Which Center for Election Science team member had the best ugly sweater?
57 ballots
Kirsten Leading
48 votes (84%)
Caitlyn
17 votes (30%)
Chris
3 votes (5%)
Aaron
3 votes (5%)
Approval Distribution
| Number of Candidates Approved | ||||
|---|---|---|---|---|
| Candidate | 1 | 2 | 3 | 4 |
|
All Candidates
(57 voters)
|
78.9% | 19.3% | — | 1.8% |
|
Kirsten
(48 voters)
|
81.3% | 16.7% | — | 2.1% |
|
Caitlyn
(17 voters)
|
29.4% | 64.7% | — | 5.9% |
|
Chris
(3 voters)
|
— | 66.7% | — | 33.3% |
|
Aaron
(3 voters)
|
33.3% | 33.3% | — | 33.3% |
Co-Approval Matrix
Percentage of voters who approved the row candidate also approved the column candidate
| Approved | Kirsten | Caitlyn | Chris | Aaron |
|---|---|---|---|---|
| Kirsten | — | 18.8% | 2.1% | 2.1% |
| Caitlyn | 52.9% | — | 17.6% | 11.8% |
| Chris | 33.3% | 100.0% | — | 33.3% |
| Aaron | 33.3% | 66.7% | 33.3% | — |
Anyone But Analysis
No "Anyone But" voting patterns detected (no ballots with exactly N-1 approvals)
When electing multiple candidates to a board or committee Proportional Approval Voting ensures that no single voting group dominates the outcome, promoting fair representation and reflecting the diverse preferences of all voters. In scenarios where there are more seats than choices available and where each choice represents a party—this method can allow a popular party to be allocated multiple seats proportionally, mirroring the party’s share of overall support.