41,518 rated or chosen profiles from 4,334 respondents, in up to 5 tasks of 2 profiles varying on 7 attributes.

About this table

Description	US online respondents (Lucid/Qualtrics, October 2019; n = 4,334, 4,042 completing all pairs) read a hypothetical employment-discrimination case (type randomized across 5 arms) and compared 5 pairs of judges varying on 7 attributes (race, gender, sexual orientation, nominating party, age, law school, previous job); outcomes are which judge they trust more to hear the case fairly, plus 1-7 ideology and impartiality placements and 1-4 trust in the Supreme Court if the judge joined it.
Reference	Bracic, A., Israel-Trummel, M., Johnson, T., & Tipler, K. (2023). "Because he is gay": How race, gender, and sexuality shape perceptions of judicial fairness. The Journal of Politics, 85(4), 1167-1181.
DOI	10.1086/723996
Licence	CC0 1.0
Source data	https://doi.org/10.7910/DVN/WDQB4C

Notes

Conjoint table (irw_conjoint). choice = 'Which of these judges do you trust more to fairly hear this case on <type> discrimination?' (forced, no opt-out); rating_ideology 1-7 (Very liberal to Very conservative), rating_politically_motivated 1-7 (Impartial to Politically motivated), rating_court_trust 1-4 (Not at all to A great deal) for trusting the Supreme Court if the judge joined it. Levels drawn independently and uniformly; attribute order randomized per respondent (attrpos_); the case's discrimination type is a respondent-level arm (trial_discrim_type). 4,334 respondents answered at least one pair, 4,042 (the authors' sample) all five; tasks not reached are omitted.

These notes describe the source data, which the IRW reproduces as released. All notes are listed on the Data Notes page.

Design

Topic	crime justice policing
A profile represents	scenario
Country	US
Language shown	en
Language of stored levels	en
Task order	recorded in the deposit
Profile position	recorded in the deposit

Outcomes:

choice	Which of these judges do you trust more to fairly hear this case on ${e://Field/discrimdescrip} discrimination? [choice, forced]
rating_court_trust	Imagine one of these judges were nominated to the United States Supreme Court. If they joined the Court, how much would you trust the United States Supreme Court to operate in the best interest of the American people? [rating, 1 (Not at all) to 4 (A great deal)]
rating_ideology	Thinking about politics these days, how would you describe the political viewpoint of the following judges? [rating, 1 (Very liberal) to 7 (Very conservative)]
rating_politically_motivated	Judges are supposed to provide an impartial hearing, but sometimes people think judges are politically motivated. Where would you place these two judges on a scale from impartial to politically motivated? [rating, 1 (Impartial) to 7 (Politically motivated)]

Columns

attr_ageattr_genderattr_law_school_rankingattr_nominated_byattr_previous_jobattr_raceattr_sexual_orientationattrpos_ageattrpos_genderattrpos_law_school_rankingattrpos_nominated_byattrpos_previous_jobattrpos_raceattrpos_sexual_orientationchoicecov_agecov_age_groupcov_duration_seccov_educationcov_gendercov_gender_questioncov_ideologycov_incomecov_lgbcov_party_scalecov_racecov_religious_attendancecov_scotus_term_knowledgecov_transgendercov_trump_approvalidprofilerating_court_trustrating_ideologyrating_politically_motivatedtasktrial_case_reasontrial_discrim_type

The layout (one row per respondent, task and profile; choice/rating outcomes; attr_ columns holding each attribute level as displayed) is defined in the IRW conjoint standard. What the outcomes asked is under Design above.

Get the data

Download CSVno account needed Browse on Redivisexplore and query Croissant metadataHugging Face, Kaggle, OpenML

Or load it directly in R or Python (both need a free Redivis account; the first call opens a browser to sign in):

# R
install.packages("remotes")
remotes::install_github("itemresponsewarehouse/Rpkg")
library(irw)
df <- irw_fetch("bracic_2023_judge_fairness", source = "conj")

# Python
pip install irw

import irw
df = irw.fetch("bracic_2023_judge_fairness", source="conj")

How to cite

@article{Bracic_2023, title={“Because He Is Gay”: How Race, Gender, and Sexuality Shape Perceptions of Judicial Fairness}, volume={85}, ISSN={1468-2508}, url={http://dx.doi.org/10.1086/723996}, DOI={10.1086/723996}, number={4}, journal={The Journal of Politics}, publisher={University of Chicago Press}, author={Bracic, Ana and Israel-Trummel, Mackenzie and Johnson, Tyler and Tipler, Kathleen}, year={2023}, month=Oct, pages={1167–1181} }

Respondents	4,334
Rows (one per respondent, task and profile)	41,518
Tasks per respondent (most)	5
Profiles per task	2
Attributes	7
Tasks with no profile chosen	0

IRW version	v584
Redivis dataset	irw_conjoint v4.2
Redivis dataset DOI	10.57761/qkye-q530
Manifest pin for this IRW version	v4.2
Metadata source	irw_meta v44.0

bracic_2023_judge_fairness