anchor Vignette V
Next we will describe to you some people. We want to know your opinion on how free each respective person can say what she really thinks.

Person H. has strong opinions to many controversial topics. She has a friend who got into legal problems because he voiced his opinions publicly. Therefore, she avoids voicing her own opinion in public places.

What do you think: How free can person H. say what she really thinks?

1. Unfree

2. R. Unfree

3. R. Free

4. Free

1103	(	25.3%	)
2002	(	46.0%	)
829	(	19.0%	)
420	(	9.6%	)

4354 (91.2%)

anchor6 [labelled, factor]

Anchor Vignette VI
Next we will describe to you some people. We want to know your opinion on how free each respective person can say what she really thinks.

Person M. disagrees with many societal developments, but is very cautious to whom she says this. Even with close friends and relative she often does not share her true opinions. She knows multiple people whose family and acquaintances ended contact with them because they said controversial things.

What do you think: How free can person M. say what she really thinks?

1. Unfree

2. R. Unfree

3. R. Free

4. Free

1286	(	29.5%	)
1796	(	41.2%	)
827	(	19.0%	)
455	(	10.4%	)

4364 (91.5%)

Randomization Variables

Variables	Meaning
io_anchor1	Placement of ‘anchor1’ in ‘Anchoring’ block
io_anchor2	Placement of ‘anchor2’ in ‘Anchoring’ block
io_anchor3	Placement of ‘anchor3’ in ‘Anchoring’ block
io_anchor4	Placement of ‘anchor4’ in ‘Anchoring’ block
io_anchor5	Placement of ‘anchor5’ in ‘Anchoring’ block
io_anchor6	Placement of ‘anchor6’ in ‘Anchoring’ block

Online Participation

Descriptive Overview

Variable

Label

Stats / Values

Freqs (% of Valid)

Graph

Valid

online_post [labelled, factor]

Online Engagement: Posting
Now to the topic of political participation in the internet. Here are some opportunities to be politically active online. Please indicate every opportunity that you have exercised in the last 12 month
Have you posted own political posts on social media?

1. Never

2. Once

3. Multiple Times

4. Regularly

2922	(	70.2%	)
458	(	11.0%	)
622	(	14.9%	)
161	(	3.9%	)

4163 (87.2%)

online_share [labelled, factor]

Online Engagement: Sharing
Now to the topic of political participation in the internet. Here are some opportunities to be politically active online. Please indicate every opportunity that you have exercised in the last 12 month
Have you shared political posts by other people on social media?

1. Never

2. Once

3. Multiple Times

4. Regularly

2499	(	60.0%	)
474	(	11.4%	)
959	(	23.0%	)
231	(	5.5%	)

4163 (87.2%)

online_comment [labelled, factor]

Online Engagement: Commenting
Now to the topic of political participation in the internet. Here are some opportunities to be politically active online. Please indicate every opportunity that you have exercised in the last 12 month
Have you commented on political posts by others on social media?

1. Never

2. Once

3. Multiple Times

4. Regularly

2591	(	62.2%	)
508	(	12.2%	)
867	(	20.8%	)
197	(	4.7%	)

4163 (87.2%)

online_groups [labelled, factor]

Online Engagement: Groups
Are you currently or were you during the last 12 months a member of a politically oriented (chat-)group on social media?

1. Never

2. Yes, One

3. Yes, Multiple

3684	(	88.6%	)
270	(	6.5%	)
204	(	4.9%	)

4158 (87.1%)

online_mean [labelled, numeric]

Online Engagement: Mean
Mean Score of the three ‘Online Engagement’ items

Mean (sd) : 1.6 (0.8)

min ≤ med ≤ max:

1 ≤ 1 ≤ 4

IQR (CV) : 1.3 (0.5)

10 distinct values

4163 (87.2%)

Randomization Variables

Variables	Meaning
io_online_post	Placement of ‘online_post’ in ‘Online Participation’ question matrix
io_online_share	Placement of ‘online_share’ in ‘Online Participation’ question matrix
io_online_comment	Placement of ‘online_comment’ in ‘Online Participation’ question matrix

Statement Ratings

Descriptive Overview

Variable

Label

Stats / Values

Freqs (% of Valid)

Graph

Valid

statement_insult_racists [labelled, numeric]

Statement: Insulting (Racists)
How insulting do you find the statement above?

All white people act racist in everyday live

0 = Not at all insulting; 10 = Extremely Insulting

Mean (sd) : 7 (2.9)

min ≤ med ≤ max:

0 ≤ 8 ≤ 10

IQR (CV) : 5 (0.4)

11 distinct values

2084 (43.7%)

statement_true_racists [labelled, numeric]

Statement: True (Racists)
How true do you find the statement above?

All white people act racist in everyday live

0 = Untrue; 10 = True

Mean (sd) : 2.8 (2.8)

min ≤ med ≤ max:

0 ≤ 2 ≤ 10

IQR (CV) : 5 (1)

11 distinct values

2084 (43.7%)

statement_danger_racists [labelled, numeric]

Statement: Dangerous (Racists)
How true do you find the statement above?

All white people act racist in everyday live

0 = Not at all dangerous; 10 = Extremely dangerous

Mean (sd) : 6.9 (2.7)

min ≤ med ≤ max:

0 ≤ 7 ≤ 10

IQR (CV) : 4 (0.4)

11 distinct values

2084 (43.7%)

statement_insult_racism [labelled, numeric]

Statement: Insulting (Racism)
How insulting do you find the statement above?

By nature, some ethnic groups are less intelligent than others

0 = Not at all insulting; 10 = Extremely Insulting

Mean (sd) : 7.2 (2.9)

min ≤ med ≤ max:

0 ≤ 8 ≤ 10

IQR (CV) : 5 (0.4)

11 distinct values

2189 (45.9%)

statement_true_racism [labelled, numeric]

Statement: True (Racism)
How true do you find the statement above?

By nature, some ethnic groups are less intelligent than others

0 = Untrue; 10 = True

Mean (sd) : 3.1 (3.2)

min ≤ med ≤ max:

0 ≤ 2 ≤ 10

IQR (CV) : 6 (1)

11 distinct values

2189 (45.9%)

statement_danger_racism [labelled, numeric]

Statement: Dangerous (Racism)
How true do you find the statement above?

By nature, some ethnic groups are less intelligent than others

0 = Not at all dangerous; 10 = Extremely dangerous

Mean (sd) : 6.8 (2.9)

min ≤ med ≤ max:

0 ≤ 7 ≤ 10

IQR (CV) : 5 (0.4)

11 distinct values

2189 (45.9%)

statement_insult_borders [labelled, numeric]

Statement: Insulting (Borders)
How insulting do you find the statement above?

All borders and nation states should be abolished

0 = Not at all insulting; 10 = Extremely Insulting

Mean (sd) : 3.8 (3.1)

min ≤ med ≤ max:

0 ≤ 4 ≤ 10

IQR (CV) : 6 (0.8)

11 distinct values

2148 (45.0%)

statement_true_borders [labelled, numeric]

Statement: True (Borders)
How true do you find the statement above?

All borders and nation states should be abolished

0 = Untrue; 10 = True

Mean (sd) : 3.6 (3)

min ≤ med ≤ max:

0 ≤ 3 ≤ 10

IQR (CV) : 5 (0.8)

11 distinct values

2148 (45.0%)

statement_danger_borders [labelled, numeric]

Statement: Dangerous (Borders)
How true do you find the statement above?

All borders and nation states should be abolished

0 = Not at all dangerous; 10 = Extremely dangerous

Mean (sd) : 6 (3)

min ≤ med ≤ max:

0 ≤ 6 ≤ 10

IQR (CV) : 4 (0.5)

11 distinct values

2148 (45.0%)

statement_insult_immigration [labelled, numeric]

Statement: Insulting (Immigration)
How insulting do you find the statement above?

Every kind of immigration into Germany should be stopped

0 = Not at all insulting; 10 = Extremely Insulting

Mean (sd) : 5.1 (3.3)

min ≤ med ≤ max:

0 ≤ 5 ≤ 10

IQR (CV) : 6 (0.7)

11 distinct values

2111 (44.2%)

statement_true_immigration [labelled, numeric]

Statement: True (Immigration)
How true do you find the statement above?

Every kind of immigration into Germany should be stopped

0 = Untrue; 10 = True

Mean (sd) : 4.3 (3.3)

min ≤ med ≤ max:

0 ≤ 4 ≤ 10

IQR (CV) : 6 (0.8)

11 distinct values

2111 (44.2%)

statement_danger_immigration [labelled, numeric]

Statement: Dangerous (Immigration)
How true do you find the statement above?

Every kind of immigration into Germany should be stopped

0 = Not at all dangerous; 10 = Extremely dangerous

Mean (sd) : 5.9 (3.1)

min ≤ med ≤ max:

0 ≤ 6 ≤ 10

IQR (CV) : 5 (0.5)

11 distinct values

2111 (44.2%)

statement_insult_sexequal [labelled, numeric]

Statement: Insulting (Sex Equality)
How insulting do you find the statement above?

Differences in abilities of men and women are determined biologically

0 = Not at all insulting; 10 = Extremely Insulting

Mean (sd) : 4.6 (3.3)

min ≤ med ≤ max:

0 ≤ 5 ≤ 10

IQR (CV) : 5 (0.7)

11 distinct values

2145 (44.9%)

statement_true_sexequal [labelled, numeric]

Statement: True (Sex Equality)
How true do you find the statement above?

Differences in abilities of men and women are determined biologically

0 = Untrue; 10 = True

Mean (sd) : 5.3 (3.2)

min ≤ med ≤ max:

0 ≤ 6 ≤ 10

IQR (CV) : 5 (0.6)

11 distinct values

2145 (44.9%)

statement_danger_sexequal [labelled, numeric]

Statement: Dangerous (Sex Equality)
How true do you find the statement above?

Differences in abilities of men and women are determined biologically

0 = Not at all dangerous; 10 = Extremely dangerous

Mean (sd) : 4.5 (3.1)

min ≤ med ≤ max:

0 ≤ 5 ≤ 10

IQR (CV) : 5 (0.7)

11 distinct values

2145 (44.9%)

statement_insult_gender [labelled, numeric]

Statement: Insulting (Gender Definition)
How insulting do you find the statement above?

A person’s gender is not given by birth but self-determined

0 = Not at all insulting; 10 = Extremely Insulting

Mean (sd) : 3.7 (3.2)

min ≤ med ≤ max:

0 ≤ 3 ≤ 10

IQR (CV) : 6 (0.9)

11 distinct values

2120 (44.4%)

statement_true_gender [labelled, numeric]

Statement: True (Gender Definition)
How true do you find the statement above?

A person’s gender is not given by birth but self-determined

0 = Untrue; 10 = True

Mean (sd) : 4.4 (3.4)

min ≤ med ≤ max:

0 ≤ 4 ≤ 10

IQR (CV) : 6 (0.8)

11 distinct values

2120 (44.4%)

statement_danger_gender [labelled, numeric]

Statement: Dangerous (Gender Definition)
How true do you find the statement above?

A person’s gender is not given by birth but self-determined

0 = Not at all dangerous; 10 = Extremely dangerous

Mean (sd) : 4.4 (3.2)

min ≤ med ≤ max:

0 ≤ 5 ≤ 10

IQR (CV) : 5 (0.7)

11 distinct values

2120 (44.4%)

statement_insult_climatedemo [labelled, numeric]

Statement: Insulting (Climate vs. Democracy)
How insulting do you find the statement above?

Saving the climate is more important than protecting democracy

0 = Not at all insulting; 10 = Extremely Insulting

Mean (sd) : 4.1 (3)

min ≤ med ≤ max:

0 ≤ 4 ≤ 10

IQR (CV) : 5 (0.7)

11 distinct values

2141 (44.9%)

statement_true_climatedemo [labelled, numeric]

Statement: True (Climate vs. Democracy) How true do you find the statement above?

STATEMENT

0 = Untrue; 10 = True

Mean (sd) : 4.2 (2.9)

min ≤ med ≤ max:

0 ≤ 4 ≤ 10

IQR (CV) : 4 (0.7)

11 distinct values

2141 (44.9%)

statement_danger_climatedemo [labelled, numeric]

Statement: Dangerous (Climate vs. Democracy)
How true do you find the statement above?

Saving the climate is more important than protecting democracy

0 = Not at all dangerous; 10 = Extremely dangerous

Mean (sd) : 6 (2.8)

min ≤ med ≤ max:

0 ≤ 6 ≤ 10

IQR (CV) : 4 (0.5)

11 distinct values

2141 (44.9%)

statement_insult_climateacti [labelled, numeric]

Statement: Insulting (Climate Activism)
How insulting do you find the statement above?

The measures against climate change are more harmful than climate change itself

0 = Not at all insulting; 10 = Extremely Insulting

Mean (sd) : 3.9 (3.1)

min ≤ med ≤ max:

0 ≤ 4 ≤ 10

IQR (CV) : 5 (0.8)

11 distinct values

2136 (44.8%)

statement_true_climateacti [labelled, numeric]

Statement: True (Climate Activism)
How true do you find the statement above?

The measures against climate change are more harmful than climate change itself

0 = Untrue; 10 = True

Mean (sd) : 4 (3.2)

min ≤ med ≤ max:

0 ≤ 4 ≤ 10

IQR (CV) : 6 (0.8)

11 distinct values

2136 (44.8%)

statement_danger_climateacti [labelled, numeric]

Statement: Dangerous (Climate Activism)
How true do you find the statement above?

The measures against climate change are more harmful than climate change itself

0 = Not at all dangerous; 10 = Extremely dangerous

Mean (sd) : 5.5 (3.1)

min ≤ med ≤ max:

0 ≤ 6 ≤ 10

IQR (CV) : 5 (0.6)

11 distinct values

2136 (44.8%)

Randomization Variables

Variables	Meaning
	STATEMENT SELECTION
io_statement_racists	Placement of ‘statement_racists’ evaluations in ‘Statement Ratings’ block
io_statement_racism	Placement of ‘statement_racism’ evaluations in ‘Statement Ratings’ block
io_statement_borders	Placement of ‘statement_borders’ evaluations in ‘Statement Ratings’ block
io_statement_immigration	Placement of ‘statement_immigration’ evaluations in ‘Statement Ratings’ block
io_statement_sexequal	Placement of ‘statement_sexequal’ evaluations in ‘Statement Ratings’ block
io_statement_gender	Placement of ‘statement_gender’ evaluations in ‘Statement Ratings’ block
io_statement_climatedemo	Placement of ‘statement_climatedemo’ evaluations in ‘Statement Ratings’ block
io_statement_climateacti	Placement of ‘statement_climateacti’ evaluations in ‘Statement Ratings’ block
	EVALUATING ORDER
qo_statement_true	At which position ‘true’ question was placed throughout each statement’s evaluation
qo_statement_danger	At which position ‘danger’ question was placed throughout each statement’s evaluation
qo_statement_insult	At which position ‘insult’ question was placed throughout each statement’s evaluation

Int. Humility & Grandstanding

Descriptive Overview

Variable

Label

Stats / Values

Freqs (% of Valid)

Graph

Valid

inthum_oth_winning [labelled, factor]

Intellectual Humility of Others: Winning
Here are some statements that can apply more or less to other people. Please tell us to what extent the singular statements generally apply in your opinion. [Randomized Group ...]
... rather want to win a discussion than learn something
Item reversed in post-coding

1. Applies

2. R. Applies

3. R. Doesn't Apply

4. Doesn't Apply

586	(	14.1%	)
1534	(	36.9%	)
1438	(	34.6%	)
599	(	14.4%	)

4157 (87.1%)

inthum_oth_defensive [labelled, factor]

Intellectual Humility of Others: Defensive
Here are some statements that can apply more or less to other people. Please tell us to what extent the singular statements generally apply in your opinion. [Randomized Group ...]
... get defensive, when others don't agree with them
Item reversed in post-coding

1. Applies

2. R. Applies

3. R. Doesn't Apply

4. Doesn't Apply

510	(	12.3%	)
1508	(	36.3%	)
1460	(	35.1%	)
679	(	16.3%	)

4157 (87.1%)

inthum_oth_ridicule [labelled, factor]

Intellectual Humility of Others: Redicule
Here are some statements that can apply more or less to other people. Please tell us to what extent the singular statements generally apply in your opinion. [Randomized Group ...]
... make fun of people with other attitudes
Item reversed in post-coding

1. Applies

2. R. Applies

3. R. Doesn't Apply

4. Doesn't Apply

409	(	9.8%	)
1359	(	32.7%	)
1397	(	33.6%	)
992	(	23.9%	)

4157 (87.1%)

inthum_oth_open [labelled, factor]

Intellectual Humility of Others: Open
Here are some statements that can apply more or less to other people. Please tell us to what extent the singular statements generally apply in your opinion. [Randomized Group ...]
... are open for the ideas of others

1. Doesn't Apply

2. R. Doesn't Apply

3. R. Applies

4. Applies

343	(	8.3%	)
1307	(	31.4%	)
1923	(	46.3%	)
584	(	14.0%	)

4157 (87.1%)

inthum_self_attack [labelled, factor]

Own Intellectual Humility: Personal Attack
Here are some statements that can apply more or less to yourself. Please tell us to what extent the singular statements generally apply to you.
When someone disagrees with ideas that are important to me, it feels like a personal attack
Item reversed in post-coding

1. Applies

2. R. Applies

3. R. Doesn't Apply

4. Doesn't Apply

205	(	4.9%	)
1121	(	27.0%	)
1977	(	47.5%	)
855	(	20.6%	)

4158 (87.1%)

inthum_self_change [labelled, factor]

Own Intellectual Humility: Change
Here are some statements that can apply more or less to yourself. Please tell us to what extent the singular statements generally apply to you.
I am ready to change my opinion based on convincing reasons

