gerard_2018_metatraits

366,849 responses from 700 respondents to 525 items.

About this table

DescriptionBig Five and Metatraits
ReferenceDeYoung, C. G., Tai, M. H., Chou, E., & Mlačić, B. (2026). Are the metatraits fact or artifact? Ruling out alternative explanations for the higher-order factors of the Big Five. Journal of Personality and Social Psychology, 130(6), 1190–1207.
DOI10.1037/pspp0000593
LicenceCC0 1.0
Source datahttps://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/GHYMEV

Size and shape

Responses366,849
Respondents700
Items525
Response categories7
Responses per respondent524.070
Responses per item698.760
Density0.998
LongitudinalFALSE

Classification

age rangeAdult (18+)
sampleTargeted/specific
construct typePersonality
measurement toolSurvey/questionnaire
item formatLikert Scale/selected response
primary language(s)eng
construct nameBig Five and Metatraits

Item text

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

Instrument525 Person-descriptive Adjectives (525-PDA)
Mean words per item1
Mean characters per item8.333
Mean characters per response93.429
Flesch-Kincaid grade level15.337

Codebook

This codebook is reconstructed by the IRW from the IRW data standard and the script that built it, gerard_2018_metatraits.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("gerard_2018_metatraits")
# Python
pip install irw

import irw
df = irw.fetch("gerard_2018_metatraits")

How to cite

@article{DeYoung_2026, title={Are the metatraits fact or artifact? Ruling out alternative explanations for the higher-order factors of the Big Five.}, volume={130}, ISSN={0022-3514}, url={http://dx.doi.org/10.1037/pspp0000593}, DOI={10.1037/pspp0000593}, number={6}, journal={Journal of Personality and Social Psychology}, publisher={American Psychological Association (APA)}, author={DeYoung, Colin G. and Tai, Ming Him and Chou, Edward and Mlačić, Boris}, year={2026}, month=June, pages={1190–1207} }

Version and provenance

IRW versionv549
Redivis datasetitem_response_warehouse_2 v33.0
Redivis dataset DOI10.57761/6m04-m698
Manifest pin for this IRW versionv33.0
Metadata sourceirw_meta v39.0