mayne_2026_electoral_reform

About this table

Notes

• Conjoint table (irw_conjoint). Four forced choices between two electoral-reform scenarios per task (Scenario 1/2, no opt-out): choice = "If you had to choose one of these scenarios, which would you pick?"; choice_voice, choice_governability (1 = scenario judged to make legislation more difficult to pass) and choice_responsiveness. Attribute order randomized by respondent (attrpos_*); the ideology attribute was a graph, stored as its lead sentence plus the authors' label. Qualtrics IDs and free text dropped; 2,177 respondents and 12,842 rows as in the Supplementary Material.

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

Size and shape

Design

Outcomes:

Columns

attr_ballot_strucattr_district_magattr_ideo_repattr_num_partiesattr_party_supportattrpos_ballot_strucattrpos_district_magattrpos_ideo_repattrpos_num_partiesattrpos_party_supportchoicechoice_governabilitychoice_responsivenesschoice_voicecov_agecov_birth_yearcov_educationcov_gendercov_hispaniccov_ideologycov_incomecov_party_idcov_party_id7cov_satisfaction_democracyidprofiletask

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

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("mayne_2026_electoral_reform", source = "conj")

# Python
pip install irw

import irw
df = irw.fetch("mayne_2026_electoral_reform", source="conj")

How to cite

@article{MAYNE_2026, title={Attitudes Toward Electoral System Reform and Party System Change in the U.S.}, ISSN={1537-5943}, url={http://dx.doi.org/10.1017/S0003055426101658}, DOI={10.1017/s0003055426101658}, journal={American Political Science Review}, publisher={Cambridge University Press (CUP)}, author={MAYNE, QUINTON and SINGH, SHANE P.}, year={2026}, month=May, pages={1–24} }

Version and provenance