1. Doesn't Apply

2. R. Doesn't Apply

3. R. Applies

4. Applies

167	(	4.0%	)
630	(	15.2%	)
2366	(	56.9%	)
995	(	23.9%	)

4158 (87.1%)

inthum_self_respect [labelled, factor]

Own Intellectual Humility: Respect
Here are some statements that can apply more or less to yourself. Please tell us to what extent the singular statements generally apply to you.
I can have great respect for someone, even if do not share an opinion on important topics

1. Doesn't Apply

2. R. Doesn't Apply

3. R. Applies

4. Applies

119	(	2.9%	)
462	(	11.1%	)
1950	(	46.9%	)
1627	(	39.1%	)

4158 (87.1%)

inthum_self_better [labelled, factor]

Own Intellectual Humility: Better
Here are some statements that can apply more or less to yourself. Please tell us to what extent the singular statements generally apply to you.
Normally, my ideas are better than the ideas of other humans
Item reversed in post-coding

1. Applies

2. R. Applies

3. R. Doesn't Apply

4. Doesn't Apply

220	(	5.3%	)
1537	(	37.0%	)
1860	(	44.7%	)
541	(	13.0%	)

4158 (87.1%)

inthum_self_mean [labelled, numeric]

Own Intellectual Humility: Mean
Mean Score of the four ego-focused ‘intellectual humility’ items

Mean (sd) : 2.9 (0.5)

min ≤ med ≤ max:

1.5 ≤ 3 ≤ 4

IQR (CV) : 0.8 (0.2)

11 distinct values

4158 (87.1%)

inthum_oth_mean [labelled, numeric]

Intellectual Humility of Others: Mean
Mean Score of the four group-focused ‘intellectual humility’ items

Mean (sd) : 2.6 (0.7)

min ≤ med ≤ max:

1 ≤ 2.5 ≤ 4

IQR (CV) : 1 (0.3)

13 distinct values

4157 (87.1%)

mgs_self_convince [labelled, factor]

Own Moral Grandstanding: Convincing
Please tell us to what extent the following statements generally apply to you in your opinon.
I hope that my [ political / moral ] views convince other people to share the same views

1. Doesn't Apply

2. R. Doesn't Apply

3. R. Applies

4. Applies

473	(	11.4%	)
1162	(	28.0%	)
2130	(	51.3%	)
385	(	9.3%	)

4150 (87.0%)

mgs_self_history [labelled, factor]

Own Moral Grandstanding: History
Please tell us to what extent the following statements generally apply to you in your opinon.
Regarding [ political / moral ] views, I want to stand on the right side of history

1. Doesn't Apply

2. R. Doesn't Apply

3. R. Applies

4. Applies

506	(	12.2%	)
985	(	23.7%	)
2105	(	50.7%	)
554	(	13.3%	)

4150 (87.0%)

mgs_self_sharing [labelled, factor]

Own Moral Grandstanding: Sharing
Please tell us to what extent the following statements generally apply to you in your opinon.
Even if it helps nobody when I share my [ political / moral ] views, it is important to me that I share them

1. Doesn't Apply

2. R. Doesn't Apply

3. R. Applies

4. Applies

597	(	14.4%	)
1237	(	29.8%	)
1787	(	43.1%	)
529	(	12.7%	)

4150 (87.0%)

mgs_self_shaming [labelled, factor]

Own Moral Grandstanding: Shaming
Please tell us to what extent the following statements generally apply to you in your opinon.
I share my [ political / moral ] views, so that people who have different opinions are ashamed

1. Doesn't Apply

2. R. Doesn't Apply

3. R. Applies

4. Applies

1817	(	43.8%	)
1519	(	36.6%	)
664	(	16.0%	)
150	(	3.6%	)

4150 (87.0%)

mgs_self_better [labelled, factor]

Own Moral Grandstanding: Better
Please tell us to what extent the following statements generally apply to you in your opinon.
When I share my [ political / moral ] views, I want to show people who have other opinions that I am better than them

1. Doesn't Apply

2. R. Doesn't Apply

3. R. Applies

4. Applies

1570	(	37.8%	)
1685	(	40.6%	)
723	(	17.4%	)
172	(	4.1%	)

4150 (87.0%)

mgs_oth_convince [labelled, factor]

Moral Grandstanding of Others: Convincing
Please tell us to what extent the following statements generally apply to [randomized group] in your opinon.
[Randomized Group] hope that their [ political / moral ] views convince other people to share the same views

1. Doesn't Apply

2. R. Doesn't Apply

3. R. Applies

4. Applies

460	(	11.1%	)
1118	(	26.9%	)
2111	(	50.9%	)
460	(	11.1%	)

4149 (86.9%)

mgs_oth_history [labelled, factor]

Moral Grandstanding of Others: History
Please tell us to what extent the following statements generally apply to [randomized group] in your opinon.
Regarding [ political / moral ] views, [randomized group] want to stand on the right side of history

1. Doesn't Apply

2. R. Doesn't Apply

3. R. Applies

4. Applies

411	(	9.9%	)
1076	(	25.9%	)
2204	(	53.1%	)
458	(	11.0%	)

4149 (86.9%)

mgs_oth_sharing [labelled, factor]

Moral Grandstanding of Others: Sharing
Please tell us to what extent the following statements generally apply to [randomized group] in your opinon.
Even if it helps nobody when they share their [ political / moral ] views, it is important to [randomized group] that they share them

1. Doesn't Apply

2. R. Doesn't Apply

3. R. Applies

4. Applies

444	(	10.7%	)
1185	(	28.6%	)
1996	(	48.1%	)
524	(	12.6%	)

4149 (86.9%)

mgs_oth_shaming [labelled, factor]

Moral Grandstanding of Others: Shaming
Please tell us to what extent the following statements generally apply to [randomized group] in your opinon.
[Randomized Group] share their [ political / moral ] views, so that people who have different opinions are ashamed

1. Doesn't Apply

2. R. Doesn't Apply

3. R. Applies

4. Applies

1105	(	26.6%	)
1754	(	42.3%	)
1043	(	25.1%	)
247	(	6.0%	)

4149 (86.9%)

mgs_oth_better [labelled, factor]

Moral Grandstanding of Others: Better
Please tell us to what extent the following statements generally apply to [randomized group] in your opinon.
When [Randomized Group] share their [ political / moral ] views, they want to show people who have other opinions that they are better than them

1. Doesn't Apply

2. R. Doesn't Apply

3. R. Applies

4. Applies

850	(	20.5%	)
1625	(	39.2%	)
1364	(	32.9%	)
310	(	7.5%	)

4149 (86.9%)

mgs_self_mean [labelled, numeric]

Own Moral Grandstanding: Mean
Mean Score of the five ego-focused ‘moral grandstanding’ items

Mean (sd) : 2.3 (0.6)

min ≤ med ≤ max:

1 ≤ 2.4 ≤ 4

IQR (CV) : 0.6 (0.3)

16 distinct values

4150 (87.0%)

mgs_oth_mean [labelled, numeric]

Moral Grandstanding of Others: Mean
Mean Score of the five group-focused ‘moral grandstanding’ items

Mean (sd) : 2.5 (0.6)

min ≤ med ≤ max:

1 ≤ 2.6 ≤ 4

IQR (CV) : 0.8 (0.2)

16 distinct values

4149 (86.9%)

Randomization Variables

Variables	Meaning
	CONTENTUAL RANDOMIZATIONS
mgs_type	Whether ‘Moral Grandstanding’ was asked about ‘moral’ or ‘political’ views
mgs_inthum_others	What reference group respondents’ should consider when thinking about the ‘others’
	ORDER RANDOMIZATIONS
io_inthum_oth_winning	Placement of ‘inthum_oth_winning’ in ‘Int. Humility: Others’ question matrix
io_inthum_oth_defensive	Placement of ‘inthum_oth_defensive’ in ‘Int. Humility: Others’ question matrix
io_inthum_oth_ridicule	Placement of ‘inthum_oth_ridicule’ in ‘Int. Humility: Others’ question matrix
io_inthum_oth_open	Placement of ‘inthum_oth_open’ in ‘Int. Humility: Others’ question matrix
io_inthum_self_attack	Placement of ‘inthum_self_attack’ in ‘Int. Humility: Self’ question matrix
io_inthum_self_change	Placement of ‘inthum_self_change’ in ‘Int. Humility: Self’ question matrix
io_inthum_self_respect	Placement of ‘inthum_self_respect’ in ‘Int. Humility: Self’ question matrix
io_inthum_self_better	Placement of ‘inthum_self_better’ in ‘Int. Humility: Self’ question matrix
io_mgs_self_convince	Placement of ‘mgs_self_convince’ in ‘Moral Grandstanding: Self’ question matrix
io_mgs_self_history	Placement of ‘mgs_self_history’ in ‘Moral Grandstanding: Self’ question matrix
io_mgs_self_sharing	Placement of ‘mgs_self_sharing’ in ‘Moral Grandstanding: Self’ question matrix
io_mgs_self_shaming	Placement of ‘mgs_self_shaming’ in ‘Moral Grandstanding: Self’ question matrix
io_mgs_self_better	Placement of ‘mgs_self_better’ in ‘Moral Grandstanding: Self’ question matrix
io_mgs_oth_convince	Placement of ‘mgs_oth_convince’ in ‘Moral Grandstanding: Others’ question matrix
io_mgs_oth_history	Placement of ‘mgs_oth_history’ in ‘Moral Grandstanding: Others’ question matrix
io_mgs_oth_sharing	Placement of ‘mgs_oth_sharing’ in ‘Moral Grandstanding: Others’ question matrix
io_mgs_oth_shaming	Placement of ‘mgs_oth_shaming’ in ‘Moral Grandstanding: Others’ question matrix
io_mgs_oth_better	Placement of ‘mgs_oth_better’ in ‘Moral Grandstanding: Others’ question matrix
	QUESTION RANDOMIZATIONS
qo_inthum_self	Placement of ‘Int. Humility: Self’ in ‘Intellectual Humility’ block
qo_inthum_oth	Placement of ‘Int. Humility: Others’ in ‘Intellectual Humility’ block
qo_mgs_self	Placement of ‘Moral Grandstanding: Self’ in ‘Moral Grandstanding’ block
qo_mgs_oth	Placement of ‘Moral Grandstanding: Others’ in ‘Moral Grandstanding’ block

Descriptive Overview split by ‘Moral’ vs. ‘Political’ Views

Group: mgs_type = Moral

Variable

Label

Stats / Values

Freqs (% of Valid)

Graph

Valid

mgs_self_convince [labelled, factor]

1. Doesn't Apply

2. R. Doesn't Apply

3. R. Applies

4. Applies

195	(	9.6%	)
562	(	27.6%	)
1078	(	53.0%	)
200	(	9.8%	)

2035 (86.7%)

mgs_self_history [labelled, factor]

1. Doesn't Apply

2. R. Doesn't Apply

3. R. Applies

4. Applies

213	(	10.5%	)
484	(	23.8%	)
1066	(	52.4%	)
272	(	13.4%	)

2035 (86.7%)

mgs_self_sharing [labelled, factor]

1. Doesn't Apply

2. R. Doesn't Apply

3. R. Applies

4. Applies

260	(	12.8%	)
605	(	29.7%	)
890	(	43.7%	)
280	(	13.8%	)

2035 (86.7%)

mgs_self_shaming [labelled, factor]

1. Doesn't Apply

2. R. Doesn't Apply

3. R. Applies

4. Applies

811	(	39.9%	)
793	(	39.0%	)
356	(	17.5%	)
75	(	3.7%	)

2035 (86.7%)

mgs_self_better [labelled, factor]

1. Doesn't Apply

2. R. Doesn't Apply

3. R. Applies

4. Applies

718	(	35.3%	)
854	(	42.0%	)
377	(	18.5%	)
86	(	4.2%	)

2035 (86.7%)

mgs_oth_convince [labelled, factor]

1. Doesn't Apply

2. R. Doesn't Apply

3. R. Applies

4. Applies

212	(	10.4%	)
529	(	26.0%	)
1072	(	52.7%	)
222	(	10.9%	)

2035 (86.7%)

mgs_oth_history [labelled, factor]

1. Doesn't Apply

2. R. Doesn't Apply

3. R. Applies

4. Applies

183	(	9.0%	)
506	(	24.9%	)
1107	(	54.4%	)
239	(	11.7%	)

2035 (86.7%)

mgs_oth_sharing [labelled, factor]

1. Doesn't Apply

2. R. Doesn't Apply

3. R. Applies

4. Applies

220	(	10.8%	)
561	(	27.6%	)
987	(	48.5%	)
267	(	13.1%	)

2035 (86.7%)

mgs_oth_shaming [labelled, factor]

1. Doesn't Apply

2. R. Doesn't Apply

3. R. Applies

4. Applies

502	(	24.7%	)
868	(	42.7%	)
544	(	26.7%	)
121	(	5.9%	)

2035 (86.7%)

mgs_oth_better [labelled, factor]

1. Doesn't Apply

2. R. Doesn't Apply

3. R. Applies

4. Applies

386	(	19.0%	)
804	(	39.5%	)
673	(	33.1%	)
172	(	8.5%	)

2035 (86.7%)

mgs_self_mean [labelled, numeric]

Own Moral Grandstanding: Mean
Mean Score of the five ego-focused ‘moral grandstanding’ items

Mean (sd) : 2.3 (0.6)

min ≤ med ≤ max:

1 ≤ 2.4 ≤ 4

IQR (CV) : 0.6 (0.2)

16 distinct values

2035 (86.7%)

mgs_oth_mean [labelled, numeric]

Moral Grandstanding of Others: Mean
Mean Score of the five group-focused ‘moral grandstanding’ items

Mean (sd) : 2.5 (0.6)

min ≤ med ≤ max:

1 ≤ 2.6 ≤ 4

IQR (CV) : 0.6 (0.2)

16 distinct values

2035 (86.7%)

Group: mgs_type = Political

Variable

Label

Stats / Values

Freqs (% of Valid)

Graph

Valid

mgs_self_convince [labelled, factor]

1. Doesn't Apply

2. R. Doesn't Apply

3. R. Applies

4. Applies

278	(	13.1%	)
600	(	28.4%	)
1052	(	49.7%	)
185	(	8.7%	)

2115 (87.2%)

mgs_self_history [labelled, factor]

1. Doesn't Apply

2. R. Doesn't Apply

3. R. Applies

4. Applies

293	(	13.9%	)
501	(	23.7%	)
1039	(	49.1%	)
282	(	13.3%	)

2115 (87.2%)

mgs_self_sharing [labelled, factor]

1. Doesn't Apply

2. R. Doesn't Apply

3. R. Applies

4. Applies

337	(	15.9%	)
632	(	29.9%	)
897	(	42.4%	)
249	(	11.8%	)

2115 (87.2%)

mgs_self_shaming [labelled, factor]

1. Doesn't Apply

2. R. Doesn't Apply

3. R. Applies

4. Applies

1006	(	47.6%	)
726	(	34.3%	)
308	(	14.6%	)
75	(	3.5%	)

2115 (87.2%)

mgs_self_better [labelled, factor]

1. Doesn't Apply

2. R. Doesn't Apply

3. R. Applies

4. Applies

852	(	40.3%	)
831	(	39.3%	)
346	(	16.4%	)
86	(	4.1%	)

2115 (87.2%)

mgs_oth_convince [labelled, factor]

1. Doesn't Apply

2. R. Doesn't Apply

3. R. Applies

4. Applies

248	(	11.7%	)
589	(	27.9%	)
1039	(	49.1%	)
238	(	11.3%	)

2114 (87.2%)

mgs_oth_history [labelled, factor]

1. Doesn't Apply

2. R. Doesn't Apply

3. R. Applies

4. Applies

228	(	10.8%	)
570	(	27.0%	)
1097	(	51.9%	)
219	(	10.4%	)

2114 (87.2%)

mgs_oth_sharing [labelled, factor]

1. Doesn't Apply

2. R. Doesn't Apply

3. R. Applies

4. Applies

224	(	10.6%	)
624	(	29.5%	)
1009	(	47.7%	)
257	(	12.2%	)

2114 (87.2%)

mgs_oth_shaming [labelled, factor]

1. Doesn't Apply

2. R. Doesn't Apply

3. R. Applies

4. Applies

603	(	28.5%	)
886	(	41.9%	)
499	(	23.6%	)
126	(	6.0%	)

2114 (87.2%)

mgs_oth_better [labelled, factor]

1. Doesn't Apply

2. R. Doesn't Apply

3. R. Applies

4. Applies

464	(	21.9%	)
821	(	38.8%	)
691	(	32.7%	)
138	(	6.5%	)

2114 (87.2%)

mgs_self_mean [labelled, numeric]

Own Moral Grandstanding: Mean
Mean Score of the five ego-focused ‘moral grandstanding’ items

Mean (sd) : 2.2 (0.6)

min ≤ med ≤ max:

1 ≤ 2.2 ≤ 4

IQR (CV) : 0.6 (0.3)

16 distinct values

2115 (87.2%)

mgs_oth_mean [labelled, numeric]

Moral Grandstanding of Others: Mean
Mean Score of the five group-focused ‘moral grandstanding’ items

Mean (sd) : 2.4 (0.6)

min ≤ med ≤ max:

1 ≤ 2.4 ≤ 4

IQR (CV) : 0.8 (0.3)

16 distinct values

2114 (87.2%)

Descriptive Overview split by “Others”

Group: mgs_inthum_others = Co-Workers

Variable

Label

Stats / Values

Freqs (% of Valid)

Graph

Valid

inthum_oth_winning [labelled, factor]

1. Applies

2. R. Applies

3. R. Doesn't Apply

4. Doesn't Apply

58	(	7.0%	)
269	(	32.4%	)
354	(	42.7%	)
148	(	17.9%	)

829 (87.9%)

inthum_oth_defensive [labelled, factor]

