The representativeness of neighbourhood associations in Toronto and Vancouver
Bibliographic record
Abstract
Neighbourhood associations are major players in urban politics throughout North American cities and increasingly are becoming a political force in other parts of the world. However, while there is a rich and well-developed literature on the role played by neighbourhood associations in urban politics, few studies examine whether their membership reflects the socio-demographic composition and interests of the broader public. This paper addresses this gap in the literature using survey data from voters conducted during the Vancouver and Toronto 2018 municipal elections. We compare the responses of participants who identify as members of neighbourhood associations (or their equivalents) with those of the broader voting public. We find that members of neighbourhood associations in both cities are not representative of the broader population. They are more likely to be white, older and have higher education than the average voter. In addition, while the ideology of neighbourhood association members differs little from that of the broader public, their policy priorities are different from those of the majority of voters in both cities. Our findings suggest that neighbourhood associations fail in providing descriptive representation and may not offer substantive representation. These findings raise important questions about the role of neighbourhood associations in local governance. Our study also demonstrates the merit of using individual-level surveys to learn more about the composition and policy preferences of neighbourhood associations.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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 source (direct Gemma or distilled Codex), 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".