gordils_2021_interracial_trust

10,180 responses from 2,549 respondents to 4 items.

One of 5 tables from the same source; this one is the interracial_trust table. The others are listed under Related tables.

About this table

Description4-item interracial trust/mistrust scale, adapted from a general trust scale (1-7 Likert, kept raw/un-reverse-coded), 2-study US survey on interracial competition and psychological outcomes
ReferenceGordils J, et al. (2021) The effect of perceived interracial competition on psychological outcomes. PLoS ONE.
DOI10.1371/journal.pone.0245671
LicenceCC BY 4.0
Source datahttps://journals.plos.org/plosone/article/file?type=supplementary&id=10.1371/journal.pone.0245671.s004

Size and shape

Responses10,180
Respondents2,549
Items4
Response categories7
Responses per respondent3.994
Responses per item2,545
Density0.998
LongitudinalFALSE

Classification

sampleInternet-based
measurement toolSurvey/questionnaire
item formatLikert Scale/selected response
primary language(s)eng

Item text

This table has item text in the IRW: the wording administered to respondents, not just the response codes.

InstrumentPerceived Interracial Trust (adapted from the General Trust Scale; Yamagishi & Yamagishi, 1994)
Mean words per item14
Mean characters per item73.500
Mean characters per response5.143
Flesch-Kincaid grade level5.041

Codebook

This codebook is reconstructed by the IRW from the IRW data standard and the script that built it, gordils_2021_interracial.py. It is our best reading, not the source’s own codebook, and it may contain mistakes. Where the two disagree, the source data are the authority. If you find an error, please tell us.

ColumnWhat it isSource column
IRW standard columns
idIRW standard Identifier for the focal unit being measured — typically a person, but sometimes another entity (e.g., a word in a lexical task).made in the build script
itemIRW standard Item identifier.made in the build script
respIRW standard Response value.made in the build script

What item codes and covariate values stand for is in the codebook released with the source data.

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("gordils_2021_interracial_trust")
# Python
pip install irw

import irw
df = irw.fetch("gordils_2021_interracial_trust")

How to cite

@article{Gordils_2021, title={The effect of perceived interracial competition on psychological outcomes}, volume={16}, ISSN={1932-6203}, url={http://dx.doi.org/10.1371/journal.pone.0245671}, DOI={10.1371/journal.pone.0245671}, number={1}, journal={PLOS ONE}, publisher={Public Library of Science (PLoS)}, author={Gordils, Jonathan and Elliot, Andrew J. and Jamieson, Jeremy P.}, editor={Shook, Natalie J.}, year={2021}, month=Jan, pages={e0245671} }

Version and provenance

IRW versionv566
Redivis datasetitem_response_warehouse_4 v13.0
Redivis dataset DOI10.57761/w8zx-td92
Manifest pin for this IRW versionv13.0
Metadata sourceirw_meta v43.0