1. Applies

2. R. Applies

3. R. Doesn't Apply

4. Doesn't Apply

52	(	6.3%	)
251	(	30.3%	)
351	(	42.3%	)
175	(	21.1%	)

829 (87.9%)

inthum_oth_ridicule [labelled, factor]

1. Applies

2. R. Applies

3. R. Doesn't Apply

4. Doesn't Apply

42	(	5.1%	)
190	(	22.9%	)
343	(	41.4%	)
254	(	30.6%	)

829 (87.9%)

inthum_oth_open [labelled, factor]

1. Doesn't Apply

2. R. Doesn't Apply

3. R. Applies

4. Applies

76	(	9.2%	)
216	(	26.1%	)
413	(	49.8%	)
124	(	15.0%	)

829 (87.9%)

inthum_oth_mean [labelled, numeric]

Intellectual Humility of Others: Mean
Mean Score of the four group-focused ‘intellectual humility’ items

Mean (sd) : 2.8 (0.6)

min ≤ med ≤ max:

1 ≤ 3 ≤ 4

IQR (CV) : 1 (0.2)

13 distinct values

829 (87.9%)

mgs_oth_convince [labelled, factor]

1. Doesn't Apply

2. R. Doesn't Apply

3. R. Applies

4. Applies

134	(	16.2%	)
287	(	34.7%	)
360	(	43.5%	)
47	(	5.7%	)

828 (87.8%)

mgs_oth_history [labelled, factor]

1. Doesn't Apply

2. R. Doesn't Apply

3. R. Applies

4. Applies

112	(	13.5%	)
236	(	28.5%	)
413	(	49.9%	)
67	(	8.1%	)

828 (87.8%)

mgs_oth_sharing [labelled, factor]

1. Doesn't Apply

2. R. Doesn't Apply

3. R. Applies

4. Applies

109	(	13.2%	)
275	(	33.2%	)
383	(	46.3%	)
61	(	7.4%	)

828 (87.8%)

mgs_oth_shaming [labelled, factor]

1. Doesn't Apply

2. R. Doesn't Apply

3. R. Applies

4. Applies

257	(	31.0%	)
353	(	42.6%	)
184	(	22.2%	)
34	(	4.1%	)

828 (87.8%)

mgs_oth_better [labelled, factor]

1. Doesn't Apply

2. R. Doesn't Apply

3. R. Applies

4. Applies

206	(	24.9%	)
353	(	42.6%	)
233	(	28.1%	)
36	(	4.3%	)

828 (87.8%)

mgs_oth_mean [labelled, numeric]

Moral Grandstanding of Others: Mean
Mean Score of the five group-focused ‘moral grandstanding’ items

Mean (sd) : 2.3 (0.6)

min ≤ med ≤ max:

1 ≤ 2.4 ≤ 4

IQR (CV) : 0.7 (0.3)

16 distinct values

828 (87.8%)

Group: mgs_inthum_others = Friends

Variable

Label

Stats / Values

Freqs (% of Valid)

Graph

Valid

inthum_oth_winning [labelled, factor]

1. Applies

2. R. Applies

3. R. Doesn't Apply

4. Doesn't Apply

47	(	5.7%	)
190	(	22.9%	)
393	(	47.3%	)
200	(	24.1%	)

830 (88.3%)

inthum_oth_defensive [labelled, factor]

1. Applies

2. R. Applies

3. R. Doesn't Apply

4. Doesn't Apply

42	(	5.1%	)
175	(	21.1%	)
397	(	47.8%	)
216	(	26.0%	)

830 (88.3%)

inthum_oth_ridicule [labelled, factor]

1. Applies

2. R. Applies

3. R. Doesn't Apply

4. Doesn't Apply

36	(	4.3%	)
152	(	18.3%	)
319	(	38.4%	)
323	(	38.9%	)

830 (88.3%)

inthum_oth_open [labelled, factor]

1. Doesn't Apply

2. R. Doesn't Apply

3. R. Applies

4. Applies

45	(	5.4%	)
117	(	14.1%	)
491	(	59.2%	)
177	(	21.3%	)

830 (88.3%)

inthum_oth_mean [labelled, numeric]

Intellectual Humility of Others: Mean
Mean Score of the four group-focused ‘intellectual humility’ items

Mean (sd) : 3 (0.6)

min ≤ med ≤ max:

1 ≤ 3 ≤ 4

IQR (CV) : 0.8 (0.2)

13 distinct values

830 (88.3%)

mgs_oth_convince [labelled, factor]

1. Doesn't Apply

2. R. Doesn't Apply

3. R. Applies

4. Applies

106	(	12.8%	)
264	(	31.8%	)
391	(	47.2%	)
68	(	8.2%	)

829 (88.2%)

mgs_oth_history [labelled, factor]

1. Doesn't Apply

2. R. Doesn't Apply

3. R. Applies

4. Applies

92	(	11.1%	)
220	(	26.5%	)
429	(	51.7%	)
88	(	10.6%	)

829 (88.2%)

mgs_oth_sharing [labelled, factor]

1. Doesn't Apply

2. R. Doesn't Apply

3. R. Applies

4. Applies

89	(	10.7%	)
260	(	31.4%	)
396	(	47.8%	)
84	(	10.1%	)

829 (88.2%)

mgs_oth_shaming [labelled, factor]

1. Doesn't Apply

2. R. Doesn't Apply

3. R. Applies

4. Applies

283	(	34.1%	)
357	(	43.1%	)
151	(	18.2%	)
38	(	4.6%	)

829 (88.2%)

mgs_oth_better [labelled, factor]

1. Doesn't Apply

2. R. Doesn't Apply

3. R. Applies

4. Applies

235	(	28.3%	)
371	(	44.8%	)
186	(	22.4%	)
37	(	4.5%	)

829 (88.2%)

mgs_oth_mean [labelled, numeric]

Moral Grandstanding of Others: Mean
Mean Score of the five group-focused ‘moral grandstanding’ items

Mean (sd) : 2.3 (0.6)

min ≤ med ≤ max:

1 ≤ 2.4 ≤ 4

IQR (CV) : 0.6 (0.3)

16 distinct values

829 (88.2%)

Group: mgs_inthum_others = Online

Variable

Label

Stats / Values

Freqs (% of Valid)

Graph

Valid

inthum_oth_winning [labelled, factor]

1. Applies

2. R. Applies

3. R. Doesn't Apply

4. Doesn't Apply

243	(	29.5%	)
394	(	47.9%	)
139	(	16.9%	)
47	(	5.7%	)

823 (86.8%)

inthum_oth_defensive [labelled, factor]

1. Applies

2. R. Applies

3. R. Doesn't Apply

4. Doesn't Apply

217	(	26.4%	)
418	(	50.8%	)
147	(	17.9%	)
41	(	5.0%	)

823 (86.8%)

inthum_oth_ridicule [labelled, factor]

1. Applies

2. R. Applies

3. R. Doesn't Apply

4. Doesn't Apply

194	(	23.6%	)
427	(	51.9%	)
152	(	18.5%	)
50	(	6.1%	)

823 (86.8%)

inthum_oth_open [labelled, factor]

1. Doesn't Apply

2. R. Doesn't Apply

3. R. Applies

4. Applies

116	(	14.1%	)
398	(	48.4%	)
238	(	28.9%	)
71	(	8.6%	)

823 (86.8%)

inthum_oth_mean [labelled, numeric]

Intellectual Humility of Others: Mean
Mean Score of the four group-focused ‘intellectual humility’ items

Mean (sd) : 2.1 (0.6)

min ≤ med ≤ max:

1 ≤ 2 ≤ 4

IQR (CV) : 0.8 (0.3)

13 distinct values

823 (86.8%)

mgs_oth_convince [labelled, factor]

1. Doesn't Apply

2. R. Doesn't Apply

3. R. Applies

4. Applies

48	(	5.8%	)
137	(	16.7%	)
486	(	59.2%	)
150	(	18.3%	)

821 (86.6%)

mgs_oth_history [labelled, factor]

1. Doesn't Apply

2. R. Doesn't Apply

3. R. Applies

4. Applies

63	(	7.7%	)
213	(	25.9%	)
441	(	53.7%	)
104	(	12.7%	)

821 (86.6%)

mgs_oth_sharing [labelled, factor]

1. Doesn't Apply

2. R. Doesn't Apply

3. R. Applies

4. Applies

53	(	6.5%	)
144	(	17.5%	)
442	(	53.8%	)
182	(	22.2%	)

821 (86.6%)

mgs_oth_shaming [labelled, factor]

1. Doesn't Apply

2. R. Doesn't Apply

3. R. Applies

4. Applies

115	(	14.0%	)
330	(	40.2%	)
300	(	36.5%	)
76	(	9.3%	)

821 (86.6%)

mgs_oth_better [labelled, factor]

1. Doesn't Apply

2. R. Doesn't Apply

3. R. Applies

4. Applies

80	(	9.7%	)
239	(	29.1%	)
384	(	46.8%	)
118	(	14.4%	)

821 (86.6%)

mgs_oth_mean [labelled, numeric]

Moral Grandstanding of Others: Mean
Mean Score of the five group-focused ‘moral grandstanding’ items

Mean (sd) : 2.7 (0.6)

min ≤ med ≤ max:

1 ≤ 2.8 ≤ 4

IQR (CV) : 0.6 (0.2)

16 distinct values

821 (86.6%)

Group: mgs_inthum_others = Others

Variable

Label

Stats / Values

Freqs (% of Valid)

Graph

Valid

inthum_oth_winning [labelled, factor]

1. Applies

2. R. Applies

3. R. Doesn't Apply

4. Doesn't Apply

173	(	20.3%	)
452	(	53.1%	)
181	(	21.3%	)
45	(	5.3%	)

851 (85.9%)

inthum_oth_defensive [labelled, factor]

1. Applies

2. R. Applies

3. R. Doesn't Apply

4. Doesn't Apply

144	(	16.9%	)
465	(	54.6%	)
199	(	23.4%	)
43	(	5.1%	)

851 (85.9%)

inthum_oth_ridicule [labelled, factor]

1. Applies

2. R. Applies

3. R. Doesn't Apply

4. Doesn't Apply

102	(	12.0%	)
425	(	49.9%	)
245	(	28.8%	)
79	(	9.3%	)

851 (85.9%)

inthum_oth_open [labelled, factor]

1. Doesn't Apply

2. R. Doesn't Apply

3. R. Applies

4. Applies

58	(	6.8%	)
352	(	41.4%	)
361	(	42.4%	)
80	(	9.4%	)

851 (85.9%)

inthum_oth_mean [labelled, numeric]

Intellectual Humility of Others: Mean
Mean Score of the four group-focused ‘intellectual humility’ items

Mean (sd) : 2.3 (0.6)

min ≤ med ≤ max:

1 ≤ 2.2 ≤ 4

IQR (CV) : 0.8 (0.2)

13 distinct values

851 (85.9%)

mgs_oth_convince [labelled, factor]

1. Doesn't Apply

2. R. Doesn't Apply

3. R. Applies

4. Applies

54	(	6.4%	)
146	(	17.2%	)
511	(	60.3%	)
137	(	16.2%	)

848 (85.6%)

mgs_oth_history [labelled, factor]

1. Doesn't Apply

2. R. Doesn't Apply

3. R. Applies

4. Applies

47	(	5.5%	)
180	(	21.2%	)
488	(	57.5%	)
133	(	15.7%	)

848 (85.6%)

mgs_oth_sharing [labelled, factor]

1. Doesn't Apply

2. R. Doesn't Apply

3. R. Applies

4. Applies

58	(	6.8%	)
206	(	24.3%	)
445	(	52.5%	)
139	(	16.4%	)

848 (85.6%)

mgs_oth_shaming [labelled, factor]

1. Doesn't Apply

2. R. Doesn't Apply

3. R. Applies

4. Applies

144	(	17.0%	)
373	(	44.0%	)
265	(	31.2%	)
66	(	7.8%	)

848 (85.6%)

mgs_oth_better [labelled, factor]

1. Doesn't Apply

2. R. Doesn't Apply

3. R. Applies

4. Applies

96	(	11.3%	)
309	(	36.4%	)
362	(	42.7%	)
81	(	9.6%	)

848 (85.6%)

mgs_oth_mean [labelled, numeric]

Moral Grandstanding of Others: Mean
Mean Score of the five group-focused ‘moral grandstanding’ items

Mean (sd) : 2.7 (0.6)

min ≤ med ≤ max:

1 ≤ 2.6 ≤ 4

IQR (CV) : 0.6 (0.2)

16 distinct values

848 (85.6%)

Group: mgs_inthum_others = Relatives

Variable

Label

Stats / Values

Freqs (% of Valid)

Graph

Valid

inthum_oth_winning [labelled, factor]

1. Applies

2. R. Applies

3. R. Doesn't Apply

4. Doesn't Apply

65	(	7.9%	)
229	(	27.8%	)
371	(	45.0%	)
159	(	19.3%	)

824 (86.7%)

inthum_oth_defensive [labelled, factor]

1. Applies

2. R. Applies

3. R. Doesn't Apply

4. Doesn't Apply

55	(	6.7%	)
199	(	24.2%	)
366	(	44.4%	)
204	(	24.8%	)

824 (86.7%)

inthum_oth_ridicule [labelled, factor]

1. Applies

2. R. Applies

3. R. Doesn't Apply

4. Doesn't Apply

35	(	4.2%	)
165	(	20.0%	)
338	(	41.0%	)
286	(	34.7%	)

824 (86.7%)

inthum_oth_open [labelled, factor]

1. Doesn't Apply

2. R. Doesn't Apply

3. R. Applies

4. Applies

48	(	5.8%	)
224	(	27.2%	)
420	(	51.0%	)
132	(	16.0%	)

824 (86.7%)

inthum_oth_mean [labelled, numeric]

Intellectual Humility of Others: Mean
Mean Score of the four group-focused ‘intellectual humility’ items

Mean (sd) : 2.9 (0.6)

min ≤ med ≤ max:

1 ≤ 3 ≤ 4

IQR (CV) : 0.8 (0.2)

13 distinct values

824 (86.7%)

mgs_oth_convince [labelled, factor]

1. Doesn't Apply

2. R. Doesn't Apply

3. R. Applies

4. Applies

118	(	14.3%	)
284	(	34.5%	)
363	(	44.1%	)
58	(	7.0%	)

823 (86.6%)

mgs_oth_history [labelled, factor]

1. Doesn't Apply

2. R. Doesn't Apply

3. R. Applies

4. Applies

97	(	11.8%	)
227	(	27.6%	)
433	(	52.6%	)
66	(	8.0%	)

823 (86.6%)

mgs_oth_sharing [labelled, factor]

1. Doesn't Apply

2. R. Doesn't Apply

3. R. Applies

4. Applies

135	(	16.4%	)
300	(	36.5%	)
330	(	40.1%	)
58	(	7.0%	)

823 (86.6%)

mgs_oth_shaming [labelled, factor]

1. Doesn't Apply

2. R. Doesn't Apply

3. R. Applies

4. Applies

306	(	37.2%	)
341	(	41.4%	)
143	(	17.4%	)
33	(	4.0%	)

823 (86.6%)

mgs_oth_better [labelled, factor]

1. Doesn't Apply

2. R. Doesn't Apply

3. R. Applies

4. Applies

233	(	28.3%	)
353	(	42.9%	)
199	(	24.2%	)
38	(	4.6%	)

823 (86.6%)

mgs_oth_mean [labelled, numeric]

Moral Grandstanding of Others: Mean
Mean Score of the five group-focused ‘moral grandstanding’ items

Mean (sd) : 2.3 (0.6)

min ≤ med ≤ max:

1 ≤ 2.2 ≤ 4

IQR (CV) : 0.6 (0.3)

16 distinct values

823 (86.6%)

Grievances

Descriptive Overview

Variable

Label

Stats / Values

Freqs (% of Valid)

Graph

Valid

class [labelled, numeric]

Perceived Social Class
Imagine that a ladder represents the different social classes of the republic's society. On top of the ladder - on rung 10 - stand the people who do best: They have the most money, the best education and a job with high prestige. At the bottom on the laddert - on rung 1 - stand the people who do worst: They have the least money, the least education and no job or a job, that noone wants and respects. Please indicate, which rung of the ladder corresponds to your current position in society

Mean (sd) : 5.6 (1.9)

min ≤ med ≤ max:

1 ≤ 6 ≤ 10

IQR (CV) : 2 (0.3)

1	:	85	(	2.1%	)
2	:	130	(	3.1%	)
3	:	352	(	8.5%	)
4	:	452	(	10.9%	)
5	:	817	(	19.8%	)
6	:	873	(	21.1%	)
7	:	855	(	20.7%	)
8	:	385	(	9.3%	)
9	:	95	(	2.3%	)
10	:	91	(	2.2%	)

4135 (86.7%)

fairness [labelled, factor]

Perceived Fairness
Compared to other people living here in Germany: Do you believe that you personally receive your fair share, or do you personally receive more or less than your fair share?

