levy_2022_perpetrator_candidates

11,925 rated or chosen profiles from 1,528 respondents, in up to 4 tasks of 2 profiles varying on 10 attributes.

About this table

DescriptionColombian online respondents (October 2019; 1,589 in the deposit, 1,528 who answered at least one task) chose in 4 tasks between two hypothetical candidates who were former combatants accused of violence against civilians (age, gender, education, recruitment, reputation, military success, crime, victims, involvement, attitude) and rated each 1-5 on likelihood of voting for them.
ReferenceLevy, G. (2022). Evaluations of violence at the polls: Civilian victimization and support for perpetrators after war. The Journal of Politics, 84(2), 783-797.
DOI10.1086/715248
LicenceCC0 1.0
Source datahttps://doi.org/10.7910/DVN/0Y1E2B

Notes

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

Size and shape

Respondents1,528
Rows (one per respondent, task and profile)11,925
Tasks per respondent (most)4
Profiles per task2
Attributes10
Tasks with no profile chosen0

Design

Topiccandidate choice
A profile representsperson
CountryCO
Language shownes
Language of stored levelses
Randomization restrictionsunknown
Task orderrecorded in the deposit
Profile positionrecorded in the deposit

Outcomes:

choice¿Si tuviera que elegir, por cuál de los dos candidatos votaría? [choice, forced]
rating¿En una escala del 1 a 5, donde 1 es "muy improbable" y 5 es "muy probable," ¿qué tan probable es que usted vote por el/la candidato/a A [B]? [rating, 1 (muy improbable) to 5 (muy probable)]

Columns

attr_ageattr_attitudeattr_crimeattr_crime_targetattr_educationattr_genderattr_involvementattr_military_successattr_recruitmentattr_reputationchoicecov_birth_yearcov_economiccov_educationcov_gendercov_ideologycov_incomecov_peace_vote_2016cov_urbanidprofileratingtask

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 neededBrowse on Redivisexplore and queryCroissant 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("levy_2022_perpetrator_candidates", source = "conj")
# Python
pip install irw

import irw
df = irw.fetch("levy_2022_perpetrator_candidates", source="conj")

How to cite

@article{Levy_2022, title={Evaluations of Violence at the Polls: Civilian Victimization and Support for Perpetrators after War}, volume={84}, ISSN={1468-2508}, url={http://dx.doi.org/10.1086/715248}, DOI={10.1086/715248}, number={2}, journal={The Journal of Politics}, publisher={University of Chicago Press}, author={Levy, Gabriella}, year={2022}, month=Apr, pages={783–797} }

Version and provenance

IRW versionv584
Redivis datasetirw_conjoint v4.2
Redivis dataset DOI10.57761/qkye-q530
Manifest pin for this IRW versionv4.2
Metadata sourceirw_meta v44.0