26,744 rated or chosen profiles from 2,233 respondents, in up to 6 tasks of 2 profiles varying on 5 attributes.

About this table

Description	Adults in 12 rural Malawian constituencies (face-to-face, 2022; n=2,233) chose which of two hypothetical MP candidates (gender, party, policy focus, education, profession) they would vote for and which others in their constituency would vote for, 6 pairs each, after a randomized voter-education or control video.
Reference	Ofosu, G. K., Seeberg, M. B., & Wahman, M. (2026). Messages matter: How voter education campaigns affect citizens' willingness to vote for women. Journal of Politics, 88(1), 145-161.
DOI	10.1086/734252
Licence	CC0 1.0
Source data	https://doi.org/10.7910/DVN/6FHV5B

Notes

Conjoint table (irw_conjoint). choice: "Which of these two candidates would you vote for as your MP?"; choice_others: "Which of these two candidates do you think others in your constituency would vote for as their MP?" Both forced choice, asked in random order (trial_self_first). Tasks with no recorded answer to one question have that outcome missing (25 and 56 tasks); tasks with neither are omitted. Attribute text is the authors' English labels; party = constituency winner (Major) / runner-up (Minor) / Independent, the actual names shown not deposited. trial_video is the randomized pre-conjoint video. Pilot dropped; 2,233 of the paper's 2,239 have answers.

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

Design

Topic	candidate choice
A profile represents	person
Country	MW
Language shown	unknown
Language of stored levels	en
Task order	recorded in the deposit
Profile position	recorded in the deposit

Outcomes:

choice	Which of these two candidates would you vote for as your MP? [choice, forced]
choice_others	Which of these two candidates do you think others in your constituency would vote for as their MP? [choice, forced]

Columns

attr_educationattr_genderattr_partyattr_policy_focusattr_professionattrpos_educationattrpos_genderattrpos_partyattrpos_policy_focusattrpos_professionchoicechoice_otherscov_agecov_close_to_partycov_constituencycov_gendercov_men_better_leaderscov_more_women_mps_2025cov_party_idcov_regioncov_vote_man_more_likely_wincov_voted_last_electioncov_woman_faces_discriminationidprofiletasktrial_self_firsttrial_video

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("ofosu_2026_malawi_women_candidates", source = "conj")

# Python
pip install irw

import irw
df = irw.fetch("ofosu_2026_malawi_women_candidates", source="conj")

How to cite

@article{Ofosu_2026, title={Messages Matter: How Voter Education Campaigns Affect Citizens’ Willingness to Vote for Women}, volume={88}, ISSN={1468-2508}, url={http://dx.doi.org/10.1086/734252}, DOI={10.1086/734252}, number={1}, journal={The Journal of Politics}, publisher={University of Chicago Press}, author={Ofosu, George Kwaku and Seeberg, Merete Bech and Wahman, Michael}, year={2026}, month=Jan, pages={145–161} }

Respondents	2,233
Rows (one per respondent, task and profile)	26,744
Tasks per respondent (most)	6
Profiles per task	2
Attributes	5
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

ofosu_2026_malawi_women_candidates