1. A lot less ...

2. A little less ...

3. My Fair Share

4. A little more ...

5. A lot more ...

447	(	10.8%	)
1290	(	31.2%	)
1938	(	46.9%	)
348	(	8.4%	)
106	(	2.6%	)

4129 (86.5%)

trust [labelled, numeric]

General Trust
Generally speaking: Do you believe one can trust most people or that one cannot be careful enough when dealing with other people?
0 = One cannot be careful enough; 10 = One can trust most people

Mean (sd) : 4.8 (2.6)

min ≤ med ≤ max:

0 ≤ 5 ≤ 10

IQR (CV) : 4 (0.5)

11 distinct values

4119 (86.3%)

depri_econ [labelled, factor]

Perceived Deprivation: Economic
To what extent do you agree with the following statements?
The economic situation of people like my does not get anough attention in society

1. Don't Agree

2. R. Don't Agree

3. Partially

4. R. Agree

5. Agree

402	(	9.7%	)
618	(	15.0%	)
1334	(	32.3%	)
1087	(	26.3%	)
686	(	16.6%	)

4127 (86.5%)

depri_recog [labelled, factor]

Perceived Deprivation: Recognition
To what extent do you agree with the following statements?
People like me do not get enough recognition by society for the work they do

1. Don't Agree

2. R. Don't Agree

3. Partially

4. R. Agree

5. Agree

460	(	11.1%	)
682	(	16.5%	)
1281	(	31.0%	)
1078	(	26.1%	)
626	(	15.2%	)

4127 (86.5%)

depri_infra [labelled, factor]

Perceived Deprivation: Infrastructure
To what extent do you agree with the following statements?
Society does not care enough about providing people like me access to basic facilities and services (like, for example, post offices, doctors, banks, public transport, schools, internet)

1. Don't Agree

2. R. Don't Agree

3. Partially

4. R. Agree

5. Agree

988	(	23.9%	)
967	(	23.4%	)
1172	(	28.4%	)
647	(	15.7%	)
353	(	8.6%	)

4127 (86.5%)

depri_mean [labelled, numeric]

Perceived Deprivation: Mean
Mean Score of the three ‘deprivation’ item

Mean (sd) : 3 (1)

min ≤ med ≤ max:

1 ≤ 3 ≤ 5

IQR (CV) : 1.3 (0.3)

13 distinct values

4127 (86.5%)

lifesat [labelled, numeric]

Life Satisfaction
Now we want to ask you about your satisfaction with your life as a whole today. How satisfied are you, everything considered, currently with your life? Please reply with the values from 0 'Completly unsatisfied' to 10 'Completly Satisfied'

Mean (sd) : 5.9 (2.4)

min ≤ med ≤ max:

0 ≤ 7 ≤ 10

IQR (CV) : 4 (0.4)

11 distinct values

4136 (86.7%)

Randomization Variables

Variables	Meaning
io_depri_econ	Placement of ‘depri_econ’ in ‘Deprivation’ question matrix
io_depri_recog	Placement of ‘depri_recop’ in ‘Deprivation’ question matrix
io_depri_infra	Placement of ‘depri_infra’ in ‘Deprivation’ question matrix

List Experiment: Direct

Descriptive Overview

Variable

Label

Stats / Values

Freqs (% of Valid)

Graph

Valid

listex_direct_equality [labelled, factor]

List Experiment: Direct (Equality)
Do you agree or disagree with the following statements?
State measures for female equality in society are already going to far

1. No

2. Yes

3073	(	73.4%	)
1116	(	26.6%	)

4189 (87.8%)

listex_direct_immigration [labelled, factor]

List Experiment: Direct (Immigration)
Do you agree or disagree with the following statements?
Immigrants should be obliged to assimilate into the German culture

1. No

2. Yes

1559	(	37.2%	)
2630	(	62.8%	)

4189 (87.8%)

listex_direct_liberty [labelled, factor]

List Experiment: Direct (Liberty)
Do you agree or disagree with the following statements?
In emergencies it is justified that the state limits citizens' liberties

1. No

2. Yes

1931	(	46.1%	)
2258	(	53.9%	)

4189 (87.8%)

listex_direct_climate [labelled, factor]

List Experiment: Direct (Climate)
Do you agree or disagree with the following statements?
To fight climate change, levies on fossil fuels such as oil, gas and coal should be increased

1. No

2. Yes

2587	(	61.8%	)
1602	(	38.2%	)

4189 (87.8%)

listex_sensitive [labelled, numeric]

List Experiment: Count Treatment
Here are some statements which one can agree or disagree with. Please tell us how many of these statements you would agree with. Please do not tell us which ones you exactly agree with, just with how many.
Recoded: Value indicates the amount of items agreed with in list including the treatment item (= 4 items overall)

Mean (sd) : 2.1 (1)

min ≤ med ≤ max:

0 ≤ 2 ≤ 4

IQR (CV) : 1 (0.5)

0	:	214	(	5.0%	)
1	:	825	(	19.2%	)
2	:	1775	(	41.3%	)
3	:	1127	(	26.2%	)
4	:	356	(	8.3%	)

4297 (90.0%)

listex_control [labelled, numeric]

List Experiment: Count Control
Here are some statements which one can agree or disagree with. Please tell us how many of these statements you would agree with. Please do not tell us which ones you exactly agree with, just with how many.
Recoded: Value indicates the amount of items agreed with in list excluding the treatment item (= 3 items overall)

Mean (sd) : 1.7 (0.8)

min ≤ med ≤ max:

0 ≤ 2 ≤ 3

IQR (CV) : 1 (0.5)

0	:	273	(	6.4%	)
1	:	1340	(	31.2%	)
2	:	2047	(	47.6%	)
3	:	639	(	14.9%	)

4299 (90.1%)

Randomization Variables

Note: Which of the four sensitive items (for wording, see direct item questions) respondents received was based on their SFS Issue randomization, with the Baseline group receiving the equality item, the Government group receiving the liberty item, and the Immigration and Climate groups receiving the respectively fitting items.

Variables	Meaning
	DIRECT QUESTIONING
io_listex_direct_equality	Placement of ‘listex_direct_equality’ in ‘Direct List Experiment’ question matrix
io_listex_direct_immigration	Placement of ‘listex_direct_immigration’ in ‘Direct List Experiment’ question matrix
io_listex_direct_liberty	Placement of ‘listex_direct_liberty’ in ‘Direct List Experiment’ question matrix
io_listex_direct_climate	Placement of ‘listex_direct_climate’ in ‘Direct List Experiment’ question matrix
	EXPERIMENT COMPOSITION
io_listex_clist1_income	Placement of ‘income’ statement in ‘Control Set 1’
io_listex_clist1_eu	Placement of ‘eu’ statement in ‘Control Set 1’
io_listex_clist1_covid	Placement of ‘covid’ statement in ‘Control Set 1’
io_listex_clist1_sens	Placement of randomized sensitive statement in ‘Control Set 1’ (if applicable)
io_listex_clist2_referendum	Placement of ‘referendum’statement in ’Control Set 2’
io_listex_clist2_rent	Placement of ‘rent’ statement in ‘Control Set 2’
io_listex_clist2_economy	Placement of ‘economy’ statement in ‘Control Set 2’
io_listex_clist2_sens	Placement of randomized sensitive statement in ‘Control Set 2’ (if applicable)
io_listex_sens	Placement of randomized sensitive statement in either control set

qo_listex_clist1	Whether ‘Control Set 1’ was presented in first or second task
qo_listex_clist2	Whether ‘Control Set 2’ was presented in first or second task
listex_order	Whether the sensitive item was added in first or second task

Living History

The living history items records respondent’s home cities throughout their life in Germany. As this is sensitive information, access to it can only me granted after in-depth contact (via Menzner@em.uni-frankfurt.de). Recoded variables that show anonymized aggregate information might be available later.

GDR vs BRD

Descriptive Overview

Variable

Label

Stats / Values

Freqs (% of Valid)

Graph

Valid

lived_brd [labelled, factor]

Living in Former West-Germany
Please indicate if you lived in the following areas during the existence of the GDR, meaning between 1949 and 1990 (Multiple answers possible). Have you, in this time, at least partially lived in ...
Recoded: 'Yes' == '... West-Germany?' was selected

1. No

2. Yes

1820	(	44.6%	)
2264	(	55.4%	)

4084 (85.6%)

lived_gdr [labelled, factor]

Living in Former GDR
Please indicate if you lived in the following areas during the existence of the GDR, meaning between 1949 and 1990 (Multiple answers possible). Have you, in this time, at least partially lived in ...
Recoded: 'Yes' == '... East-Germany?' was selected

1. No

2. Yes

3018	(	73.9%	)
1066	(	26.1%	)

4084 (85.6%)

lived_outside [labelled, factor]

Residence during German Division: Other Country
Please indicate if you lived in the following areas during the existence of the GDR, meaning between 1949 and 1990 (Multiple answers possible). Have you, in this time, at least partially lived ...
Recoded: 'Yes' == '... outside of Germany?' was selected

1. No

2. Yes

3893	(	95.3%	)
191	(	4.7%	)

4084 (85.6%)

lifesat_gdr [labelled, numeric]

Life Satisfaction: GDR
Now we want to ask you about your satisfaction with your former life in the GDR as a whole. How satisfied were you, everything considered, with your former life? Please reply with the values from 0 'Completly unsatisfied' to 10 'Completly Satisfied'
Filter: lived_gdr == 'Yes'

Mean (sd) : 6.5 (2.2)

min ≤ med ≤ max:

0 ≤ 7 ≤ 10

IQR (CV) : 3 (0.3)

11 distinct values

1065 (22.3%)

lifesat_brd [labelled, numeric]

Life Satisfaction: BRD
Now we want to ask you about your satisfaction with your former life West-Germany as a whole. How satisfied were you, everything considered, with your former life? Please reply with the values from 0 'Completly unsatisfied' to 10 'Completly Satisfied'
Filter: lived_brd == 'Yes'

Mean (sd) : 7.6 (1.8)

min ≤ med ≤ max:

0 ≤ 8 ≤ 10

IQR (CV) : 2 (0.2)

11 distinct values

2260 (47.4%)

gdr_orga_fdgb [labelled, factor]

GDR Organisations: 'Freier Deutscher Gewerkschaftsbund'
Were you a member in one of the following mass organisations before 01.01.1989? (Multiple answers possible)
Filter: lived_gdr == 'Yes'
Recoded: 'Yes' == 'Ja, im Freien Deutschen Gewerkschaftsbund (FDGB)' was selected

1. No

2. Yes

681	(	65.6%	)
357	(	34.4%	)

1038 (21.8%)

gdr_orga_fdj [labelled, factor]

GDR Organisations: 'Freie Deutsche Jugend'
Were you a member in one of the following mass organisations before 01.01.1989? (Multiple answers possible)
Filter: lived_gdr == 'Yes'
Recoded: 'Yes' == 'Ja, in der Freien Deutschen Jugend (FDJ)' was selected

1. No

2. Yes

519	(	50.0%	)
519	(	50.0%	)

1038 (21.8%)

gdr_orga_dfd [labelled, factor]

GDR Organisations: 'Demokratischer Frauenbund Deutschlands'
Were you a member in one of the following mass organisations before 01.01.1989? (Multiple answers possible)
Filter: lived_gdr == 'Yes'
Recoded: 'Yes' == 'Ja, im Demokratischen Frauenbund Deutschlands (DFD)' was selected

1. No

2. Yes

996	(	96.0%	)
42	(	4.0%	)

1038 (21.8%)

gdr_orga_kb [labelled, factor]

GDR Organisations: 'Kulturbund'
Were you a member in one of the following mass organisations before 01.01.1989? (Multiple answers possible)
Filter: lived_gdr == 'Yes'
Recoded: 'Yes' == 'Ja, im Kulturbund (KB)' was selected

1. No

2. Yes

986	(	95.0%	)
52	(	5.0%	)

1038 (21.8%)

gdr_orga_dsf [labelled, factor]

GDR Organisations: 'Deutsch-Sowjetische Freundschaft'
Were you a member in one of the following mass organisations before 01.01.1989? (Multiple answers possible)
Filter: lived_gdr == 'Yes'
Recoded: 'Yes' == 'Ja, bei der Deutsch-Sowjetischen Freundschaft (DSF)' was selected

1. No

2. Yes

719	(	69.3%	)
319	(	30.7%	)

1038 (21.8%)

gdr_orga_other [labelled, character]

GDR Organisations: Other
Were you a member in one of the following mass organisations before 01.01.1989? (Multiple answers possible)
Filter: lived_gdr == 'Yes'

1. SED

2. DTSB

3. GST

4. Jungpioniere

5. Pioniere

6. Junge Pioniere

7. Pionier

8. Anglerverband

9. CDU

10. Den Jungpionieren, Vorstu

[ 12 others ]

7	(	15.6%	)
5	(	11.1%	)
5	(	11.1%	)
4	(	8.9%	)
4	(	8.9%	)
3	(	6.7%	)
2	(	4.4%	)
1	(	2.2%	)
1	(	2.2%	)
1	(	2.2%	)
12	(	26.7%	)

45 (0.9%)

gdr_oppo_self [labelled, factor]

GDR Opposition: Self
Were you yourself, family members or friends of yours engaged in the political or religious opposition in the GDR? (Multiple answers possible)
Filter: lived_gdr == 'Yes'
Recoded: 'Yes' == 'Ja, ich selbst' was selected

1. No

2. Yes

938	(	90.4%	)
100	(	9.6%	)

1038 (21.8%)

gdr_oppo_fam [labelled, factor]

GDR Opposition: Family
Were you yourself, family members or friends of yours engaged in the political or religious opposition in the GDR? (Multiple answers possible)
Filter: lived_gdr == 'Yes'
Recoded: 'Yes' == 'Ja, ein oder mehrere Familienmitglieder' was selected

1. No

2. Yes

903	(	87.0%	)
135	(	13.0%	)

1038 (21.8%)

gdr_oppo_friends [labelled, factor]

GDR Opposition: Friends
Were you yourself, family members or friends of yours engaged in the political or religious opposition in the GDR? (Multiple answers possible)
Filter: lived_gdr == 'Yes'
Recoded: 'Yes' == 'Ja, ein oder mehrere Freunde' was selected

1. No

2. Yes

950	(	91.5%	)
88	(	8.5%	)

1038 (21.8%)

gdr_moving [labelled, factor]

GDR Moving Away
Did you plan to move into the BRD or applied for an exit visa before 01.01.1989? (Multiple answers possible)
Filter: lived_gdr == 'Yes'
Recoded: 'Yes' == 'Ja, einen Umzug geplant' was selected

1. No

2. Yes

979	(	94.4%	)
58	(	5.6%	)

1037 (21.7%)

gdr_emigration [labelled, factor]

GDR Exit Visa
Did you plan to move into the BRD or applied for an exit visa before 01.01.1989? (Multiple answers possible)
Filter: lived_gdr == 'Yes'
Recoded: 'Yes' == 'Ja, einen Ausreiseantrag gestellt' was selected

1. No

2. Yes

953	(	91.9%	)
84	(	8.1%	)

1037 (21.7%)

gdr_escape [labelled, factor]

GDR Escape
How is it with escapes, so-called illegal border crossings, into Western foreign states.
Filter: lived_gdr == 'Yes'
Recoded based on five answer categories: 'never thought about it', 'only played it through in the mind', 'concretly planned, but not executed', 'executed but failed', 'successfully executed'

1. Never

2. Thoughts

3. Plans

4. Failed

5. Success

744	(	71.8%	)
213	(	20.6%	)
52	(	5.0%	)
2	(	0.2%	)
25	(	2.4%	)

1036 (21.7%)

gdr_escapeattempt [labelled, factor]

GDR Escape Attempt
How is it with escapes, so-called illegal border crossings, into Western foreign states.
Filter: lived_gdr == 'Yes'
Recoded: 'Yes' = gdr_escape == 'Failed | gdr_escape == 'Success'

1. No

2. Yes

1009	(	97.4%	)
27	(	2.6%	)

1036 (21.7%)

gdr_escapeyear [labelled, character]

GDR Escape Year
How is it with escapes, so-called illegal border crossings, into Western foreign states.
Filter: lived_gdr == 'Yes' & (gdr_escape == 'Failed' | gdr_escape == 'Success')

1. 1989
2. 1960
3. 1988
4. 1951
5. 1953
6. 1956
7. 1959
8. 1961
9. 1966
10. 1982
[ 7 others ]

6	(	23.1%	)
3	(	11.5%	)
3	(	11.5%	)
1	(	3.8%	)
1	(	3.8%	)
1	(	3.8%	)
1	(	3.8%	)
1	(	3.8%	)
1	(	3.8%	)
1	(	3.8%	)
7	(	26.9%	)

26 (0.5%)

gdr_surveillance [labelled, factor]

GDR Surveillance
When talking or reading about the GDR, one often finds hints that people controlled each other. Also the Ministry of State Security controlled and monitored the behavior of GDR citizens. How about you? Did you know or did you have the feeling that you have been observed or monitored by other people in your everyday live in the GDR?
Filter: lived_gdr == 'Yes'

1. No

2. Sometimes Feeling

3. General Feeling

4. Knew it

5. Refuse

372	(	35.9%	)
184	(	17.8%	)
137	(	13.2%	)
259	(	25.0%	)
84	(	8.1%	)

1036 (21.7%)

gdr_informants [labelled, factor]

GDR Informants
Do you suspect or know that someone has reported you to the GDR authorities?
Filter: lived_gdr == 'Yes'

1. No

2. Believe it

3. Know it

4. Refuse

579	(	55.9%	)
254	(	24.5%	)
140	(	13.5%	)
63	(	6.1%	)

1036 (21.7%)

gdr_prison_self [labelled, factor]

GDR Prison: Self
Were you yourself, family members or friends of yours ever imprisoned for political reasons before the re-unification? (Multiple answers possible) Please also indicate 'Yes' if the official reasoning was another, but you nevertheless suspect political reasons.
Filter: lived_gdr == 'Yes'
Recoded: 'Yes' == 'Ja, ich selbst' was selected

1. No

2. Yes

985	(	95.1%	)
51	(	4.9%	)

1036 (21.7%)

gdr_prison_fam [labelled, factor]

GDR Prison: Family
Were you yourself, family members or friends of yours ever imprisoned for political reasons before the re-unification? (Multiple answers possible) Please also indicate 'Yes' if the official reasoning was another, but you nevertheless suspect political reasons.
Filter: lived_gdr == 'Yes'
Recoded: 'Yes' == 'Ja, ein oder mehrere Familienmitglieder' was selected

1. No

2. Yes

931	(	89.9%	)
105	(	10.1%	)

