davenport_2026_black_classification

23,966 rated or chosen profiles from 2,397 respondents, in up to 5 tasks of 2 profiles varying on 9 attributes.

About this table

Description2,397 Black, White and mixed Black-White US adults (Qualtrics Panels, Dec 2020-Feb 2021) compared 5 pairs of hypothetical people varying parents' race (in half the forms), gender, skin tone, class, neighborhood, spouse, incarceration, discrimination and party; they picked the person who is more Black and rated each 0-10 on how Black.
ReferenceDavenport, L. D., Jefferson, H., & Rendleman, H. E. (2026). The politics of Black classification: Sociopolitical cues and racial perception. Perspectives on Politics.
LicenceCC0 1.0
Source datahttps://doi.org/10.7910/DVN/MRXND8

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

Respondents2,397
Rows (one per respondent, task and profile)23,966
Tasks per respondent (most)5
Profiles per task2
Attributes9
Tasks with no profile chosen0

Design

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

Outcomes:

choiceWhich person is more Black? (paraphrase) [choice, forced]
ratingHow Black is this person? (paraphrase) [rating, 0 (Not at all) to 10 (Very)]

Columns

attr_classattr_discriminationattr_genderattr_incarcerationattr_neighborhoodattr_parentsattr_partyattr_skin_toneattr_spousechoicecov_agecov_educationcov_gendercov_ideologycov_incomecov_mixed_black_whitecov_party_idcov_party_leancov_racecov_stateidprofileratingtasktrial_ancestry_showntrial_skin_tone_row

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("davenport_2026_black_classification", source = "conj")
# Python
pip install irw

import irw
df = irw.fetch("davenport_2026_black_classification", source="conj")

How to cite

@misc{https://doi.org/10.7910/dvn/mrxnd8,
  doi = {10.7910/DVN/MRXND8},
  url = {https://dataverse.harvard.edu/citation?persistentId=doi:10.7910/DVN/MRXND8},
  author = {Rendleman, Hunter and Jefferson, Hakeem and Davenport, Lauren},
  keywords = {Social Sciences, Race, Identity politics, Political behavior, Partisanship},
  title = {Replication Data for: The Politics of Black Classification: Sociopolitical Cues and Racial Perception},
  publisher = {Harvard Dataverse},
  year = {2026}
}

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