Data · dataset · 2010
Replication data for: Spatial Approval Voting
Listed in Harvard Dataverse
This article provides a model for analyzing approval voting elections.
Description
Within a standard probabilistic spatial voting setting, we show that principal component analysis makes it possible to derive candidates' relative locations from the approval votes. We apply this technique to original experimental data from the French 2002 presidential election.
Links
Where it is published
- Dataverse dataset page dataverse.harvard.edu/dataset.xhtml?persistentId=doi%3A10.7910%2FDVN%2FUT9WBM ↗
landing page · from Harvard Dataverse
- DOI doi.org/10.7910/dvn/ut9wbm ↗
DOI / persistent id · from Harvard Dataverse
Catalogue records · 1
- Dataverse API dataverse.harvard.edu/api/datasets/:persistentId/?persistentId=doi%3A10.7910%2FDVN%2… ↗
metadata API · from Harvard Dataverse
Provenance · 1 source records, 6 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| Harvard Dataverse | doi:10.7910/DVN/UT9WBM | 14 d ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| created_date | source · Harvard Dataverse | connector:dataverse@1.0.0 | |
| description | source · Harvard Dataverse | connector:dataverse@1.0.0 | /description |
| publication_date | source · Harvard Dataverse | connector:dataverse@1.0.0 | |
| title | source · Harvard Dataverse | connector:dataverse@1.0.0 | /name |
| updated_date | source · Harvard Dataverse | connector:dataverse@1.0.0 | |
| version_label | source · Harvard Dataverse | connector:dataverse@1.0.0 |