1036 (21.7%)

gdr_prison_friends [labelled, factor]

GDR Prison: Friends
Were you yourself, family members or friends of yours ever imprisoned for political reasons before the re-unification? (Multiple answers possible) Please also indicate 'Yes' if the official reasoning was another, but you nevertheless suspect political reasons.
Filter: lived_gdr == 'Yes'
Recoded: 'Yes' == 'Ja, ein oder mehrere Freunde' was selected

1. No

2. Yes

956	(	92.3%	)
80	(	7.7%	)

1036 (21.7%)

gdr_stasi [labelled, factor]

GDR Stasi Contact
Has the Ministry of State Security ever in any form actively contacted you - e.g. in form of recruitment, questioning, interrogation, threatening of sanctions etc. Occupational and every-day contacts are not meant here
Filter: lived_gdr == 'Yes'

1. Never

2. Once

3. Multiple Times

769	(	74.3%	)
164	(	15.8%	)
102	(	9.9%	)

1035 (21.7%)

gdr_contacts_closerelative [labelled, factor]

GDR Contacts: Close Relatives (For Westerners)
Did you have relative or friends during the division of Germany who at least partially lived in the GDR? (Multiple answers possible)
Filter: lived_brd == 'Yes' & lived_gdr == 'No'
Recoded: 'Yes' == 'Ja, enge Verwandte' was selected

1. No

2. Yes

2004	(	87.3%	)
291	(	12.7%	)

2295 (48.1%)

gdr_contacts_distrelative [labelled, factor]

GDR Contacts: Distant Relatives (For Westerners)
Did you have relative or friends during the division of Germany who at least partially lived in the GDR? (Multiple answers possible)
Filter: lived_brd == 'Yes' & lived_gdr == 'No'
Recoded: 'Yes' == 'Ja, entfernte Verwandte' was selected

1. No

2. Yes

1951	(	85.0%	)
344	(	15.0%	)

2295 (48.1%)

gdr_contacts_closefriend [labelled, factor]

GDR Contacts: Close Friends (For Westerners)
Did you have relative or friends during the division of Germany who at least partially lived in the GDR? (Multiple answers possible)
Filter: lived_brd == 'Yes' & lived_gdr == 'No'
Recoded: 'Yes' == 'Ja, enge Freunde' was selected

1. No

2. Yes

2172	(	94.6%	)
123	(	5.4%	)

2295 (48.1%)

gdr_contacts_acquaintance [labelled, factor]

GDR Contacts: Distant Acquaintances (For Westerners)
Did you have relative or friends during the division of Germany who at least partially lived in the GDR? (Multiple answers possible)
Filter: lived_brd == 'Yes' & lived_gdr == 'No'
Recoded: 'Yes' == 'Ja, entfernte Bekannte' was selected

1. No

2. Yes

2114	(	92.1%	)
181	(	7.9%	)

2295 (48.1%)

gdr_west_oppo_fam [labelled, factor]

GDR Opposition: Family (For Westerners)
Were family members or friends of yours engaged in the political or religious opposition in the GDR? (Multiple answers possible)
Filter: lived_brd == 'Yes' & lived_gdr == 'No' & gdr_contact_any == 'Yes'
Recoded: 'Yes' == 'Ja, ein oder mehrere Familienmitglieder' was selected

1. No

2. Yes

729	(	84.6%	)
133	(	15.4%	)

862 (18.1%)

gdr_west_oppo_friends [labelled, factor]

GDR Opposition: Friends (For Westerners)
Were family members or friends of yours engaged in the political or religious opposition in the GDR? (Multiple answers possible)
Filter: lived_brd == 'Yes' & lived_gdr == 'No' & gdr_contact_any == 'Yes'
Recoded: 'Yes' == 'Ja, ein oder mehrere Freunde' was selected

1. No

2. Yes

720	(	83.5%	)
142	(	16.5%	)

862 (18.1%)

gdr_west_escapeplanned [labelled, factor]

GDR Escape Planned (For Westerners)
Please indicate which of these statements applies according to your knowledge. Your relatives and former friends have ... an escape into the West
Filter: lived_brd == 'Yes' & lived_gdr == 'No' & gdr_contact_any == 'Yes'
Recoded: 'Yes' == 'only played it through in their mind' and/or 'concretly planned, but not executed' was selected

1. No

2. Yes

527	(	61.1%	)
335	(	38.9%	)

862 (18.1%)

gdr_west_escapeattempt [labelled, factor]

GDR Escape Planned (For Westerners)
Please indicate which of these statements applies according to your knowledge. Your relatives and former friends have ... an escape into the West
Filter: lived_brd == 'Yes' & lived_gdr == 'No' & gdr_contact_any == 'Yes'
Recoded: 'Yes' == 'executed but failed' and/or 'successfully executed' was selected

1. No

2. Yes

818	(	94.9%	)
44	(	5.1%	)

862 (18.1%)

gdr_west_escapeyear [labelled, character]

GDR Escape Year (For Westerners)
Please indicate which of these statements applies according to your knowledge. Your relatives and former friends have ... an escape into the West
Filter: lived_brd == 'Yes' & lived_gdr == 'No' & gdr_contact_any == 'Yes' & gdr_west_escapeattempt == 'Yes'

1. 1960
2. 1989
3. -99
4. 1961
5. 1988
6. 1980
7. 1984
8. 1990
9. ??
10. 1952
[ 15 others ]

6	(	13.6%	)
6	(	13.6%	)
3	(	6.8%	)
3	(	6.8%	)
3	(	6.8%	)
2	(	4.5%	)
2	(	4.5%	)
2	(	4.5%	)
1	(	2.3%	)
1	(	2.3%	)
15	(	34.1%	)

44 (0.9%)

gdr_west_prison_fam [labelled, factor]

GDR Prison: Family (For Westerners)
Were family members or friends of yours ever imprisoned for political reasons before the re-unification? (Multiple answers possible) Please also indicate 'Yes' if the official reasoning was another, but you nevertheless suspect political reasons.
Filter: lived_brd == 'Yes' & lived_gdr == 'No' & gdr_contact_any == 'Yes'
Recoded: 'Yes' == 'Ja, ein oder mehrere Familienmitglieder' was selected

1. No

2. Yes

738	(	85.7%	)
123	(	14.3%	)

861 (18.0%)

gdr_west_prison_friends [labelled, factor]

GDR Prison: Friends (For Westerners)
Were family members or friends of yours ever imprisoned for political reasons before the re-unification? (Multiple answers possible) Please also indicate 'Yes' if the official reasoning was another, but you nevertheless suspect political reasons.
Filter: lived_brd == 'Yes' & lived_gdr == 'No' & gdr_contact_any == 'Yes'
Recoded: 'Yes' == 'Ja, ein oder mehrere Freunde' was selected

1. No

2. Yes

741	(	86.1%	)
120	(	13.9%	)

861 (18.0%)

gdr_orga_sum [labelled, numeric]

GDR Organisations: Sum
Were you a member in one of the following mass organisations before 01.01.1989? (Multiple answers possible)
Filter: lived_gdr == 'Yes'
Recoded: Sum of indicated organisations

Mean (sd) : 1.3 (1.2)

min ≤ med ≤ max:

0 ≤ 1 ≤ 5

IQR (CV) : 2 (1)

0	:	371	(	35.7%	)
1	:	272	(	26.2%	)
2	:	171	(	16.5%	)
3	:	179	(	17.2%	)
4	:	42	(	4.0%	)
5	:	3	(	0.3%	)

1038 (21.8%)

gdr_oppo_any [labelled, factor]

GDR Opposition: Any
Were you yourself, family members or friends of you engaged in the political or religious opposition in the GDR? (Multiple answers possible)
Filter: lived_gdr == 'Yes'
Recoded: 'Yes' == 'Nein, weder ich selbst noch Familie oder Freunde' was not selected

1. No

2. Yes

751	(	72.4%	)
287	(	27.6%	)

1038 (21.8%)

gdr_oppo_sum [labelled, numeric]

GDR Opposition: Sum
Were you yourself, family members or friends of you engaged in the political or religious opposition in the GDR? (Multiple answers possible)
Filter: lived_gdr == 'Yes'
Recoded: Sum of indicated answer options

Mean (sd) : 0.3 (0.5)

min ≤ med ≤ max:

0 ≤ 0 ≤ 3

IQR (CV) : 1 (1.8)

0	:	751	(	72.4%	)
1	:	258	(	24.9%	)
2	:	22	(	2.1%	)
3	:	7	(	0.7%	)

1038 (21.8%)

gdr_prison_any [labelled, factor]

GDR Prison: Any
Were you yourself, family members or friends of yours ever imprisoned for political reasons before the re-unification? (Multiple answers possible) Please also indicate 'Yes' if the official reasoning was another, but you nevertheless suspect political reasons.
Filter: lived_gdr == 'Yes'
Recoded: 'Yes' == 'Nein, weder ich selbst noch Familie oder Freunde' was not selected

1. No

2. Yes

812	(	78.4%	)
224	(	21.6%	)

1036 (21.7%)

gdr_prison_sum [labelled, numeric]

GDR Prison: Sum
Were you yourself, family members or friends of yours ever imprisoned for political reasons before the re-unification? (Multiple answers possible) Please also indicate 'Yes' if the official reasoning was another, but you nevertheless suspect political reasons.
Filter: lived_gdr == 'Yes'
Recoded: Sum of indicated answers

Mean (sd) : 0.2 (0.4)

min ≤ med ≤ max:

0 ≤ 0 ≤ 2

IQR (CV) : 0 (2)

0	:	812	(	78.4%	)
1	:	212	(	20.5%	)
2	:	12	(	1.2%	)

1036 (21.7%)

gdr_contact_any [labelled, factor]

GDR Contacts: Any (For Westerners)
Did you have relative or friends during the division of Germany who at least partially lived in the GDR? (Multiple answers possible)
Filter: lived_brd == 'Yes' & lived_gdr == 'No'
Recoded: 'Yes' == 'Nein, ich kannte damals niemanden persönlich, der in der DDR gelebt hat' was not selected

1. No

2. Yes

1433	(	67.8%	)
681	(	32.2%	)

2114 (44.3%)

gdr_west_oppo_any [labelled, factor]

GDR Opposition: Any (For Westerners)
Were family members or friends of yours engaged in the political or religious opposition in the GDR? (Multiple answers possible)
Filter: lived_brd == 'Yes' & lived_gdr == 'No' & gdr_contact_any == 'Yes'
Recoded: 'Yes' == 'Nein, weder Famile oder Freunde' was not selected

1. No

2. Yes

267	(	31.0%	)
595	(	69.0%	)

862 (18.1%)

gdr_west_prison_any [labelled, factor]

GDR Prison: Any (For Westerners)
Were family members or friends of yours ever imprisoned for political reasons before the re-unification? (Multiple answers possible) Please also indicate 'Yes' if the official reasoning was another, but you nevertheless suspect political reasons.
Filter: lived_brd == 'Yes' & lived_gdr == 'No' & gdr_contact_any == 'Yes'
Recoded: 'Yes' == 'Nein, weder Familienmitglieder noch Freunde' was not selected

1. No

2. Yes

626	(	72.7%	)
235	(	27.3%	)

861 (18.0%)

Randomization Variables

Variables	Meaning
io_gdr_orga_fdgb	Placement of ‘gdr_orga_fdgb’ in ‘GDR Organisations’ question matrix
io_gdr_orga_fdj	Placement of ‘gdr_orga_fdj’ in ‘GDR Organisations’ question matrix
io_gdr_orga_dfd	Placement of ‘gdr_orga_dfd’ in ‘GDR Organisations’ question matrix
io_gdr_orga_kb	Placement of ‘gdr_orga_kb’ in ‘GDR Organisations’ question matrix
io_gdr_orga_dsf	Placement of ‘gdr_orga_dsf’ in ‘GDR Organisations’ question matrix
io_gdr_orga_other	Placement of ‘gdr_orga_other’ in ‘GDR Organisations’ question matrix
io_gdr_orga_none	Placement of ‘gdr_orga_none’ in ‘GDR Organisations’ question matrix
qo_gdr_orga	Whether ‘GDR Organisations’ question came first or second (vs. Opposition)
qo_gdr_oppo	Whether ‘GDR Opposition’ question came first or second (vs. Organisations)

Socio-Demographics

Variable

Label

Stats / Values

Freqs (% of Valid)

Graph

Valid

female [labelled, factor]

Gender: Female
How would you yourself describe your gender?
Yes == 'Female'; No == 'Male', 'Divers' or 'Other'

1. No

2. Yes

2251	(	47.2%	)
2521	(	52.8%	)

4772 (100.0%)

male [labelled, factor]

Gender: Male
How would you yourself describe your gender?
Yes == 'Male'; No == 'Female', 'Divers' or 'Other'

1. No

2. Yes

2539	(	53.2%	)
2233	(	46.8%	)

4772 (100.0%)

age [labelled, numeric]

Age
How old are you?

Mean (sd) : 45.3 (16.9)

min ≤ med ≤ max:

18 ≤ 45 ≤ 99

IQR (CV) : 28 (0.4)

71 distinct values

4771 (100.0%)

east [labelled, factor]

Residence East/West-Germany
Do you currently have your main residence in the old states (formerly West-Germany) or the new states (formerly East-Germany)?
Recoded so that 'Yes' == 'East'

1. West

2. East

3390	(	71.0%	)
1382	(	29.0%	)

4772 (100.0%)

education [labelled, factor]

Education
What is your highest general education or vocational degree?

1. Abend-Gym

2. Abi

3. Apprenticeship

4. Fachabi

5. Haupt

6. In School

7. None

8. Other

9. Real

10. Uni-Degree

479	(	10.0%	)
1205	(	25.3%	)
208	(	4.4%	)
449	(	9.4%	)
278	(	5.8%	)
8	(	0.2%	)
26	(	0.5%	)
81	(	1.7%	)
856	(	17.9%	)
1182	(	24.8%	)

4772 (100.0%)

education_cat [labelled, factor]

Education Categories
What is your highest general education or vocational degree?
Recoded based on education variable

1. Abi

2. High School

3. Master

4. None

5. Other

6. Uni-Degree

1654	(	38.5%	)
1134	(	26.4%	)
208	(	4.8%	)
34	(	0.8%	)
81	(	1.9%	)
1182	(	27.5%	)

4293 (90.0%)

education_abi [labelled, factor]

High School (Abi)
What is your highest general education or vocational degree?
Recoded so that 'Yes' == at least 'Abitur'

1. No

2. Yes

1457	(	33.9%	)
2836	(	66.1%	)

4293 (90.0%)

nationality_german [labelled, factor]

Statehood: German
Which statehood do you possess?
Yes == 'Only German' | 'German and Other'; No == 'One or more Other(s)'

1. No

2. Yes

131	(	3.3%	)
3853	(	96.7%	)

3984 (83.5%)

nationality_oth [labelled, character]

Statehood: Other
Which statehood do you possess?
Only asked for respondents who indicated 'German and Other' or 'One or more Other(s)'

1. Deutsch

2. Türkisch

3. Österreich

4. Polnisch

5. Russisch

6. Französische

7. Britisch

8. Griechisch

9. Italienische

10. Schweiz

[ 115 others ]

10	(	4.8%	)
10	(	4.8%	)
8	(	3.8%	)
8	(	3.8%	)
7	(	3.4%	)
5	(	2.4%	)
4	(	1.9%	)
4	(	1.9%	)
4	(	1.9%	)
4	(	1.9%	)
144	(	69.2%	)

208 (4.4%)

born_german [labelled, factor]

Country of Origin: German
In which country were you born?
Yes == 'In the territory of today's Germany'; No == 'Other'

1. No

2. Yes

263	(	6.6%	)
3716	(	93.4%	)

3979 (83.4%)

born_oth [labelled, character]

Country of Origin: German
In which country were you born?
Only asked for respondents who indicated 'Other' as country of origin'

1. Polen

2. Russland

3. Deutschland

4. Kasachstan

5. Österreich

6. Türkei

7. Frankreich

8. Rumänien

9. polen

10. Ukraine

[ 107 others ]

31	(	11.8%	)
21	(	8.0%	)
9	(	3.4%	)
9	(	3.4%	)
9	(	3.4%	)
8	(	3.0%	)
7	(	2.7%	)
7	(	2.7%	)
6	(	2.3%	)
6	(	2.3%	)
150	(	57.0%	)

263 (5.5%)

parents_german [labelled, factor]

Country of Origin: German (Parents)
In which country were your parents born?
Original anser categories: 'Both in the territory of today's Germany'; 'One parent in the territory of today's Germany, the other in ...', 'Both parents in a different country, namely in ...'

1. Both

2. None

3. One

3340	(	84.0%	)
362	(	9.1%	)
275	(	6.9%	)

3977 (83.3%)

parent_nationality [labelled, character]

Country of Origin: Other (1 Parent)
In which country were your parents born?
Only asked for respondents who indicated 'One parent in the territory of today's Germany, the other in ...'

1. Polen

2. Schlesien

3. Frankreich

4. Italien

5. Tschechien

6. Griechenland

7. Österreich

8. polen

9. Türkei

10. USA

[ 86 others ]

61	(	22.2%	)
13	(	4.7%	)
9	(	3.3%	)
9	(	3.3%	)
9	(	3.3%	)
7	(	2.5%	)
7	(	2.5%	)
7	(	2.5%	)
7	(	2.5%	)
7	(	2.5%	)
139	(	50.5%	)

275 (5.8%)

parents_nationality [labelled, character]

Country of Origin: Other (2 Parents)
In which country were your parents born?
Only asked for respondents who indicated 'Both parents in a different country, namely in ...'

