22,192 rated or chosen profiles from 1,387 respondents, in up to 8 tasks of 2 profiles varying on 8 attributes.

One of 4 tables from the same source; this one is the unm_students table. The others are listed under Related tables.

About this table

Description	University of New Mexico students (2016) (n = 1387) each chose between 8 pairs of hypothetical faculty candidates described by 8 randomized attributes (gender, race/ethnicity, heritage, research record, teaching record, PhD institution, spouse/partner a faculty member, community service record); outcome: which candidate should be given priority to be hired.
Reference	Carey, J. M., Carman, K. R., Clayton, K. P., Horiuchi, Y., Htun, M., & Ortiz, B. (2020). Who wants to hire a more diverse faculty? A conjoint analysis of faculty and student preferences for gender and racial/ethnic diversity. Politics, Groups, and Identities, 8(3), 535-553.
DOI	10.1080/21565503.2018.1491866
Licence	CC0 1.0
Source data	https://doi.org/10.7910/DVN/GD1UEI

Notes

Conjoint table (irw_conjoint). choice: "If you had to choose between them, which of these two candidates should be given priority to be hired as a new faculty member at the University of New Mexico?", forced choice between Candidate 1 and Candidate 2, no opt-out. Gender drawn 0.45/0.45/0.10 (Woman/Man/Non-binary), race White and Hispanic 0.35 each, and Non U.S. Citizen never paired with American Indian or Alaska Native; attribute order randomized per respondent (attrpos_). Respondents who did not finish the survey are not included, as in the paper; 1387 respondents, one more than the authors' estimates (1386), whose reader drops the first row of the export.

These notes describe the source data, which the IRW reproduces as released. All notes are listed on the Data Notes page.

Design

Topic	labour hiring
A profile represents	person
Country	US
Language shown	en
Language of stored levels	en
Randomization restrictions	observed in the data (not documented by the source): Heritage 'Non U.S. Citizen' never shown with race 'American Indian or Alaska Native' (randomizer restriction); level probabilities gender Woman/Man/Non-binary 0.45/0.45/0.10, race White 0.35, Hispanic or Latino 0.35, Black or African American/Asian/American Indian or Alaska Native 0.10 each, other attributes uniform; documented only in the faculty survey's randomizer (UNM_faculty.php); the student data show the same missing pair and shares
Task order	recorded in the deposit
Profile position	recorded in the deposit

Because the attribute levels were not randomized independently, an estimator has to account for the restriction; a plain difference in means across levels can mislead.

Outcomes:

choice	If you had to choose between them, which of these two candidates should be given priority to be hired as a new faculty member at the University of New Mexico? [choice, forced]

Columns

attr_genderattr_heritageattr_phdattr_raceattr_researchattr_serviceattr_spouse_facultyattr_teachingattrpos_genderattrpos_heritageattrpos_phdattrpos_raceattrpos_researchattrpos_serviceattrpos_spouse_facultyattrpos_teachingchoicecov_duration_seccov_gendercov_parent_collegecov_parent_incomecov_raceidprofiletask

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("carey_2020_hiring_unm_students", source = "conj")

# Python
pip install irw

import irw
df = irw.fetch("carey_2020_hiring_unm_students", source="conj")

How to cite

@article{Carey_2018, title={Who wants to hire a more diverse faculty? A conjoint analysis of faculty and student preferences for gender and racial/ethnic diversity}, volume={8}, ISSN={2156-5511}, url={http://dx.doi.org/10.1080/21565503.2018.1491866}, DOI={10.1080/21565503.2018.1491866}, number={3}, journal={Politics, Groups, and Identities}, publisher={Informa UK Limited}, author={Carey, John M. and Carman, Kevin R. and Clayton, Katherine P. and Horiuchi, Yusaku and Htun, Mala and Ortiz, Brittany}, year={2018}, month=Nov, pages={535–553} }

Respondents	1,387
Rows (one per respondent, task and profile)	22,192
Tasks per respondent (most)	8
Profiles per task	2
Attributes	8
Tasks with no profile chosen	0

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

carey_2020_hiring_unm_students