6,224 rated or chosen profiles from 778 respondents, in up to 4 tasks of 2 profiles varying on 5 attributes.

About this table

Description	778 market vendors, motorcycle-taxi drivers and shopkeepers in 18 Ugandan towns, interviewed face to face, compared 4 pairs of hypothetical officials accused of embezzlement. Outcomes are which official they would rather see punished and a 1-5 rating of how serious each official's corruption was.
Reference	Martin, L. (2021). All sins are not created equal: The factors that drive perceptions of corruption severity. Journal of Experimental Political Science, 8(1), 15-25.
DOI	10.1017/xps.2019.33
Licence	CC0 1.0
Source data	https://doi.org/10.7910/DVN/ID1KJG

Notes

Conjoint table (irw_conjoint). choice: "which official would you rather see prosecuted and punished?" (forced, no opt-out). rating: seriousness of the corruption, 1 = not at all to 5 = extremely serious; higher means more severe, the same direction as choice. Levels were shown as icons explained in Lusoga/Luganda; attr_ holds the English captions. GPS and interviewer identifiers dropped.

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

Size and shape

Respondents	778
Rows (one per respondent, task and profile)	6,224
Tasks per respondent (most)	4
Profiles per task	2
Attributes	5
Tasks with no profile chosen	0

Design

Topic	corruption accountability
A profile represents	person
Country	UG
Language shown	lg, xog
Language of stored levels	en
Task order	recorded in the deposit
Profile position	recorded in the deposit

Outcomes:

choice	Which of these two officials would you personally rather see prosecuted and punished for what they have done? (translated) [choice, forced]
rating	Now, on a scale of 1 to 5, how serious was the corruption that Official 1 is accused of (point to correct profile)? Was it not at all serious, a bit serious, somewhat serious, very serious, or extremely serious? (translated) [rating, 1 (not at all serious) to 5 (extremely serious)]

Columns

attr_funds_purposeattr_funds_sourceattr_governmentattr_money_spent_onattr_rolechoicecov_agecov_campaign_againstcov_contact_officialcov_education_yearscov_gendercov_goprotestcov_occupationcov_steal_upsetcov_talkneighbcov_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 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("martin_2021_corruption", source = "conj")

# Python
pip install irw

import irw
df = irw.fetch("martin_2021_corruption", source="conj")

How to cite

@article{Martin_2019, title={All Sins are not Created Equal: The Factors that Drive Perceptions of Corruption Severity}, volume={8}, ISSN={2052-2649}, url={http://dx.doi.org/10.1017/xps.2019.33}, DOI={10.1017/xps.2019.33}, number={1}, journal={Journal of Experimental Political Science}, publisher={Cambridge University Press (CUP)}, author={Martin, Lucy E. S.}, year={2019}, month=Dec, pages={15–25} }

Version and provenance

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