1. Polen

2. Türkei

3. Russland

4. Kasachstan

5. Italien

6. Schlesien

7. Ostpreußen

8. Ungarn

9. polen

10. Rumänien

[ 141 others ]

45	(	12.4%	)
34	(	9.4%	)
24	(	6.6%	)
15	(	4.1%	)
7	(	1.9%	)
7	(	1.9%	)
6	(	1.7%	)
6	(	1.7%	)
5	(	1.4%	)
5	(	1.4%	)
208	(	57.5%	)

362 (7.6%)

migration_background [labelled, factor]

Migration Background
Recoded Variable
'No': nationality_german == 'Yes' & born_german == 'Yes' & parents_german == 'Both', 'Yes': Any of these three conditions does not apply

1. No

2. Yes

3271	(	82.2%	)
708	(	17.8%	)

3979 (83.4%)

job_position [labelled, factor]

Job Position
Which of the following terms describes your job position the best?
Filter: job_position == 'Full-Time Employed' | 'Part-Time Employed'

1. Civil Servant

2. Employee

3. Self-Employed

4. Self-Employer

90	(	3.8%	)
2035	(	86.2%	)
152	(	6.4%	)
85	(	3.6%	)

2362 (49.5%)

job [labelled, factor]

Job What describes your current main job the best?

1. Apprenticeship

2. Betterment

3. FSJ/FÖJ

4. Full-Time Employed

5. Housewife/-husband

6. In School/Uni

7. Minijob

8. Other

9. Parental Leave

10. Part-Time Employed

[ 3 others ]

31	(	0.8%	)
21	(	0.5%	)
10	(	0.3%	)
1853	(	46.7%	)
140	(	3.5%	)
178	(	4.5%	)
69	(	1.7%	)
70	(	1.8%	)
46	(	1.2%	)
515	(	13.0%	)
1038	(	26.1%	)

3971 (83.2%)

job_ed_apprentice [labelled, factor]

Job Education: Apprenticeship Do you have a vocational training qualification - if so, which? (Multiple answers possible)
Yes: 'Beruflich-betriebliche Anlernzeit mit Abschlusszeugnis, aber keine Lehre', 'Teilfacharbeiterabschluss', 'Abgeschlossene gewerbliche oder landwirtschaftliche Lehre' or 'Abgeschlossene kaufmännische Lehre'

1. No

2. Yes

2530	(	63.6%	)
1445	(	36.4%	)

3975 (83.3%)

job_ed_trainee [labelled, factor]

Job Education: Traineeship Do you have a vocational training qualification - if so, which? (Multiple answers possible)
Yes: 'Berufliches Praktikum, Volontariat'

1. No

2. Yes

3912	(	98.4%	)
63	(	1.6%	)

3975 (83.3%)

job_ed_college [labelled, factor]

Job Education: College Do you have a vocational training qualification - if so, which? (Multiple answers possible)
Yes: 'Berufsfachschulabschluss' or 'Fachschulabschluss'

1. No

2. Yes

2949	(	74.2%	)
1026	(	25.8%	)

3975 (83.3%)

job_ed_technical [labelled, factor]

Job Education: Technical Do you have a vocational training qualification - if so, which? (Multiple answers possible)
Yes: 'Meister-, Techniker-, oder gleichwertigen Fachschulabschluss'

1. No

2. Yes

3657	(	92.0%	)
318	(	8.0%	)

3975 (83.3%)

job_ed_university [labelled, factor]

Job Education: University Do you have a vocational training qualification - if so, which? (Multiple answers possible)
Yes: 'Fachhochschulabschluss (auch Abschluss einer Ingenieurschule)' or 'Hochschulabschluss'

1. No

2. Yes

2727	(	68.6%	)
1248	(	31.4%	)

3975 (83.3%)

job_ed_other [labelled, character]

Job Education: Other Do you have a vocational training qualification - if so, which? (Multiple answers possible)
Filter: 'Other' was selected

1. Abitur

2. Staatsexamen

3. Ausbildung

4. Altenpflegerin

5. Geselle

6. Kinderpflegerin

7. Krankenschwester

8. Abgeschlossene Ausbildung

9. Abgeschlossene Beamtenaus

10. Abgeschlossene Lehre als

[ 67 others ]

8	(	8.2%	)
8	(	8.2%	)
4	(	4.1%	)
2	(	2.0%	)
2	(	2.0%	)
2	(	2.0%	)
2	(	2.0%	)
1	(	1.0%	)
1	(	1.0%	)
1	(	1.0%	)
67	(	68.4%	)

98 (2.1%)

job_ed_none [labelled, factor]

Job Education: None Do you have a vocational training qualification - if so, which? (Multiple answers possible)
Yes == 'None' was selected

1. No

2. Yes

3692	(	92.9%	)
283	(	7.1%	)

3975 (83.3%)

---
title: "SFS Wave 1 - Codebook"
author: "Jan Menzner"
date: "`r Sys.Date()`"
output:
  html_notebook:
    theme: darkly
    toc: yes
    toc_depth: 4
    toc_float: yes
  prettydoc::html_pretty:
    theme: architect
    toc: yes
    toc_depth: 4
  html_document:
    css: C:/R/win-library/3.4/summarytools/includes/stylesheets/summarytools.css
    toc: yes
    toc_float: yes
    toc_depth: '4'
    df_print: paged
editor_options: 
  chunk_output_type: inline
---

```{r packages, message=FALSE, warning=FALSE, echo=FALSE, results="hide"}

if (!require("pacman")) install.packages("pacman")
pacman::p_load(    # List all packages here - checks whether they are installed
  "rmdformats",    # Output
  "readr",         # For reading csv-data file
  "tidyverse",     # For data transformations
  "summarytools",  # For Codebook Stats
  "kable",         # Tables
  "kableExtra",     # Tables
  "prettydoc"
) 

```


```{r data, message=FALSE, warning=FALSE, echo=FALSE, results="hide"}
# Setting Working directory to folder where this script is located
library("rstudioapi")
setwd(dirname(rstudioapi::getActiveDocumentContext()$path))

# Importing data
load("wave1_final.RData")
wave1 <- wave1_anon
```

```{r tablesettings, echo = F}
st_options('footnote' = NA)          # Gets rid of citation in footnote
st_options('headings' = F)           # Gets rid of weird header over table
st_options('display.labels' = T)    # Displays variable and value labels
st_options('dfSummary.na.col' = F)  # Excludes NA column
st_options(dfSummary.graph.magnif = 0.75) # Shrink graphs
# st_options(dfSummary.custom.1 = NA) # No IQR etc. in the Stats / Values column
st_options(dfSummary.varnumbers	= F) # No numbering of vars
# st_options(dfSummary.custom.1 = expression(paste(
#   "Valid Obs:"), format_number(sum(!is.na(wave1$sfs)), round.digits), 
#   paste0("(", format_number(sum(!is.na(column_data)/length(wave1$sfs)), round.digits) ,"%)"),
#   "Missing:", format_number(sum(is.na(column_data)), round.digits), 
#   paste0("(", format_number(sum(is.na(column_data)/length(wave1$sfs)), round.digits) ,"%)"),
#   collapse = "", sep = "")
# )
```

## Meta-Data

##  Information / Read Me

If there are any questions about the data set or requests to share data, please direct them to: *Menzner@em.uni-frankfurt.de*. 

### Information about randomized display orders 

This survey includes many randomizations - both in explicitly designed experiments and in order to avoid and detect ordering effects. In each section of the following overview, first descriptive statistics will be presented for the contextual variables followed by a table-style overview of randomization variables. These include:

a) Variables starting with **"io_"** denote the displayed *item order* within a larger answer matrix underneath a single question.
b) Variables starting with **"qo_"** denote the displayed *question order* within a question block.
c) Variables starting with **"bo_"** denote the displayed *block order* within the overall survey flow. 
d) Additional contextual randomizations (e.g. within question phrasing) are explained explicitly within their respective section.

Note, that generally the presented descriptive data is the average over all randomizations. For some select, relevant cases, we also present the descriptive data for the singular randomization conditions. 

## General Items
```{r, echo = F}
# Selecting relevant variables
general <- wave1 %>% 
  dplyr::select(attentioncheck, duration)

# Printing data description
table <- summarytools::dfSummary(general)
view(table, method = 'render')
```

- **start** denotes date and time the respondent started the survey
- **end** denotes date and time the respondent finished the survey

## SFS Variables

### Descriptive Overview

```{r, echo = F}
# Selecting relevant variables
sfs <- wave1 %>% 
  dplyr::select(starts_with("sfs")) %>% 
  dplyr::select(-sfs_issue)

# Printing data description
table <- summarytools::dfSummary(sfs)
view(table, method = 'render')
```

### Randomization Variables

```{r, echo=F, warning= F, include = T}
sfs_random <- data.frame( Variables = c(" ",
  "io_sfs_family", "io_sfs_friends", "io_sfs_neighbor", "io_sfs_internet", "io_sfs_work", "io_sfs_stranger", " ",
  "io_sancdisprob_disagreement", "io_sancdisprob_insulting", "io_sancdisprob_justifying", "io_sancdisprob_hurting", "io_sancdisprob_misunderstood", " ",
  "io_sancdisexp_disagreement", "io_sancdisexp_insulting", "io_sancdisexp_justifying", "io_sancdisexp_hurting", "io_sancdisexp_misunderstood", " ",
  "io_sancsocprob_radical", "io_sancsocprob_online", "io_sancsocprob_falsepraise", "io_sancsocprob_wronggroup"," ",
  "io_sancsocexp_radical", "io_sancsocexp_online", "io_sancsocexp_falsepraise", "io_sancsocexp_wronggroup", " ",
  "io_sancclaprob_friends", "io_sancclaprob_job",  "io_sancclaprob_law",  "io_sancclaprob_harm",  " ",
  "io_sancclaexp_friends", "io_sancclaexp_job",  "io_sancclaexp_law",  "io_sancclaexp_harm", " ",
  "bo_sancdis", "bo_sancsoc", "bo_sanccla", " ", "qo_prob", "qo_exp", " ",
  "io_sanctdir_family", "io_sanctdir_friends", "io_sanctdir_neighbor", "io_sanctdir_boss", "io_sanctdir_colleagues", " ",
  "io_sancteli_politics", "io_sancteli_media", "io_sancteli_elites",  " ",
  "io_sancton_smcompany", "io_sancton_smusers", "io_sancton_smregulation", " ",
  "io_sanctpol_activists", "io_sanctpol_left", "io_sanctpol_right", " ",
  "qo_sanctdir", "qo_sancteli", "qo_sancton", "qo_sanctpol", " ",
  "io_sfs_left", "io_sfs_green", "io_sfs_spd", "io_sfs_cdu", "io_sfs_csu", "io_sfs_fdp", "io_sfs_afd", " ",
  "bo_sfs_countries_ger", "bo_sfs_countries_gdr", "bo_sfs_countries_ns", " ", "qo_sfs_countries_public", "qo_sfs_countries_state"),
  Meaning = c("SFS SOCIAL CONTEXTS",
              "Placement of 'sfs_family' in 'SFS Social Context' question matrix",
              "Placement of 'sfs_friends' in 'SFS Social Context' question matrix",
              "Placement of 'sfs_neighbor' in 'SFS Social Context' question matrix",
              "Placement of 'sfs_internet' in 'SFS Social Context' question matrix",
              "Placement of 'sfs_work' in 'SFS Social Context' question matrix",
              "Placement of 'sfs_stranger' in 'SFS Social Context' question matrix",
              "SANCTION VARIABLES",
              "Placement of 'sancdisprob_disagreement' in 'Sanction Probability: Discursive' question matrix",
              "Placement of 'sancdisprob_insulting' in 'Sanction Probability: Discursive' question matrix",
              "Placement of 'sancdisprob_justifying' in 'Sanction Probability: Discursive' question matrix",
              "Placement of 'sancdisprob_hurting' in 'Sanction Probability: Discursive' question matrix",
              "Placement of 'sancdisprob_misunderstood' in 'Sanction Probability: Discursive' question matrix",
              " ",
              "Placement of 'sancdisexp_disagreement' in 'Sanction Experience: Discursive' question matrix",
              "Placement of 'sancdisexp_insulting' in 'Sanction Experience: Discursive' question matrix",
              "Placement of 'sancdisexp_justifying' in 'Sanction Experience: Discursive' question matrix",
              "Placement of 'sancdisexp_hurting' in 'Sanction Experience: Discursive' question matrix",
              "Placement of 'sancdisexp_misunderstood' in 'Sanction Experience: Discursive' question matrix",
              " ",
              "Placement of 'sancsocprob_radical' in 'Sanction Probability: Social' question matrix",
              "Placement of 'sancsocprob_online' in 'Sanction Probability: Social' question matrix",
              "Placement of 'sancsocprob_falsepraise' in 'Sanction Probability: Social' question matrix",
              "Placement of 'sancsocprob_wronggroup' in 'Sanction Probability: Social' question matrix",
              " ",
              "Placement of 'sancsocexp_radical' in 'Sanction Experience: Social' question matrix",
              "Placement of 'sancsocexp_online' in 'Sanction Experience: Social' question matrix",
              "Placement of 'sancsocexp_falsepraise' in 'Sanction Experience: Social' question matrix",
              "Placement of 'sancsocexp_wronggroup' in 'Sanction Experience: Social' question matrix",
              " ",
              "Placement of 'sancclaprob_friends' in 'Sanction Probability: Classical' question matrix",
              "Placement of 'sancclaprob_job' in 'Sanction Probability: Classical' question matrix",
              "Placement of 'sancclaprob_law' in 'Sanction Probability: Classical' question matrix",              
              "Placement of 'sancclaprob_harm' in 'Sanction Probability: Classical' question matrix",
              " ",
              "Placement of 'sancclaexp_friends' in 'Sanction Experience: Classical' question matrix",
              "Placement of 'sancclaexp_job' in 'Sanction Experience: Classical' question matrix",
              "Placement of 'sancclaexp_law' in 'Sanction Experience: Classical' question matrix",              
              "Placement of 'sancclaexp_harm' in 'Sanction Experience: Classical' question matrix",
              " ",
              "Placement of 'Discursive Sanctions' block in 'Sanctions' module",
              "Placement of 'Social Sanctions' block in 'Sanctions' module",
              "Placement of 'Classical Sanctions' block in 'Sanctions' module",
              " ",
              "Order of 'probablity' and 'experience' items throughout sanction evaluations: 'Probability' ",
              "Order of 'probablity' and 'experience' items throughout sanction evaluations: 'Experience' ",
              "SANCTIONERS VARIABLES",
              "Placement of 'sanctdir_family' in 'Sanctioners: Direct' question matrix",
              "Placement of 'sanctdir_friends' in 'Sanctioners: Direct' question matrix",
              "Placement of 'sanctdir_neighbor' in 'Sanctioners: Direct' question matrix",
              "Placement of 'sanctdir_boss' in 'Sanctioners: Direct' question matrix",
              "Placement of 'sanctdir_colleagues' in 'Sanctioners: Direct' question matrix",
              " ",
              "Placement of 'sancteli_politics' in 'Sanctioners: Elites' question matrix",
              "Placement of 'sancteli_media' in 'Sanctioners: Elites' question matrix",
              "Placement of 'sancteli_elites' in 'Sanctioners: Elites' question matrix",
              " ",
              "Placement of 'sancton_smcompany' in 'Sanctioners: Social Media' question matrix",
              "Placement of 'sancton_smusers' in 'Sanctioners: Social Media' question matrix",
              "Placement of 'sancton_smregulation' in 'Sanctioners: Social Media' question matrix",
              " ",
              "Placement of 'sanctpol_activists' in 'Sanctioners: Political' question matrix",
              "Placement of 'sanctpol_left' in 'Sanctioners: Political' question matrix",
              "Placement of 'sanctpol_right' in 'Sanctioners: Political' question matrix",
              " ",
              "Placement of 'Sanctioners: Direct' question matrix in survey block order",
              "Placement of 'Sanctioners: Elites' question matrix in survey block order",
              "Placement of 'Sanctioners: Social Media' question matrix in survey block order",
              "Placement of 'Sanctioners: Political' question matrix in survey block order",
              "PARTY INFLUENCE ON SFS",
              "Placement of 'sfs_left' in 'Party SFS' question matrix",
              "Placement of 'sfs_green' in 'Party SFS' question matrix",
              "Placement of 'sfs_spd' in 'Party SFS' question matrix",
              "Placement of 'sfs_cdu' in 'Party SFS' question matrix",
              "Placement of 'sfs_csu' in 'Party SFS' question matrix",
              "Placement of 'sfs_fdp' in 'Party SFS' question matrix",
              "Placement of 'sfs_afd' in 'Party SFS' question matrix",
              "SFS IN GERMANY: EVALUATIONS",
              "Placement of evaluations of 'Germany' in country evaluation block",
              "Placement of evaluations of 'GDR' in country evaluation block",
              "Placement of evaluations of 'National Socialism' in country evaluation block",
              " ",
              "Order of evaluating 'public' and 'state' restrictions throughout country evaluations : 'Public' ",
              "Order of evaluating 'public' and 'state' restrictions throughout country evaluations : 'State' ") 
)

kable(sfs_random, format = "pipe", align = c("l", "l")) %>% 
  kable_classic(full_width = T, position = "center" ) 
```

#### Descriptive Overview split by SFS Issues

```{r, echo = F}
# Printing data by issue randomization
sfs <- wave1 %>%
  dplyr::select(starts_with("sfs"))

sfs_byissue <- by(data = sfs,
                  INDICES = sfs$sfs_issue, 
                  FUN = dfSummary, 
                  transpose = TRUE,
                  )

view(sfs_byissue, method = "render")
```
## Sanctions
```{r, echo = F}
# Selecting relevant variables
sanc <- wave1 %>% 
  dplyr::select(starts_with("sanc"))
# Printing data description
table <- summarytools::dfSummary(sanc)
view(table, method = 'render')
```
## (Self-)Censorship

