rcv_burlington_20060307_mayor

28,060 marked positions from 9,788 rankers over 7 options.

One of 4 tables from the same source; this one is the burlington_20060307_mayor table. The others are listed under Related tables.

About this table

DescriptionRanked-choice cast vote records, Burlington, Vermont mayor, 7 March 2006: single-winner (instant-runoff) election, 6 candidates, 5 rank positions offered, 9788 ballots with at least one mark (of 9865 in the file). One row per ballot x marked position; item = candidate code c01.. in alphabetical order of the printed names (names not stored), resp = position as marked. Rankings layout (draft irw_rankings family, data/rankings/README.md).
ReferenceFairVote. Single winner ranked choice voting CVRs [data set]. Harvard Dataverse. https://doi.org/10.7910/DVN/AMK8PJ
LicenceCC0 1.0
Source datahttps://doi.org/10.7910/DVN/AMK8PJ

Size and shape

Items7
Rankers9,788
Marked positions (one row each)28,060
Rankings per respondent1
Counting methodirv
Seatsunknown
Positions offered5
Candidates6
Ballots cast9,865
Ballots with marks9,788
Duplicate marks2
Overvotes34
Write-ins0
Write-in allowedunknown
Candidate orderunknown
JurisdictionBurlington
Contest date2006-03-07
OfficeMayor

Columns

iditemresptask

The layout (one row per respondent, ranking and marked position; resp the position as recorded, 1 = first choice; item a candidate code c01, c02, … or a reserved value) is defined in the IRW rankings standard. Skipped positions are gaps and duplicate marks are kept, so compress with irw_rank_compress() / irw.rank_compress() before a person-by-item pivot.

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("rcv_burlington_20060307_mayor", source = "rank")
# Python
pip install irw

import irw
df = irw.fetch("rcv_burlington_20060307_mayor", source="rank")

How to cite

@misc{https://doi.org/10.7910/dvn/amk8pj,
  doi = {10.7910/DVN/AMK8PJ},
  url = {https://dataverse.harvard.edu/citation?persistentId=doi:10.7910/DVN/AMK8PJ},
  author = {Otis, Deb},
  keywords = {Social Sciences},
  title = {Single winner ranked choice voting CVRs},
  publisher = {Harvard Dataverse},
  year = {2022}
}

Version and provenance

IRW versionv581
Redivis datasetirw_rank v1.1
Redivis dataset DOI10.57761/amk1-y692
Manifest pin for this IRW versionv1.0
Metadata sourceirw_meta v44.0