18,000 rated or chosen profiles from 1,000 respondents, in up to 6 tasks of 3 profiles varying on 3 attributes.

About this table

Description	Discrete choice experiment: 1,000 French adults chose among a glyphosate ban and two glyphosate taxes described by reduction of farmers' glyphosate use, weekly food basket price rise and use of the tax revenue; two cost-vector blocks (B3, B4); 6 forced choices each.
Reference	Martinet, V., David, M., Mermet-Bijon, V., & Crastes dit Sourd, R. (2025). Cost vector effects in forced-choice discrete choice experiments: Assessing the acceptability of future glyphosate policies. Journal of Choice Modelling.
DOI	10.1016/j.jocm.2025.100550
Licence	Etalab 2.0
Source data	https://doi.org/10.57745/0VNN1B

Notes

Conjoint table (irw_conjoint_2). Forced choice among three glyphosate policies per task (a ban and two taxes) described by the reduction of farmers' glyphosate use, the rise in weekly food basket price (EUR) and the use of the tax revenue (French card text): "Quelle est votre option préférée?"; no opt-out. Option 1 is always the ban. trial_cost_vector marks the two cost-vector blocks (B3: ban +3 EUR, B4: ban +4 EUR). Levels were decoded from numeric codes and checked against the choice-card images; gender and education codes have no codebook and are kept as _code columns. 1,000 respondents, 6 tasks.

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

Size and shape

Respondents	1,000
Rows (one per respondent, task and profile)	18,000
Tasks per respondent (most)	6
Profiles per task	3
Attributes	3
Tasks with no profile chosen	0

Design

Topic	climate energy environment
A profile represents	policy
Country	FR
Language shown	fr
Language of stored levels	fr
Randomization restrictions	observed in the data (not documented by the source): option 1 is always the ban (100% reduction, no revenue); each tax option has exactly one revenue use; price levels depend on the reduction and block (B3 tax prices 1-2, B4 1-3)
Task order	recorded in the deposit
Profile position	recorded in the deposit

Because the attribute levels were not randomized independently, an estimator has to account for the restriction; a plain difference in means across levels can mislead.

Outcomes:

choice	Quelle est votre option préférée? (Je choisis : l'option 1; option 2; option 3) [choice, forced]

Columns

attr_food_basket_price_riseattr_glyphosate_reductionattr_tax_revenue_usechoicecov_agecov_education_codecov_gender_codeidprofiletasktrial_cost_vector

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("martinet_2025_glyphosate_policy", source = "conj")

# Python
pip install irw

import irw
df = irw.fetch("martinet_2025_glyphosate_policy", source="conj")

How to cite

@article{Martinet_2025, title={Cost vector effects in forced-choice discrete choice experiments: Assessing the acceptability of future glyphosate policies}, volume={55}, ISSN={1755-5345}, url={http://dx.doi.org/10.1016/j.jocm.2025.100550}, DOI={10.1016/j.jocm.2025.100550}, journal={Journal of Choice Modelling}, publisher={Elsevier BV}, author={Martinet, Vincent and David, Maïa and Mermet-Bijon, Vincent and Crastes Dit Sourd, Romain}, year={2025}, month=June, pages={100550} }

Version and provenance

IRW version	v584
Redivis dataset	irw_conjoint_2 v1.4
Redivis dataset DOI	10.57761/hk97-wv30
Manifest pin for this IRW version	v1.4
Metadata source	irw_meta v44.0