### Descriptive Overview
```{r, echo=F}
# Selecting relevant variables
cens <- wave1 %>% 
  dplyr::select(starts_with("cens"))

# Printing data description
table <- summarytools::dfSummary(cens)
view(table, method = 'render')
```

### Randomization Variables

```{r, echo = F, warning = F, include = T}
cens_random <- data.frame(Variables = c("io_censself_hurting", "io_censself_majority", "io_censself_correcting", "io_censself_agreement", "io_censself_disagreement",  "io_censoth_democracy", "io_censoth_silencing", "io_censoth_unacceptable", "io_censoth_duty", "io_censoth_inform", "qo_censself", "qo_censoth"),
                          Meaning = c("Placement of 'censself_hurting' in 'Self-Censorship' question matrix",
                                      "Placement of 'censself_majority' in 'Self-Censorship' question matrix",
                                      "Placement of 'censself_correcting' in 'Self-Censorship' question matrix",
                                      "Placement of 'censself_agreement' in 'Self-Censorship' question matrix",
                                      "Placement of 'censself_disagreement' in 'Self-Censorship' question matrix",
                                      "Placement of 'censoth_democracy' in 'Willingness to Censor Others' question matrix",
                                      "Placement of 'censoth_silencing' in 'Willingness to Censor Others' question matrix",
                                      "Placement of 'censoth_unacceptable' in 'Willingness to Censor Others' question matrix",
                                      "Placement of 'censoth_duty' in 'Willingness to Censor Others' question matrix",
                                      "Placement of 'censoth_inform' in 'Willingness to Censor Others' question matrix",
                                      "Placement of 'Self-Censorship' question matrix in 'Censorship' module",
                                      "Placement of 'Willingness to Censor Others' question matrix in 'Censorship' module"
                                      
                                      )
)

kable(cens_random, format = "pipe", align = c("l", "l")) %>% 
  kable_classic(full_width = T, position = "center" ) 

```


## De-Platforming

### Descriptive Overview
```{r, echo=F}
# Selecting relevant variables
deplat <- wave1 %>% 
  dplyr::select(starts_with("deplat")) %>% 
  dplyr::select(-deplat_target)

# Printing data description
table <- summarytools::dfSummary(deplat)
view(table, method = 'render')
```


### Randomization Variables

*Note: When evaluating the item order randomizations, consider that item "deplat_electionposter" was not asked for those who received the 'controversial speaker' as a randomized target of the de-platforming measures. *

```{r, echo = F, warning = F, include = T}
deplat_random <- data.frame(Variables = c("deplat_target", "io_deplat_advertising", "io_deplat_electionposter", "io_deplat_entering", "io_deplat_screaming", "io_deplat_violence", "io_deplat_online", "io_deplat_work", "io_deplat_partners"),
                            Meaning = c("Randomized Target of De-Platforming Measures",
                                        "Placement of 'deplat_advertising' in 'De-Platforming' question matrix",
                                        "Placement of 'deplat_electionposter' in 'De-Platforming' question matrix",
                                        "Placement of 'deplat_entering' in 'De-Platforming' question matrix",
                                        "Placement of 'deplat_screaming' in 'De-Platforming' question matrix",
                                        "Placement of 'deplat_violence' in 'De-Platforming' question matrix",
                                        "Placement of 'deplat_online' in 'De-Platforming' question matrix",
                                        "Placement of 'deplat_work' in 'De-Platforming' question matrix",
                                        "Placement of 'deplat_partners' in 'De-Platforming' question matrix"
                                        )
) # Attention that electionposter doesnt always apply

kable(deplat_random, format = "pipe", align = c("l", "l")) %>% 
  kable_classic(full_width = T, position = "center" ) 

```
#### Descriptive Overview split by De-Platforming Target

```{r, echo = F}
# Selecting relevant variables
deplat <- wave1 %>% 
  dplyr::select(starts_with("deplat"))

deplat_byissue <- by(data = deplat,
                  INDICES = deplat$deplat_target, 
                  FUN = dfSummary, 
                  transpose = TRUE
                  )

view(deplat_byissue, method = "render")
```

## Conjoint Experiment: Allowed to say

### Variables

*Note: There were ten randomized conjoint statements to which support was surveyed binary (with ave. agreement around 60 %). The variables for all ten iterations follow the same logic as the one presented below (replacing "1" with the numbers "2" to "10").*

Example Statement with randomization variable labels in brackets: Ein männlicher [Female] Politiker [Speaker ID], der regelmäßg [Frequency] Homosexuelle [Target ID  & Targetgroup] im Internet [Context] bedroht [Content], sollte eine Geldstrafe zahlen müssen [Response], wenn diese Gruppe sich beleidigt fühlt [Reaction].


```{r, echo = F, warning = F, include = T}
conjoint_random <- data.frame(Variables = c(" ", "conj1", " ", "conj1_speakerfemale", "conj1_speakerid", "conj1_targetgroup", "conj1_targetsex", "conj1_targetid", "conj1_context", "conj1_response", "conj1_frequency", "conj1_content", "conj1_reaction"),
                             Meaning = c("OUTCOME VARIABLES", 
                                         "Agreement with the statement", 
                                         "RANDOMIZED ATTRIBUTES", 
                                         "Whether speaker is female or not",
                                         "The speaker's social identity",
                                         "Whether the target is a group or a singular person",
                                         "If a singular person, the target's sex",
                                         "The target's social identity",
                                         "In which social context the situation is placed",
                                         "Which sanction the speaker should face",
                                         "How often the situation occurs",
                                         "What the speaker effectively says",
                                         "How the target reacts")
                             )
kable(conjoint_random, format = "pipe", align = c("l", "l")) %>% 
  kable_classic(full_width = T, position = "center" ) 
```


## Conservatism, Socialism, Liberalism

### Descriptive Overview
```{r, echo=F}
# Selecting relevant variables
conssoclib <- wave1 %>% 
  dplyr::select(starts_with("cons"), starts_with("soc"), starts_with("lib"))

# Printing data description
table <- summarytools::dfSummary(conssoclib)
view(table, method = 'render')
```
### Randomization Variables

```{r, echo=F, warning= F, include = T}
conssoclib_random <- data.frame( Variables = c("io_cons_maintain", "io_cons_together", "io_cons_important",
                                               "io_soc_equality",  "io_soc_empathy",  "io_soc_income",
                                               "io_lib_protection", "io_lib_interference", "io_lib_intervention",
                                               "qo_cons", "qo_soc", "qo_lib"), 
                                 Meaning = c("Placement of 'cons_maintain' in 'Conservatism' question matrix",
                                             "Placement of 'cons_together' in 'Conservatism' question matrix",
                                             "Placement of 'cons_important' in 'Conservatism' question matrix",
                                             "Placement of 'soc_equality' in 'Socialism' question matrix",
                                             "Placement of 'soc_empathy' in 'Socialism' question matrix",
                                             "Placement of 'soc_income' in 'Socialism' question matrix",
                                             "Placement of 'lib_protection' in 'Liberalism' question matrix",
                                             "Placement of 'lib_interference' in 'Liberalism' question matrix",
                                             "Placement of 'lib_intervention' in 'Liberalism' question matrix",
                                             "Placement of 'Conservatism' question matrix in survey block order",
                                             "Placement of 'Socialism' question matrix in survey block order",
                                             "Placement of 'Liberalism' question matrix in survey block order"
                                 )
)

kable(conssoclib_random, format = "pipe", align = c("l", "l")) %>% 
  kable_classic(full_width = T, position = "center" ) 
```



## Political Variables

### Descriptive Overview

```{r, echo=F}
# Selecting relevant variables
political <- wave1 %>% 
  dplyr::select(polint, starts_with("efficacy"), starts_with("ego_"))

# Printing data description
table <- summarytools::dfSummary(political)
view(table, method = 'render')
```
### Randomization Variables

```{r, echo = F, warning = F, include = T}

pol_random <- data.frame(Variables = c("io_efficacy_understanding", "io_efficacy_talking", "io_efficacy_complexity", "io_ego_clim", "io_ego_tax", "io_ego_cimm"),
                Meaning = c("Placement of 'efficacy_understanding' in 'Internal Efficacy' question matrix",
                            "Placement of 'efficacy_talking' in 'Internal Efficacy' question matrix",
                            "Placement of 'efficacy_complexity' in 'Internal Efficacy' question matrix",
                            "Placement of 'ego_clim' in 'Political Positions' block",
                            "Placement of 'ego_tax' in 'Political Positions' block",
                            "Placement of 'ego_imm' in 'Political Positions' block"
                            )
)

kable(pol_random, format = "pipe", align = c("l", "l")) %>% 
  kable_classic(full_width = T, position = "center" ) 
```

## Racism, Sexism

### Descriptive Overview
```{r, echo=F}
# Selecting relevant variables
racesex <- wave1 %>% 
  dplyr::select(starts_with("prejudice_"), starts_with("racis"), starts_with("sexis"))

# Printing data description
table <- summarytools::dfSummary(racesex)
view(table, method = 'render')
```

### Randomization Variables

```{r, echo = F, warning = F, include = T}
racsex_random <- data.frame(Variables = c("prejudice_type", "io_racism_open_intelligence", "io_racism_open_better", "io_racism_open_industrious", "io_racism_meaning", "io_racism_reaction", "io_racism_society", "io_racism_words", "io_sexism_meaning", "io_sexism_reaction", "io_sexism_society", "io_sexism_words", "io_prejudice_meaning", "io_prejudice_reaction", "io_prejudice_society", "io_prejudice_words"),
                            Meaning = c("Randomized Prejudice Type",
                                        "Placement of 'racism_open_intelligence' in 'Open Racism' question matrix",
                                        "Placement of 'racism_open_better' in 'Open Racism' question matrix",
                                        "Placement of 'racism_open_industrious' in 'Open Racism' question matrix",
                                        "Placement of 'racism_meaning' in 'Racism' question matrix",
                                        "Placement of 'racism_reaction' in 'Racism' question matrix",
                                        "Placement of 'racism_society' in 'Racism' question matrix",
                                        "Placement of 'racism_words' in 'Racism' question matrix",
                                        "Placement of 'sexism_meaning' in 'Sexism' question matrix",
                                        "Placement of 'sexism_reaction' in 'Sexism' question matrix",
                                        "Placement of 'sexism_society' in 'Sexism' question matrix",
                                        "Placement of 'sexism_words' in 'Sexism' question matrix",
                                        "Variable displaying either sexism or racism items' order depending on prejudice type",
                                        "Variable displaying either sexism or racism items' order depending on prejudice type",
                                        "Variable displaying either sexism or racism items' order depending on prejudice type",
                                        "Variable displaying either sexism or racism items' order depending on prejudice type"                                        )
)

kable(racsex_random, format = "pipe", align = c("l", "l")) %>% 
  kable_classic(full_width = T, position = "center" ) 
```



## Populism, Authoritarianism, Pluralism

### Descriptive Overview

```{r, echo=F}
# Selecting relevant variables
popautplu <- wave1 %>% 
  dplyr::select(starts_with("pop"),starts_with("aut"),starts_with("plu") )

# Printing data description
table <- summarytools::dfSummary(popautplu)
view(table, method = 'render')
```
### Randomization Variables

```{r, echo = F, warning = F, include = T}
popautplu_random <- data.frame(Variables = c("io_pop_peoplepower", "io_pop_elitediff", "io_pop_goodbad", "io_pop_homogen", "io_attentioncheck", "io_aut_right_deviant", "io_aut_left_deviant", "io_aut_right_sub", "io_aut_left_sub", "io_plu_compromise", "io_plu_dispute", "io_plu_parties", " ", "qo_pop", "qo_aut", "qo_plu"),
                               Meaning = c("Placement of 'pop_peoplepower' in 'Populism' question matrix",
                                           "Placement of 'pop_elitediff' in 'Populism' question matrix",
                                           "Placement of 'pop_goodbad' in 'Populism' question matrix",
                                           "Placement of 'pop_homogen' in 'Populism' question matrix",
                                           "Placement of 'attentioncheck' in 'Populism' question matrix",
                                           "Placement of 'aut_right_deviant' in 'Authoritarianism' question matrix",
                                           "Placement of 'aut_left_deviant' in 'Authoritarianism' question matrix",
                                           "Placement of 'aut_right_sub' in 'Authoritarianism' question matrix",
                                           "Placement of 'aut_left_sub' in 'Authoritarianism' question matrix",
                                           "Placement of 'plu_compromise' in 'Pluralism' question matrix",
                                           "Placement of 'plu_dispute' in 'Pluralism' question matrix",
                                           "Placement of 'plu_parties' in 'Pluralism' question matrix",
                                           " ",
                                           "Placement of 'Populism' question matrix in 'Pop-Aut-Plu' block",
                                           "Placement of 'Authoritarianism' question matrix in 'Pop-Aut-Plu' block",
                                           "Placement of 'Pluralism' question matrix in 'Pop-Aut-Plu' block")
                               )

kable(popautplu_random, format = "pipe", align = c("l", "l")) %>% 
  kable_classic(full_width = T, position = "center" ) 

```

## Vote Choice, Partisanship

### Descriptive Overview

```{r, echo=F}
# Selecting relevant variables
partisan <- wave1 %>% 
  dplyr::select(starts_with("scalo"), starts_with("vote"), 
                starts_with("pid"), starts_with("nid"),
                starts_with("aff"))

# Printing data description
table <- summarytools::dfSummary(partisan, graph.magnif = 0.9) # Shrink graphs

view(table, method = 'render')
```
### Randomization Variables

```{r, echo = F, warning = F, include = T}
vote_random <- data.frame(Variables = c(" ", "io_vote_left", "io_vote_greens", "io_vote_spd", "io_vote_union", "io_vote_fdp", "io_vote_afd", " ", "io_scalo_left", "io_scalo_greens", "io_scalo_spd", "io_scalo_cdu", "io_scalo_csu", "io_scalo_fdp", "io_scalo_afd", "io_scalo_other", " ", "io_pid_left", "io_pid_greens", "io_pid_spd", "io_pid_cdu", "io_pid_csu", "io_pid_fdp", "io_pid_afd", "io_nid_left", "io_nid_greens", "io_nid_spd", "io_nid_cdu", "io_nid_csu", "io_nid_fdp", "io_nid_afd", " ", "io_aff_pos_criticism", "io_aff_pos_positive", "io_aff_pos_similar", "io_aff_neg_criticism", "io_aff_neg_different", "io_aff_neg_anti","io_aff_neg_damaging","io_aff_neg_democracy", " ", "qo_aff_pos", "qo_aff_neg", " ", "io_affass_pos_intelligent", "io_affass_pos_sympathetic", "io_affass_pos_tolerant", "io_affass_pos_informed", "io_affass_pos_honest", "io_affass_pos_good", "io_affass_pos_selfless", "io_affass_neg_intelligent", "io_affass_neg_sympathetic", "io_affass_neg_tolerant", "io_affass_neg_informed", "io_affass_neg_honest", "io_affass_neg_good", "io_affass_neg_selfless", " ", "qo_affass_pos", "qo_affass_neg" ),
                          Meaning = c("VOTE INTENTION",
              "Placement of Party 'Left' in 'Vote Intention' answering matrix",
              "Placement of Party 'Greens' in 'Vote Intention' answering matrix",
              "Placement of Party 'SPD' in 'Vote Intention' answering matrix",
              "Placement of Party 'Union' in 'Vote Intention' answering matrix",
              "Placement of Party 'FDP' in 'Vote Intention' answering matrix",
              "Placement of Party 'AfD' in 'Vote Intention' answering matrix",
              "SCALOMETER RATINGS",
              "Placement of Party 'Left' in 'Scalometer' question matrix",
              "Placement of Party 'Greens' in 'Scalometer' question matrix",
              "Placement of Party 'SPD' in 'Scalometer' question matrix",
              "Placement of Party 'CDU' in 'Scalometer' question matrix",
              "Placement of Party 'CSU' in 'Scalometer' question matrix",
              "Placement of Party 'FDP' in 'Scalometer' question matrix",
              "Placement of Party 'AfD' in 'Scalometer' question matrix",
              "Placement of Party 'Other' in 'Scalometer' question matrix (If vote choice was 'Other')",
              "POSITIVE & NEGATIVE PARTISAN IDs",
              "Placement of Party 'Left' in 'Positive Partisanship' answering matrix",
              "Placement of Party 'Greens' in 'Positive Partisanship' answering matrix",
              "Placement of Party 'SPD' in 'Positive Partisanship' answering matrix",
              "Placement of Party 'CDU' in 'Positive Partisanship' answering matrix",
              "Placement of Party 'CSU' in 'Positive Partisanship' answering matrix",
              "Placement of Party 'FDP' in 'Positive Partisanship' answering matrix",
              "Placement of Party 'AfD' in 'Positive Partisanship' answering matrix",
              "Placement of Party 'Left' in 'Negative Partisanship' answering matrix",
              "Placement of Party 'Greens' in 'Negative Partisanship' answering matrix",
              "Placement of Party 'SPD' in 'Negative Partisanship' answering matrix",
              "Placement of Party 'CDU' in 'Negative Partisanship' answering matrix",
              "Placement of Party 'CSU' in 'Negative Partisanship' answering matrix",
              "Placement of Party 'FDP' in 'Negative Partisanship' answering matrix",
              "Placement of Party 'AfD' in 'Negative Partisanship' answering matrix",
              "AFFECTIVE POLARIZATION SCALES",
              "Placement of 'aff_pos_criticism' in 'Positive Affective Partisanship' question matrix",
              "Placement of 'aff_pos_positive' in 'Positive Affective Partisanship' question matrix",
              "Placement of 'aff_pos_similar' in 'Positive Affective Partisanship' question matrix",
              "Placement of 'aff_neg_criticism' in 'Negative Affective Partisanship' question matrix",
              "Placement of 'aff_neg_different' in 'Negative Affective Partisanship' question matrix",
              "Placement of 'aff_neg_anti' in 'Negative Affective Partisanship' question matrix",
              "Placement of 'aff_neg_damaging' in 'Negative Affective Partisanship' question matrix",
              "Placement of 'aff_neg_democracy' in 'Negative Affective Partisanship' question matrix",
              " ",
              "Placement of 'Positive Affective Partisanship' question matrix in 'Affective Partisanship' block",
              "Placement of 'Negative Affective Partisanship' question matrix in 'Affective Partisanship' block",
              "AFFECTIVE ASSOCIATIONS",
              "Placement of 'affass_pos_intelligent' in 'Positive Affective Associations' question matrix",
              "Placement of 'affass_pos_sympathetic' in 'Positive Affective Associations' question matrix",
              "Placement of 'affass_pos_tolerant' in 'Positive Affective Associations' question matrix",
              "Placement of 'affass_pos_informed' in 'Positive Affective Associations' question matrix",
              "Placement of 'affass_pos_honest' in 'Positive Affective Associations' question matrix",
              "Placement of 'affass_pos_good' in 'Positive Affective Associations' question matrix",
              "Placement of 'affass_pos_selfless' in 'Positive Affective Associations' question matrix",
              "Placement of 'affass_neg_intelligent' in 'Negative Affective Associations' question matrix",
              "Placement of 'affass_neg_sympathetic' in 'Negative Affective Associations' question matrix",
              "Placement of 'affass_neg_tolerant' in 'Negative Affective Associations' question matrix",
              "Placement of 'affass_neg_informed' in 'Negative Affective Associations' question matrix",
              "Placement of 'affass_neg_honest' in 'Negative Affective Associations' question matrix",
              "Placement of 'affass_neg_good' in 'Negative Affective Associations' question matrix",
              "Placement of 'affass_neg_selfless' in 'Negative Affective Associations' question matrix",
              " ",
              "Placement of 'Positive Affective Associations' question matrix in 'Affective Associations' block",
              "Placement of 'Negative Affective Associations' question matrix in 'Affective Associations' block"
              )
)


kable(vote_random, format = "pipe", align = c("l", "l")) %>% 
  kable_classic(full_width = T, position = "center" ) 
```

