niazi_2020_mfq_stereotype

9,599 responses from 300 respondents to 32 items.

About this table

DescriptionSame 32 MFQ-32 statements rated as a prediction of the "average person's" moral judgment
ReferenceNiazi F, Inam A, Akhtar Z (2020). Accuracy of consensual stereotypes in moral foundations: A gender analysis. PLOS ONE, 15(3), e0229926. https://doi.org/10.1371/journal.pone.0229926
DOI10.1371/journal.pone.0229926
LicenceCC BY 4.0
Source datahttps://doi.org/10.1371/journal.pone.0229926.s002

Size and shape

Responses9,599
Respondents300
Items32
Response categories6
Responses per respondent31.997
Responses per item299.969
Density1.000
LongitudinalFALSE

Classification

age rangeAdult (18+)
sampleEducational
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.

InstrumentMoral Foundations Questionnaire (MFQ30), stereotype administration (rated as a typical member of the opposite gender would respond)
Mean words per item10.906
Mean characters per item60.781
Mean characters per response16.500
Flesch-Kincaid grade level6.549

Columns

cov_agecov_educationcov_genderiditemresp

Get the data

Download CSVno account neededBrowse on Redivisexplore and queryCroissant metadataHugging Face, Kaggle, OpenML

Or load it directly in R or Python:

# R
install.packages("remotes")
remotes::install_github("itemresponsewarehouse/Rpkg")
library(irw)
df <- irw_fetch("niazi_2020_mfq_stereotype")
# Python
pip install irw

import irw
df = irw.fetch("niazi_2020_mfq_stereotype")

Version and provenance

IRW versionv393
Redivis datasetitem_response_warehouse_3 v7.0
Redivis dataset DOI10.57761/pqqn-pm43
Manifest pin for this IRW versionv7.0
Metadata sourceirw_meta v23.0