3,468 rated or chosen profiles from 1,734 respondents, in up to 1 tasks of 2 profiles varying on 7 attributes.

One of 2 tables from the same source; this one is the uk table. The others are listed under Related tables.

About this table

Description	1,734 UK (YouGov) respondents each chose between two hypothetical parliamentary candidates varying on 7 attributes and rated each candidate's qualification (1-11), after a randomized Control/Parity/Quota framing.
Reference	Coffé, H., Saha, S., & Weeks, A. C. (2024). Quotas or parity? How the framing of positive action measures impacts public support and backlash. Journal of European Public Policy, 32(10), 2409-2438.
DOI	10.1080/13501763.2024.2402864
Licence	CC0 1.0
Source data	https://doi.org/10.7910/DVN/KH0SQ2

Notes

Conjoint table (irw_conjoint_2). UK sample: one pair of hypothetical parliamentary candidates per respondent (7 attributes: gender, marital status, policy priority, experience, age, career, skill) after a randomized framing of positive-action measures (Control/Parity/Quota, trial_framing). choice = which candidate, no opt-out; rating_qualified = 1-11 qualified-to-be-MP rating. Wording not in the deposit; N=1734.

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	1,734
Rows (one per respondent, task and profile)	3,468
Tasks per respondent (most)	1
Profiles per task	2
Attributes	7
Tasks with no profile chosen	0

Design

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

Outcomes:

choice	Which of the two candidates (Candidate 1 / Candidate 2) would you choose? (paraphrase; wording not in deposit) [choice, forced]
rating_qualified	How qualified is this candidate to be an MP? 1-11 (paraphrase; main.R: Perceived 'Qualified to be an MP' (1-11)) [rating, 1 (unknown) to 11 (unknown)]

Columns

attr_ageattr_careerattr_experienceattr_genderattr_marital_statusattr_policyattr_skillchoicecov_agecov_educationcov_gendercov_party_idcov_survey_weightidprofilerating_qualifiedtasktrial_framing

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("coffe_2024_quota_uk", source = "conj")

# Python
pip install irw

import irw
df = irw.fetch("coffe_2024_quota_uk", source="conj")

How to cite

@article{Coff__2024, title={Quotas or parity? How the framing of positive action measures impacts public support and backlash}, volume={32}, ISSN={1466-4429}, url={http://dx.doi.org/10.1080/13501763.2024.2402864}, DOI={10.1080/13501763.2024.2402864}, number={10}, journal={Journal of European Public Policy}, publisher={Informa UK Limited}, author={Coffé, Hilde and Saha, Sparsha and Weeks, Ana Catalano}, year={2024}, month=Sept, pages={2409–2438} }

Version and provenance

IRW version	v584
Redivis dataset	irw_conjoint_2 v1.4
Redivis dataset DOI	10.57761/hk97-wv30
Manifest pin for this IRW version	v1.4
Metadata source	irw_meta v44.0