Replication Data for: Non-verbal cues as a test of gender and race bias in politics: the Italian case (doi:10.7910/DVN/ZMZDHG)

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Part 2: Study Description
Part 3: Data Files Description
Part 4: Variable Description
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Replication Data for: Non-verbal cues as a test of gender and race bias in politics: the Italian case

doi:10.7910/DVN/ZMZDHG

Harvard Dataverse

2015-07-10

1

Iyengar, Shanto; Barisione, Mauro, 2015, "Replication Data for: Non-verbal cues as a test of gender and race bias in politics: the Italian case", https://doi.org/10.7910/DVN/ZMZDHG, Harvard Dataverse, V1, UNF:6:Dw0ylRHdLRVUzMCKykiXDg== [fileUNF]

Replication Data for: Non-verbal cues as a test of gender and race bias in politics: the Italian case

doi:10.7910/DVN/ZMZDHG

Iyengar, Shanto (Department of Communication and Political Science, Stanford University)

Barisione, Mauro (Department of Social and Political Sciences, Università degli Studi di Milano)

Harvard Dataverse

Barisione, Mauro

Franchino, Fabio

2015-07-10

https://doi.org/10.7910/DVN/ZMZDHG

Social Sciences, survey experiment; candidate images; public opinion; social prejudice; interaction models

Gender and race biases persist in western democracies, with male and white candidates still being the norm. Voters may be more inclined to express sexist and racist attitudes in countries with a traditionally male-dominated political system and a majority-white population. As sexism and racism are notoriously difficult to document, and because many people are unaware of their biases toward social groups, we bypass conventional survey measurement and observe voters’ willingness to support candidates whose physical features have been manipulated to make them appear more prototypically feminine or non-white. We implemented this approach in the context of the 2013 Italian election, by presenting a national sample of Italian voters with pictures of male and female parliamentary candidates – both unknown and well known. Overall, we found no main effects of gender or race bias in political judgment. For Italian voters, party cues are by far the most powerful indicators of out-group status, and therefore the strongest predictors of candidate perception and support. This result may be of particular interest to other political contexts characterized by strong partisan polarization.

<a href="http://creativecommons.org/publicdomain/zero/1.0">CC0 1.0</a>

Iyengar, Shanto, and Mauro Barisione. “Non-Verbal Cues as a Test of Gender and Race Bias in Politics: The Italian Case.” Italian Political Science Review / Rivista Italiana Di Scienza Politica 45, no. 02 (July 2015): 131–57.

10.1017/ipo.2015.9

Iyengar, Shanto, and Mauro Barisione. “Non-Verbal Cues as a Test of Gender and Race Bias in Politics: The Italian Case.” Italian Political Science Review / Rivista Italiana Di Scienza Politica 45, no. 02 (July 2015): 131–57.

• Number of cases: 4216

• No. of variables per record: 17

• Type of File: text/tab-separated-values

UNF:6:NYtiAJX7BkAMBvupqB8nNQ==

• Number of cases: 1721

• No. of variables per record: 9

• Type of File: text/tab-separated-values

UNF:6:MtT1OAAN/6Ewdavn9demOA==

• Number of cases: 2495

• No. of variables per record: 5

• Type of File: text/tab-separated-values

UNF:6:QePTO0Owh5gCVbmRun2QVw==

• id
• support - Candidate Support Index
• candidate - Candidate Condition
• leader - Leader Condition
• gender - Gender (Voter)
• cgender - Gender (Candidate)
• edu - Education (Voter)
• age - Age (Voter)
• lrs3 - Left-Right Ideology (Voter)
• intpol - Political Interest
• vp2 - Party Vote
• sextypcand - Sex Typicality
• racetypcand - Race Typicality
• inoutcand - Partisan Similarity
• sextyplead
• racetyplead
• inoutlead - Party similarity
• couple1
• couple2
• couple3
• couple4
• couple5
• couple6
• couple7
• couple8
• support
• leader
• support
• berlusconi
• renzi
• vendola

f2692954 Location:

Summary Statistics: Min. 1.0; StDev 2527.924612195473; Mean 4218.8097722960165; Valid 4216.0; Max. 8713.0;

Variable Format: numeric

Notes: UNF:6:j2ys/zRWxtOoVXhtm2ubog==

f2692954 Location:

Summary Statistics: Max. 1.0; Min. 0.0; Valid 4216.0; Mean 0.43031309388685673; StDev 0.2933997313074205

Variable Format: numeric

Notes: UNF:6:w6lTFIdiOZC/WJIvycPluA==

f2692954 Location:

Summary Statistics: Min. 1.0; Mean 8.760023242300988; Valid 1721.0; StDev 4.607999212635101; Max. 16.0

Variable Format: numeric

Notes: UNF:6:ZFYDgwb/vj8vRf+nG2J4OQ==

f2692954 Location:

Summary Statistics: StDev 2.3094370302192107; Mean 4.501002004008017; Min. 1.0; Valid 2495.0; Max. 8.0

Variable Format: numeric

Notes: UNF:6:c6Z3Yo//WQxuS+Mhgks4zQ==

f2692954 Location:

Summary Statistics: Valid 4216.0; Min. 1.0; StDev 0.4999552607831119; Mean 1.4898007590132831; Max. 2.0;

Variable Format: numeric

Notes: UNF:6:SnRJ7/4m+vcsjuavDlBejw==

f2692954 Location:

Summary Statistics: Mean 1.4944799535153979; Max. 2.0; StDev 0.5001148470185387; Min. 1.0; Valid 1721.0;

Variable Format: numeric

Notes: UNF:6:tkt23RUe2MceTNF5lNxneA==

f2692954 Location:

Summary Statistics: StDev 0.6532217417110355; Valid 4213.0; Max. 3.0; Mean 2.2810348920009504; Min. 1.0

Variable Format: numeric

Notes: UNF:6:nUx1tbyrMdjjQVmYtMaWCA==

f2692954 Location:

Summary Statistics: Max. 89.0; Mean 47.031309297912735; StDev 16.026963247310672; Min. 18.0; Valid 4216.0

Variable Format: numeric

Notes: UNF:6:dYjaKdp49wpWqcqxFGM/1w==

f2692954 Location:

Summary Statistics: Max. 3.0; StDev 0.8110557659176274; Mean 1.976518026565465; Valid 4216.0; Min. 1.0

Variable Format: numeric

Notes: UNF:6:q5ZIQD21RUqlWNoJ4pLX1g==

f2692954 Location:

Summary Statistics: Mean 1.7435958254269455; Valid 4216.0; Max. 2.0; StDev 0.43669933338456934; Min. 1.0;

Variable Format: numeric

Notes: UNF:6:27ink23f8CundUURu/IOTA==

f2692954 Location:

Summary Statistics: Mean 1.4280798348245007; Valid 1453.0; Min. 1.0; Max. 2.0; StDev 0.49497081107359175

Variable Format: numeric

Notes: UNF:6:yI9Twu5d9e793V2+Q99jEQ==

f2692954 Location:

Summary Statistics: Max. 2.0; StDev 0.829874493319232; Mean 1.2742591516560138; Min. 0.0; Valid 1721.0;

Variable Format: numeric

Notes: UNF:6:BCuO/Umb+dSVgaU8yt4/TQ==

f2692954 Location:

Summary Statistics: Min. 0.0; Mean 1.2242882045322485; StDev 0.8294803476408634; Valid 1721.0; Max. 2.0;

Variable Format: numeric

Notes: UNF:6:mc1ApJlP4ApWu6oltmWljg==

f2692954 Location:

Summary Statistics: Mean 0.5052264808362369; Min. 0.0; Max. 1.0; Valid 574.0; StDev 0.5004087693081597

Variable Format: numeric

Notes: UNF:6:FbUsrmaVy+kMBvKxMXKeow==

f2692954 Location:

Summary Statistics: StDev 0.5001313516300113; Min. 1.0; Mean 1.5007915567282324; Max. 2.0; Valid 1895.0;

Variable Format: numeric

Notes: UNF:6:26sqG9laxQvkJqRVLpxJFw==

f2692954 Location:

Summary Statistics: StDev 0.46765538604221357; Valid 1859.0; Min. 1.0; Max. 2.0; Mean 1.3227541689080151

Variable Format: numeric

Notes: UNF:6:Evscmxw0Mwfd//WOkvaBHA==

f2692954 Location:

Summary Statistics: StDev 0.4981560063438552; Max. 1.0; Valid 879.0; Mean 0.546075085324232; Min. 0.0

Variable Format: numeric

Notes: UNF:6:Aos2Wy434tcix/VAEggrwA==

f2692950 Location:

Summary Statistics: Mean 1.4712041884816753; Min. 1.0; Valid 191.0; Max. 2.0; StDev 0.5004819941902814;

Variable Format: numeric

Notes: UNF:6:jlUM3pVnSMyi1RCmBn6ckw==

f2692950 Location:

Summary Statistics: Max. 4.0; Min. 3.0; Valid 196.0; StDev 0.4999999999999999; Mean 3.4642857142857144

Variable Format: numeric

Notes: UNF:6:a5Rk/FoEu1wuiB2YeYpeAQ==

f2692950 Location:

Summary Statistics: Valid 210.0; Mean 5.5; Min. 5.0; Max. 6.0; StDev 0.5011947448335864

Variable Format: numeric

Notes: UNF:6:vIToeJBlQdrd7xbw4Jei1Q==

f2692950 Location:

Summary Statistics: Valid 254.0; StDev 0.4979338593501383; Mean 7.55511811023622; Max. 8.0; Min. 7.0

Variable Format: numeric

Notes: UNF:6:53P4zb6HAbw8TwvIzZbO0Q==

f2692950 Location:

Summary Statistics: Valid 194.0; Max. 10.0; Mean 9.489690721649485; StDev 0.5011870956913795; Min. 9.0;

Variable Format: numeric

Notes: UNF:6:XrxwAERK7X5rn5ET0kXmAg==

f2692950 Location:

Summary Statistics: Min. 11.0; Mean 11.448275862068966; StDev 0.49854688127629204; Valid 203.0; Max. 12.0

Variable Format: numeric

Notes: UNF:6:baK09hyjpUvRd0vQFogTLA==

f2692950 Location:

Summary Statistics: Mean 13.515021459227468; Max. 14.0; Min. 13.0; Valid 233.0; StDev 0.5008502464460837

Variable Format: numeric

Notes: UNF:6:DHkb2IjbRE0wt3xPtjxZWA==

f2692950 Location:

Summary Statistics: Valid 240.0; Max. 16.0; Mean 15.533333333333333; Min. 15.0; StDev 0.4999302601293766;

Variable Format: numeric

Notes: UNF:6:Wl9J2wOi0QKcTS4mY4/y4Q==

f2692950 Location:

Summary Statistics: Mean 0.333798180386762; Min. 0.0; StDev 0.2630878616525538; Max. 1.0; Valid 1721.0

Variable Format: numeric

Notes: UNF:6:VdJHrXf/NqH4VDxgjctMog==

f2692952 Location:

Summary Statistics: Valid 2495.0; Min. 1.0; Max. 8.0; StDev 2.3094370302192107; Mean 4.501002004008017;

Variable Format: numeric

Notes: UNF:6:sxR0XwXjBLU8Adk3xlGbOw==

f2692952 Location:

Summary Statistics: Valid 2495.0; Max. 1.0; Mean 0.49688710836928796; Min. 0.0; StDev 0.29476992315323747

Variable Format: numeric

Notes: UNF:6:hpm03nLSTJ6b5WzVYIyPbw==

f2692952 Location:

Summary Statistics: Mean 1.498427672955975; Max. 2.0; Valid 636.0; StDev 0.5003910717447118; Min. 1.0

Variable Format: numeric

Notes: UNF:6:WkLY3YQJPVsAlh60TNhvZw==

f2692952 Location:

Summary Statistics: StDev 0.81528974901597; Min. 3.0; Max. 5.0; Valid 903.0; Mean 3.9778516057585827

Variable Format: numeric

Notes: UNF:6:lz5PMr7wNbZWBS0Ck32Rog==

f2692952 Location:

Summary Statistics: Min. 6.0; Max. 8.0; Valid 956.0; StDev 0.8102412185391292; Mean 6.9926778242677825

Variable Format: numeric

Notes: UNF:6:fAqpbttu0o+9FvSF/KDrAg==

Label:

italy2013_R_script.R

text/plain; charset=US-ASCII

Label:

italy2013_script.do

application/x-stata-syntax