american_multiracial_face

124,082 responses from 1,145 respondents to 2,371 items.

About this table

DescriptionParticipants rate photos of smiling and neutral faces of mix-heritage people based on different measures
ReferenceChen, J.M., Norman, J.B. & Nam, Y. Broadening the stimulus set: Introducing the American Multiracial Faces Database. Behav Res (2020). https://doi.org/10.3758/s13428-020-01447-8
DOI10.3758/s13428-020-01447-8
LicenceCC BY 4.0
Source datahttps://osf.io/qsdrp/

Size and shape

Responses124,082
Respondents1,145
Items2,371
Response categories7
Responses per respondent108.369
Responses per item52.333
Density0.046
LongitudinalFALSE

Classification

age rangeAdult (18+)
sampleEducational, Internet-based
construct typeOpinion/attitude
measurement toolSurvey/questionnaire
item formatLikert Scale/selected response
primary language(s)eng
construct nameAmerican Multiracial Faces Database

Item text

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

InstrumentAmerican Multiracial Faces Database (AMFD) face-rating norming task
Mean words per item24.339
Mean characters per item171.305
Mean characters per response14.276
Flesch-Kincaid grade level16.753

Columns

iditemresp

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("american_multiracial_face")
# Python
pip install irw

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

Version and provenance

IRW versionv393
Redivis datasetitem_response_warehouse v53.0
Redivis dataset DOI10.57761/4g08-xt41
Manifest pin for this IRW versionv53.0
Metadata sourceirw_meta v23.0