49,350 rated or chosen profiles from 4,935 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_pilot table. The others are listed under Related tables.

About this table

Description	Pilot fielding (file 'August pilot', n = 4,935) of the same design in China, Germany, India, the UK and the USA: respondents 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.
Reference	Dasandi, 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.
DOI	10.1038/s43247-022-00571-x
Licence	CC0 1.0
Source data	https://doi.org/10.7910/DVN/XJ4VEH

Notes

Conjoint table (irw_conjoint). Forced choice between two climate statements: "Indicate which of the two statements would make you more likely to support policies to tackle climate change." (exactly one chosen per task, no opt-out); four frames randomized without constraints (96 statements). Attribute levels are the authors' frame names, not the displayed sentences; the willingness-to-pay rating is dropped as undocumented. Pilot: the article mentions earlier pilots in the five countries (Supplementary Figs. S24-S25) but gives no n or date; 4,935 respondents in the file. Deltapoll IDs re-keyed; survey weight kept.

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

Design

Topic	political communication, climate energy environment
A profile represents	message
Country	CN, DE, IN, GB, US
Language shown	en, zh, de
Language of stored levels	en
Task order	recorded in the deposit
Profile position	recorded in the deposit

Outcomes:

choice	Indicate 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 needed Browse on Redivisexplore and query Croissant 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_pilot", source = "conj")

# Python
pip install irw

import irw
df = irw.fetch("dasandi_2022_climate_frames_pilot", 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 }

Respondents	4,935
Rows (one per respondent, task and profile)	49,350
Tasks per respondent (most)	5
Profiles per task	2
Attributes	4
Tasks with no profile chosen	0

IRW version	v584
Redivis dataset	irw_conjoint v4.2
Redivis dataset DOI	10.57761/qkye-q530
Manifest pin for this IRW version	v4.2
Metadata source	irw_meta v44.0

dasandi_2022_climate_frames_pilot