martin_2021_minority_candidates

15,806 rated or chosen profiles from 7,903 respondents, in up to 1 tasks of 2 profiles varying on 6 attributes.

About this table

DescriptionPaired candidate-vignette conjoint on ethnic-minority candidates in Britain: 7,903 British Election Study Internet Panel (wave 11, April-May 2017) respondents chose between two hypothetical local candidates varying party, ethnic background (white British/Pakistani/black Caribbean), gender, immigration stance, law-enforcement priority and route into politics; half were randomly offered a 'neither' option.
ReferenceMartin, N. S., & Blinder, S. (2021). Biases at the ballot box: How multiple forms of voter discrimination impede the descriptive and substantive representation of ethnic minority groups. Political Behavior, 43(4), 1487-1510.
DOI10.1007/s11109-020-09596-4
LicenceCC0 1.0
Source datahttps://doi.org/10.7910/DVN/SUDLEG

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

Respondents7,903
Rows (one per respondent, task and profile)15,806
Tasks per respondent (most)1
Profiles per task2
Attributes6
Tasks with no profile chosen1,603

Design

Topiccandidate choice
A profile representsperson
CountryGB
Language shownen
Language of stored levelsen
Randomization restrictionsunknown
Task orderinferred from row order
Profile positioninferred from row order

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

Outcomes:

choiceWhich of these candidates would you rather have as your MP? [choice, opt-out allowed]

Columns

attr_ethnicityattr_genderattr_immigrationattr_law_enforcementattr_partyattr_routechoicecov_ethnicitycov_ft_asiancov_ft_blackcov_immig_enriches_culturecov_religioncov_religion_denominationcov_vote_intentionidprofiletasktrial_neither_offered

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("martin_2021_minority_candidates", source = "conj")
# Python
pip install irw

import irw
df = irw.fetch("martin_2021_minority_candidates", source="conj")

How to cite

@article{Martin_2020, title={Biases at the Ballot Box: How Multiple Forms of Voter Discrimination Impede the Descriptive and Substantive Representation of Ethnic Minority Groups}, volume={43}, ISSN={1573-6687}, url={http://dx.doi.org/10.1007/s11109-020-09596-4}, DOI={10.1007/s11109-020-09596-4}, number={4}, journal={Political Behavior}, publisher={Springer Science and Business Media LLC}, author={Martin, Nicole S. and Blinder, Scott}, year={2020}, month=Feb, pages={1487–1510} }

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