islam_2026_ethical_distance_us

43,344 rated or chosen profiles from 3,612 respondents, in up to 6 tasks of 2 profiles varying on 7 attributes.

One of 2 tables from the same source; this one is the us table. The others are listed under Related tables.

About this table

Description3,612 US respondents each completed six paired candidate conjoints, one per ethical issue (death penalty, lying, bribery, cheating on a spouse, homosexuality, suicide), with candidates varying in age, gender, party, race, profession, government experience and their stated acceptability of that issue; they chose one candidate and rated both 0-100.
ReferenceIslam, M. M., & Loewen, P. (2026). Ethical distance and electoral accountability: Voters punish politicians whose ethical views diverge from societal consensus.
LicenceCC0 1.0
Source datahttps://doi.org/10.7910/DVN/O2RSXG

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

Respondents3,612
Rows (one per respondent, task and profile)43,344
Tasks per respondent (most)6
Profiles per task2
Attributes7
Tasks with no profile chosen0

Design

Topiccandidate choice
A profile representsperson
CountryUS
Language shownen
Language of stored levelsen
Randomization restrictionsunknown
Task orderunknown
Profile positionrecorded in the deposit

Outcomes:

choiceIf you had to choose between them, which of these two candidates would you vote for? [choice, forced]
ratingunknown [rating, 0 (unknown) to 100 (unknown)]

Columns

attr_ageattr_ethical_positionattr_experienceattr_genderattr_partyattr_professionattr_racechoicecov_accept_briberycov_accept_cheatingcov_accept_death_penaltycov_accept_homosexualitycov_accept_lyingcov_accept_suicidecov_agecov_birth_yearcov_census_regioncov_educ_bachelorscov_gendercov_lr_scalecov_racecov_rstatuscov_survey_weightidprofileratingtasktrial_issue

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("islam_2026_ethical_distance_us", source = "conj")
# Python
pip install irw

import irw
df = irw.fetch("islam_2026_ethical_distance_us", source="conj")

How to cite

@misc{https://doi.org/10.7910/dvn/o2rsxg,
  doi = {10.7910/DVN/O2RSXG},
  url = {https://dataverse.harvard.edu/citation?persistentId=doi:10.7910/DVN/O2RSXG},
  author = {Islam, Md Mujahedul},
  keywords = {Social Sciences, Ethical Distance and Candidate Support; Moral Disagreement and Electoral Accountability; Moral Issues; Conjoint Experiments},
  title = {Replication Data for: Ethical Distance and Electoral Accountability: Voters Punish Politicians Whose Ethical Views Diverge from Societal Consensus},
  publisher = {Harvard Dataverse},
  year = {2026}
}

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