623 marked positions from 576 rankers over 2 options.
One of 4 tables from the same source; this one is the takoma_20221108_councilward4 table. The others are listed under Related tables.
| Description | Ranked-choice cast vote records, Takoma Park, Maryland city council Ward 4, 8 November 2022 (one named candidate on the ballot): single-winner (instant-runoff) election, 1 candidates, 2 rank positions offered, 576 ballots with at least one mark (of 576 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. Single winner ranked choice voting CVRs [data set]. Harvard Dataverse. https://doi.org/10.7910/DVN/AMK8PJ |
| Licence | CC0 1.0 |
| Source data | https://doi.org/10.7910/DVN/AMK8PJ |
| Items | 2 |
|---|---|
| Rankers | 576 |
| Marked positions (one row each) | 623 |
| Rankings per respondent | 1 |
| Counting method | irv |
| Seats | unknown |
| Positions offered | 2 |
| Candidates | 1 |
| Ballots cast | 576 |
| Ballots with marks | 576 |
| Duplicate marks | 18 |
| Overvotes | 0 |
| Write-ins | 36 |
| Write-in allowed | yes |
| Candidate order | unknown |
| Jurisdiction | TakomaPark |
| Contest date | 2022-11-08 |
| Office | CityCouncilWard4 |
cov_wardiditemresptask
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_takoma_20221108_councilward4", source = "rank")
# Python
pip install irw
import irw
df = irw.fetch("rcv_takoma_20221108_councilward4", source="rank")
@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}
}
| 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 |