1,058 marked positions from 384 rankers over 4 options.
| Description | Ranked-choice cast vote records, Genola, Utah city council, 2 November 2021: sequential election, 3 candidates, 4 rank positions offered, 384 ballots with at least one mark (of 393 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). |
|---|---|
| Reference | FairVote. Sequential ranked choice voting CVRs [data set]. Harvard Dataverse. https://doi.org/10.7910/DVN/04LOQX |
| Licence | CC0 1.0 |
| Source data | https://doi.org/10.7910/DVN/04LOQX |
| Items | 4 |
|---|---|
| Rankers | 384 |
| Marked positions (one row each) | 1,058 |
| Rankings per respondent | 1 |
| Counting method | sequential |
| Seats | unknown |
| Positions offered | 4 |
| Candidates | 3 |
| Ballots cast | 393 |
| Ballots with marks | 384 |
| Duplicate marks | 13 |
| Overvotes | 6 |
| Write-ins | 0 |
| Write-in allowed | unknown |
| Candidate order | unknown |
| Jurisdiction | Genola |
| Contest date | 2021-11-02 |
| Office | CityCouncil |
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.
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_genola_20211102_council", source = "rank")
# Python
pip install irw
import irw
df = irw.fetch("rcv_genola_20211102_council", source="rank")
@misc{https://doi.org/10.7910/dvn/04loqx,
doi = {10.7910/DVN/04LOQX},
url = {https://dataverse.harvard.edu/citation?persistentId=doi:10.7910/DVN/04LOQX},
author = {Laverty, Sabrina},
keywords = {Social Sciences},
title = {Sequential ranked choice voting CVRs},
publisher = {Harvard Dataverse},
year = {2022}
}
| IRW version | v581 |
|---|---|
| Redivis dataset | irw_rank v1.1 |
| Redivis dataset DOI | 10.57761/amk1-y692 |
| Manifest pin for this IRW version | v1.0 |
| Metadata source | irw_meta v44.0 |