Understanding Support for Municipal Political Parties: Evidence from Canada
Bibliographic record
Abstract
The province of Ontario, Canada, has a longstanding history of non-partisanship in municipal elections. In this distinctive context, we report results on citizen attitudes toward municipal partisanship using a survey of eligible voters in Canada's most populous province. Using a mixed-methods approach, we focus on three interrelated research questions. First, how much does citizen support for municipal parties depend on the type of party under consideration? Second, what reasons do citizens provide for their preference for either municipal political parties or independents? Finally, what are the correlates of support for municipal parties? We find little support for municipal political parties, and that many voters have sophisticated reasons for preferring either independents or parties. We also identify several factors associated with support for parties. These results provide an in-depth picture of attitudes on municipal partisanship in Ontario, and suggest that public opinion may provide an overlooked mechanism that maintains Ontario's non-partisanship.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".