31,070 rated or chosen profiles from 3,107 respondents, in up to 5 tasks of 2 profiles varying on 6 attributes.

About this table

Description	Paraguayan respondents compared pairs of street-level bureaucrats described by 6 attributes (took bribes, diverted public funds, gender, party, age, education). 3,107 respondents, 5 paired tasks, three forced-choice outcomes per pair whose wording is not in the deposit.
Reference	Carreras, M., Vera, S., & Visconti, G. (2024). Gender stereotypes and petty corruption among street-level bureaucrats: Evidence from a conjoint experiment. Research & Politics, 11(3).
DOI	10.1177/20531680241277405
Licence	CC0 1.0
Source data	https://doi.org/10.7910/DVN/MGAQDT

Notes

Conjoint table (irw_conjoint). Three forced choices per pair (choice = the authors' main outcome outcome_q3; choice_q1, choice_q2 = alternative outcomes); the question wording is not in the deposit, no opt-out. Task and profile are inferred from row order (verified one chosen per pair). Attribute levels are the authors' English translations; the authors' matched subsample is not included.

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	3,107
Rows (one per respondent, task and profile)	31,070
Tasks per respondent (most)	5
Profiles per task	2
Attributes	6
Tasks with no profile chosen	0

Design

Topic	corruption accountability, public administration
A profile represents	person
Country	PY
Language shown	unknown
Language of stored levels	en
Randomization restrictions	unknown
Task order	inferred from row order
Profile position	inferred from row order

Task order or profile position was rebuilt from row order; analyses of position or task order should leave it out.

Outcomes:

choice	unknown (the authors' main outcome, outcome_q3; wording not in the deposit) [choice, forced]
choice_q1	unknown (alternative outcome outcome_q1; wording not in the deposit) [choice, forced]
choice_q2	unknown (alternative outcome outcome_q2; wording not in the deposit) [choice, forced]

Columns

attr_ageattr_educationattr_genderattr_partyidattr_speedattr_theftchoicechoice_q1choice_q2cov_education_codecov_genderidprofiletask

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("carreras_2024_corrupt_bureaucrats", source = "conj")

# Python
pip install irw

import irw
df = irw.fetch("carreras_2024_corrupt_bureaucrats", source="conj")

How to cite

@article{Carreras_2024, title={Gender stereotypes and petty corruption among street-level bureaucrats: Evidence from a conjoint experiment}, volume={11}, ISSN={2053-1680}, url={http://dx.doi.org/10.1177/20531680241277405}, DOI={10.1177/20531680241277405}, number={3}, journal={Research &amp; Politics}, publisher={SAGE Publications}, author={Carreras, Miguel and Vera, Sofia and Visconti, Giancarlo}, year={2024}, month=July }

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