## Anchoring Vignettes

### Descriptive Overview
```{r, echo=F}
# Selecting relevant variables
anchor <- wave1 %>% 
  dplyr::select(starts_with("anchor"))

# Printing data description
table <- summarytools::dfSummary(anchor)
view(table, method = 'render')
```
### Randomization Variables

```{r, echo = F, warning = F, include = T}
anchor_random <- data.frame(Variables = c("io_anchor1", "io_anchor2", "io_anchor3", "io_anchor4", "io_anchor5", "io_anchor6"),
                            Meaning = c("Placement of 'anchor1' in 'Anchoring' block",
                                       "Placement of 'anchor2' in 'Anchoring' block",
                                       "Placement of 'anchor3' in 'Anchoring' block",
                                       "Placement of 'anchor4' in 'Anchoring' block",
                                       "Placement of 'anchor5' in 'Anchoring' block",
                                       "Placement of 'anchor6' in 'Anchoring' block")
                            )


kable(anchor_random, format = "pipe", align = c("l", "l")) %>% 
  kable_classic(full_width = T, position = "center" ) 
```

## Online Participation

### Descriptive Overview

```{r, echo=F}
# Selecting relevant variables
onlinepart <- wave1 %>% 
  dplyr::select(starts_with("online"))

# Printing data description
table <- summarytools::dfSummary(onlinepart)
view(table, method = 'render')
```
### Randomization Variables
```{r, echo = F, warning = F, include = T}

participation_random <- data.frame(Variables = c("io_online_post", "io_online_share", "io_online_comment"),
                                   Meaning = c("Placement of 'online_post' in 'Online Participation' question matrix",
                                               "Placement of 'online_share' in 'Online Participation' question matrix",
                                               "Placement of 'online_comment' in 'Online Participation' question matrix")
                                   )

kable(participation_random, format = "pipe", align = c("l", "l")) %>% 
  kable_classic(full_width = T, position = "center" ) 
```

## Statement Ratings

### Descriptive Overview
```{r, echo=F}
# Selecting relevant variables
statement <- wave1 %>% 
  dplyr::select(starts_with("statement"))

# Printing data description
table <- summarytools::dfSummary(statement)
view(table, method = 'render')
```

### Randomization Variables

```{r, echo = F, warning = F, include = T}
statement_random <- data.frame(Variables = c(" ", "io_statement_racists", "io_statement_racism", "io_statement_borders", "io_statement_immigration", "io_statement_sexequal", "io_statement_gender", "io_statement_climatedemo", "io_statement_climateacti", " ", "qo_statement_true", "qo_statement_danger", "qo_statement_insult"),
                               Meaning = c("STATEMENT SELECTION",
                                           "Placement of 'statement_racists' evaluations in 'Statement Ratings' block",
                                           "Placement of 'statement_racism' evaluations in 'Statement Ratings' block",
                                           "Placement of 'statement_borders' evaluations in 'Statement Ratings' block",
                                           "Placement of 'statement_immigration' evaluations in 'Statement Ratings' block",
                                           "Placement of 'statement_sexequal' evaluations in 'Statement Ratings' block",
                                           "Placement of 'statement_gender' evaluations in 'Statement Ratings' block",
                                           "Placement of 'statement_climatedemo' evaluations in 'Statement Ratings' block",
                                           "Placement of 'statement_climateacti' evaluations in 'Statement Ratings' block",
                                           "EVALUATING ORDER",
                                           "At which position 'true' question was placed throughout each statement's evaluation",
                                           "At which position 'danger' question was placed throughout each statement's evaluation",
                                           "At which position 'insult' question was placed throughout each statement's evaluation")
                               )

kable(statement_random, format = "pipe", align = c("l", "l")) %>% 
  kable_classic(full_width = T, position = "center" ) 
```

## Int. Humility & Grandstanding

### Descriptive Overview
```{r, echo = F}
# Selecting relevant variables
hummgs <- wave1 %>% 
  dplyr::select(starts_with("int"), starts_with("mgs") ) %>% 
  dplyr:: select(-mgs_type, -mgs_inthum_others)

# Printing data description
table <- summarytools::dfSummary(hummgs)
view(table, method = 'render')
```
### Randomization Variables

```{r, echo = F, warning = F, include = T}
hummgs_random <- data.frame(Variables = c(" ", "mgs_type", "mgs_inthum_others", " ",  "io_inthum_oth_winning", "io_inthum_oth_defensive", "io_inthum_oth_ridicule", "io_inthum_oth_open",  "io_inthum_self_attack", "io_inthum_self_change", "io_inthum_self_respect", "io_inthum_self_better", "io_mgs_self_convince", "io_mgs_self_history", "io_mgs_self_sharing", "io_mgs_self_shaming", "io_mgs_self_better", "io_mgs_oth_convince", "io_mgs_oth_history", "io_mgs_oth_sharing", "io_mgs_oth_shaming", "io_mgs_oth_better"," ",  "qo_inthum_self", "qo_inthum_oth","qo_mgs_self", "qo_mgs_oth"),
                            Meaning = c("CONTENTUAL RANDOMIZATIONS",
                                        "Whether 'Moral Grandstanding' was asked about 'moral' or 'political' views",
                                        "What reference group respondents' should consider when thinking about the 'others' ",
                                        "ORDER RANDOMIZATIONS",
                                        "Placement of 'inthum_oth_winning' in 'Int. Humility: Others' question matrix",
                                        "Placement of 'inthum_oth_defensive' in 'Int. Humility: Others' question matrix",
                                        "Placement of 'inthum_oth_ridicule' in 'Int. Humility: Others' question matrix",
                                        "Placement of 'inthum_oth_open' in 'Int. Humility: Others' question matrix",
                                        "Placement of 'inthum_self_attack' in 'Int. Humility: Self' question matrix",
                                        "Placement of 'inthum_self_change' in 'Int. Humility: Self' question matrix",
                                        "Placement of 'inthum_self_respect' in 'Int. Humility: Self' question matrix",
                                        "Placement of 'inthum_self_better' in 'Int. Humility: Self' question matrix",
                                        "Placement of 'mgs_self_convince' in 'Moral Grandstanding: Self' question matrix",
                                        "Placement of 'mgs_self_history' in 'Moral Grandstanding: Self' question matrix",
                                        "Placement of 'mgs_self_sharing' in 'Moral Grandstanding: Self' question matrix",
                                        "Placement of 'mgs_self_shaming' in 'Moral Grandstanding: Self' question matrix",
                                        "Placement of 'mgs_self_better' in 'Moral Grandstanding: Self' question matrix",
                                        "Placement of 'mgs_oth_convince' in 'Moral Grandstanding: Others' question matrix",
                                        "Placement of 'mgs_oth_history' in 'Moral Grandstanding: Others' question matrix",
                                        "Placement of 'mgs_oth_sharing' in 'Moral Grandstanding: Others' question matrix",
                                        "Placement of 'mgs_oth_shaming' in 'Moral Grandstanding: Others' question matrix",
                                        "Placement of 'mgs_oth_better' in 'Moral Grandstanding: Others' question matrix",
                                        "QUESTION RANDOMIZATIONS",
                                        "Placement of 'Int. Humility: Self' in 'Intellectual Humility' block",
                                        "Placement of 'Int. Humility: Others' in 'Intellectual Humility' block",
                                        "Placement of 'Moral Grandstanding: Self' in 'Moral Grandstanding' block",
                                        "Placement of 'Moral Grandstanding: Others' in 'Moral Grandstanding' block")
                            )

kable(hummgs_random, format = "pipe", align = c("l", "l")) %>% 
  kable_classic(full_width = T, position = "center" ) 
```


#### Descriptive Overview split by 'Moral' vs. 'Political' Views

```{r, echo = F}
# Printing data by issue randomization
hummgs <- wave1 %>% 
  dplyr::select(starts_with("mgs") ) %>% 
  dplyr:: select(-mgs_inthum_others)

hummgs_byissue <- by(data = hummgs,
                  INDICES = hummgs$mgs_type, 
                  FUN = dfSummary, 
                  transpose = TRUE
                  )

view(hummgs_byissue, method = "render")
```

#### Descriptive Overview split by "Others"

```{r, echo = F}
# Printing data by issue randomization
hummgs2 <- wave1 %>% 
  dplyr::select(starts_with("inthum_oth"), starts_with("mgs_oth"), mgs_inthum_others )

hummgs2_byissue <- by(data = hummgs2,
                  INDICES = hummgs2$mgs_inthum_others, 
                  FUN = dfSummary, 
                  transpose = TRUE
                  )

view(hummgs2_byissue, method = "render")
```

## Grievances

### Descriptive Overview
```{r, echo=F}
# Selecting relevant variables
grievance <- wave1 %>% 
  dplyr::select(class, fairness, trust, starts_with("depri"), lifesat)

# Printing data description
table <- summarytools::dfSummary(grievance)
view(table, method = 'render')
```
### Randomization Variables

```{r, echo = F, warning = F, include = T}
grievance_random <- data.frame(Variables = c("io_depri_econ", "io_depri_recog", "io_depri_infra"),
                               Meaning = c("Placement of 'depri_econ' in 'Deprivation' question matrix",
                                           "Placement of 'depri_recop' in 'Deprivation' question matrix",
                                           "Placement of 'depri_infra' in 'Deprivation' question matrix")
                               )

kable(grievance_random, format = "pipe", align = c("l", "l")) %>% 
  kable_classic(full_width = T, position = "center" ) 
```

## List Experiment: Direct

### Descriptive Overview
```{r, echo=F}
# Selecting relevant variables
listexdirect <- wave1 %>% 
  dplyr::select(starts_with("listex_")) %>% 
  dplyr::select(-listex_order)

# Printing data description
table <- summarytools::dfSummary(listexdirect)
view(table, method = 'render')
```
### Randomization Variables

*Note: Which of the four sensitive items (for wording, see direct item questions) respondents received was based on their SFS Issue randomization, with the Baseline group receiving the equality item, the Government group receiving the liberty item, and the Immigration and Climate groups receiving the respectively fitting items.*

```{r, echo = F, warning = F, include = T}
listex_random <- data.frame(Variables = c(" ","io_listex_direct_equality", "io_listex_direct_immigration", "io_listex_direct_liberty", "io_listex_direct_climate", " ", "io_listex_clist1_income", "io_listex_clist1_eu", "io_listex_clist1_covid", "io_listex_clist1_sens",  "io_listex_clist2_referendum", "io_listex_clist2_rent",  "io_listex_clist2_economy", "io_listex_clist2_sens", "io_listex_sens", " ", "qo_listex_clist1", "qo_listex_clist2", "listex_order"),
                            Meaning = c("DIRECT QUESTIONING",
                                        "Placement of 'listex_direct_equality' in 'Direct List Experiment' question matrix",
                                        "Placement of 'listex_direct_immigration' in 'Direct List Experiment' question matrix",
                                        "Placement of 'listex_direct_liberty' in 'Direct List Experiment' question matrix",
                                        "Placement of 'listex_direct_climate' in 'Direct List Experiment' question matrix",
                                        "EXPERIMENT COMPOSITION",
                                        "Placement of 'income' statement in 'Control Set 1' ",
                                        "Placement of 'eu' statement in 'Control Set 1' ",
                                        "Placement of 'covid' statement in 'Control Set 1' ",
                                        "Placement of randomized sensitive statement in 'Control Set 1' (if applicable) ",
                                        "Placement of 'referendum'statement in 'Control Set 2' ",
                                        "Placement of 'rent' statement in 'Control Set 2' ",
                                        "Placement of 'economy' statement in 'Control Set 2' ",
                                        "Placement of randomized sensitive statement in 'Control Set 2' (if applicable) ",
                                        "Placement of randomized sensitive statement in either control set",
                                        " ",
                                        "Whether 'Control Set 1' was presented in first or second task",
                                        "Whether 'Control Set 2' was presented in first or second task",
                                        "Whether the sensitive item was added in first or second task")
)

kable(listex_random, format = "pipe", align = c("l", "l")) %>% 
  kable_classic(full_width = T, position = "center" ) 
```

## Living History

The living history items records respondent's home cities throughout their life in Germany. As this is sensitive information, access to it can only me granted after in-depth contact (via Menzner@em.uni-frankfurt.de). Recoded variables that show anonymized aggregate information might be available later. 

## GDR vs BRD

### Descriptive Overview
```{r, echo=F}
# Selecting relevant variablesgdr <- wave1 %>% 
gdr <- wave1 %>% 
  dplyr::select(starts_with("lived"), lifesat_gdr, lifesat_brd, starts_with("gdr"))

# Printing data description
table <- summarytools::dfSummary(gdr)
view(table, method = 'render')
```

### Randomization Variables

```{r, echo = F, warning = F, include = T}

gdr_random <- data.frame(Variables = c("io_gdr_orga_fdgb", "io_gdr_orga_fdj", "io_gdr_orga_dfd", "io_gdr_orga_kb", "io_gdr_orga_dsf", "io_gdr_orga_other", "io_gdr_orga_none", "qo_gdr_orga", "qo_gdr_oppo"),
                         Meaning = c("Placement of 'gdr_orga_fdgb' in 'GDR Organisations' question matrix",
                                     "Placement of 'gdr_orga_fdj' in 'GDR Organisations' question matrix",
                                     "Placement of 'gdr_orga_dfd' in 'GDR Organisations' question matrix",
                                     "Placement of 'gdr_orga_kb' in 'GDR Organisations' question matrix",
                                     "Placement of 'gdr_orga_dsf' in 'GDR Organisations' question matrix",
                                     "Placement of 'gdr_orga_other' in 'GDR Organisations' question matrix",
                                     "Placement of 'gdr_orga_none' in 'GDR Organisations' question matrix",
                                     "Whether 'GDR Organisations' question came first or second (vs. Opposition)",
                                     "Whether 'GDR Opposition' question came first or second (vs. Organisations)")
                         )


kable(gdr_random, format = "pipe", align = c("l", "l")) %>% 
  kable_classic(full_width = T, position = "center" ) 
```


## Socio-Demographics
```{r, echo=F}
# Selecting relevant variables
sd <- wave1 %>% 
  dplyr::select(female, male, age, east,education, education_cat, education_abi, starts_with("nationality"), starts_with("born"), starts_with("parent"), migration_background, starts_with("job"))

# Printing data description
table <- summarytools::dfSummary(sd)
view(table, method = 'render')
```

SFS Wave 1 - Codebook

Jan Menzner

2022-12-14

Meta-Data

Information / Read Me

Information about randomized display orders

General Items

SFS Variables

Descriptive Overview

Randomization Variables

Descriptive Overview split by SFS Issues

Sanctions

(Self-)Censorship

Descriptive Overview

Randomization Variables

De-Platforming

Descriptive Overview

Randomization Variables

Descriptive Overview split by De-Platforming Target

Conjoint Experiment: Allowed to say

Variables

Conservatism, Socialism, Liberalism

Descriptive Overview

Randomization Variables

Political Variables

Descriptive Overview

Randomization Variables

Racism, Sexism

Descriptive Overview

Randomization Variables

Populism, Authoritarianism, Pluralism

Descriptive Overview

Randomization Variables

Vote Choice, Partisanship

Descriptive Overview

Randomization Variables

Anchoring Vignettes

Descriptive Overview

Randomization Variables

Online Participation

Descriptive Overview

Randomization Variables

Statement Ratings

Descriptive Overview

Randomization Variables

Int. Humility & Grandstanding

Descriptive Overview

Randomization Variables

Descriptive Overview split by ‘Moral’ vs. ‘Political’ Views

Descriptive Overview split by “Others”

Grievances

Descriptive Overview

Randomization Variables

List Experiment: Direct

Descriptive Overview

Randomization Variables

Living History

GDR vs BRD

Descriptive Overview

Randomization Variables

Socio-Demographics