ahler_2022_james_vignette

1,991 rated or chosen profiles from 1,991 respondents, in up to 1 tasks of 1 profile varying on 4 attributes.

About this table

DescriptionUS MTurk workers (2018, n = 1,991; 1,507 pass the authors' quality filter) read one 'James' vignette with race, spouse's name (Karen/Keith), free-time activity (Baptist/secular scouting/sports) and demonstrations (anti-tax/living-wage/student government) randomized, and chose which statement about James is most likely (sales / sales and Democrat / sales and Republican).
ReferenceAhler, D. J., & Sood, G. (2022). Typecast: A routine mental shortcut causes party stereotyping. Political Behavior.
DOI10.1007/s11109-022-09780-8
LicenceCC0 1.0
Source datahttps://doi.org/10.7910/DVN/KBX2SL

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

Respondents1,991
Rows (one per respondent, task and profile)1,991
Tasks per respondent (most)1
Profiles per task1
Attributes4

Design

Topicsocial identity interpersonal
A profile representsperson
CountryUS
Language shownen
Language of stored levelsen
Task orderrecorded in the deposit
Profile positionrecorded in the deposit

Outcomes:

ratingWhich of the following is most likely? (James works in sales / James works in sales and is an active supporter of the Democratic Party / James works in sales and is an active supporter of the Republican Party) [rating, 1 (James works in sales) to 3 (James works in sales and is an active supporter of the Republican Party)]

Columns

attr_activityattr_demonstrationsattr_raceattr_spousecov_age_group_codecov_education_codecov_gender_codecov_ideo3cov_party_idcov_party_id7_codecov_state_codecov_untrustworthyidprofileratingtask

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("ahler_2022_james_vignette", source = "conj")
# Python
pip install irw

import irw
df = irw.fetch("ahler_2022_james_vignette", source="conj")

How to cite

@article{Ahler_2022, title={Typecast: A Routine Mental Shortcut Causes Party Stereotyping}, volume={45}, ISSN={1573-6687}, url={http://dx.doi.org/10.1007/s11109-022-09780-8}, DOI={10.1007/s11109-022-09780-8}, number={4}, journal={Political Behavior}, publisher={Springer Science and Business Media LLC}, author={Ahler, Douglas J. and Sood, Gaurav}, year={2022}, month=Feb, pages={1581–1607} }

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