35,376 rated or chosen profiles from 2,948 respondents, in up to 3 tasks of 4 profiles varying on 2 attributes.

About this table

Description	US Qualtrics respondents (fall 2020; 2,418 in wave 1 plus 530 recontacted in wave 2) voted in three mock local elections (mayor, district council, at-large council) of four candidates shown by name (signalling race and gender) and, for half, party, under randomly assigned plurality or ranked-choice rules. Outcomes: top choice (single-winner races), plurality vote marks and RCV ranks.
Reference	Crowder-Meyer, M., Gadarian, S. K., & Trounstine, J. (2023). Ranking candidates in local elections: Neither panacea nor catastrophe for candidates of color. Journal of Experimental Political Science, 11(2), 117-134.
DOI	10.1017/XPS.2023.6
Licence	CC0 1.0
Source data	https://doi.org/10.7910/DVN/30EYIE

Notes

Conjoint table (irw_conjoint). Mock local elections with 4 named candidates per office (party shown in the partisan arm, else (not shown)); trial_rcv: plurality or ranked-choice ballot. choice = top choice in mayor and district races (plurality vote or first rank), NA for the two-winner at-large race; rating_vote = plurality mark (1 = voted for), rating_rank = RCV rank (1 = first preference, lower = more preferred). No abstention. Wave-2 recontacts (trial_wave = 2) have new, unlinkable ids. Wording not deposited.

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	2,948
Rows (one per respondent, task and profile)	35,376
Tasks per respondent (most)	3
Profiles per task	4
Attributes	2
Tasks with no profile chosen	0

Design

Topic	candidate choice
A profile represents	person
Country	US
Language shown	en
Language of stored levels	en
Task order	inferred from row order
Profile position	recorded in the deposit

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

Outcomes:

choice	Vote for one candidate (plurality) or rank the candidates (RCV); top choice in the mayor and district council races (paraphrase) [choice, forced]
rating_rank	Ranked-choice ballot: rank all four candidates (paraphrase) [rating, 1 (first preference) to 4 (last preference)]
rating_vote	Plurality ballot: vote for one candidate (mayor, district council) or two candidates (at-large council) (paraphrase) [rating, 0 (not voted for) to 1 (voted for)]

Columns

attr_nameattr_partychoicecov_duration_seccov_educationcov_gendercov_ideology3cov_latinocov_party_id7cov_race2idprofilerating_rankrating_votetasktrial_officetrial_partisantrial_rcvtrial_wave

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("crowdermeyer_2023_rcv_candidates", source = "conj")

# Python
pip install irw

import irw
df = irw.fetch("crowdermeyer_2023_rcv_candidates", source="conj")

How to cite

@article{Crowder_Meyer_2023, title={Ranking Candidates in Local Elections: Neither Panacea nor Catastrophe for Candidates of Color}, volume={11}, ISSN={2052-2649}, url={http://dx.doi.org/10.1017/XPS.2023.6}, DOI={10.1017/xps.2023.6}, number={2}, journal={Journal of Experimental Political Science}, publisher={Cambridge University Press (CUP)}, author={Crowder-Meyer, Melody and Gadarian, Shana Kushner and Trounstine, Jessica}, year={2023}, month=Mar, pages={117–134} }

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