Bang for Your Buck? Campaign Expenditures, Gender, and Election Outcomes in British Columbia Municipalities
Bibliographic record
Abstract
Elected municipal officials make key decisions about the bread-and-butter issues facing their constituents – and yet, little is known about the path to get there. Campaign expenditures within local elections, while regulated and publicly available, are not widely researched. Instead, the research agenda seems laser focused on federal and provincial campaign expenditures. Further, while local elections are seen as an electoral entry point for women, there are still persistent challenges women face. Researching campaign expenditures is important, as it can provide insight into the impacts of regulations, and the spending patterns of specific candidate populations. The research question is two-fold: Do candidates that are women invest more financial and volunteer resources than men throughout their municipal election campaigns? And if so, do they have more favourable election outcomes? This report will leverage data from a survey sent to all nominated candidates in the 2022 British Columbia municipal election. It will also draw on data published centrally by the province, including campaign expenditures and incumbency information. We find that there is no statistically significant relationship between financial campaign investments and sex. However, women do self-report leveraging more volunteers. We also find that a statistically significant relationship between campaign expenditures and overall vote share does exist. Further, in alignment with other studies, female candidates outperformed male in terms of electoral outcomes. Since understudied, this analysis can open the door for more research into the intersection of gender, campaign investments, and election outcomes in a Canadian context.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".