dasandi_2022_climate_frames

75,120 rated or chosen profiles from 7,512 respondents, in up to 5 tasks of 2 profiles varying on 4 attributes.

One of 2 tables from the same source; this one is the frames table. The others are listed under Related tables.

About this table

DescriptionOnline panel respondents in China, Germany, India, the UK and the USA (Deltapoll, October 2020, n = 7,512) chose which of two climate-change statements, varying valence, theme, scale and time frame, would make them more likely to support climate policies, in 5 paired tasks.
ReferenceDasandi, N., Graham, H., Hudson, D., Jankin, S., vanHeerde-Hudson, J., & Watts, N. (2022). Positive, global, and health or environment framing bolsters public support for climate policies. Communications Earth & Environment, 3, 239.
DOI10.1038/s43247-022-00571-x
LicenceCC0 1.0
Source datahttps://doi.org/10.7910/DVN/XJ4VEH

Notes

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

Size and shape

Respondents7,512
Rows (one per respondent, task and profile)75,120
Tasks per respondent (most)5
Profiles per task2
Attributes4
Tasks with no profile chosen0

Design

Topicpolitical communication, climate energy environment
A profile representsmessage
CountryCN, DE, IN, GB, US
Language shownen, zh, de
Language of stored levelsen
Task orderrecorded in the deposit
Profile positionrecorded in the deposit

Outcomes:

choiceIndicate which of the two statements would make you more likely to support policies to tackle climate change. [choice, forced]

Columns

attr_scaleattr_themeattr_timeattr_valencechoicecov_age_groupcov_care_climatecov_care_economiccov_care_educationcov_care_fakenewscov_care_globaldiseasescov_care_immigrationcov_care_inequalitycov_care_populismcov_care_technologycov_care_warcov_childrencov_concerncov_countrycov_gendercov_party_idcov_survey_weightcov_university_degreecov_work_statusidprofiletask

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 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("dasandi_2022_climate_frames", source = "conj")
# Python
pip install irw

import irw
df = irw.fetch("dasandi_2022_climate_frames", source="conj")

How to cite

@article{Dasandi_2022, title={Positive, global, and health or environment framing bolsters public support for climate policies}, volume={3}, ISSN={2662-4435}, url={http://dx.doi.org/10.1038/s43247-022-00571-x}, DOI={10.1038/s43247-022-00571-x}, number={1}, journal={Communications Earth &amp; Environment}, publisher={Springer Science and Business Media LLC}, author={Dasandi, Niheer and Graham, Hilary and Hudson, David and Jankin, Slava and vanHeerde-Hudson, Jennifer and Watts, Nick}, year={2022}, month=Oct }

Version and provenance

IRW versionv584
Redivis datasetirw_conjoint v4.2
Redivis dataset DOI10.57761/qkye-q530
Manifest pin for this IRW versionv4.2
Metadata sourceirw_meta v44.0