Bibliographic record
Abstract
Electorate size is recognized to affect a wide range of democratic processes and outcomes. This is particularly true at the local level of government where amalgamations have been common in recent years. Here, we explore the extent to which electorate size affects how city councillors communicate with their constituents in order to learn about those constituents’ needs and preferences. We hypothesize that councillors cope with increases in electorate size by using face-to-face methods of communication less and mediated forms of communication, including social media, more. Drawing on original interview and survey data with Canadian city councillors, we find that councillors tend to rely on face-to-face meetings, telephone calls, and email to communicate with constituents, but are less likely to use social media to do so. However, we find no evidence to support the hypothesized relationships between electorate size and representational communication. Résumé La taille de l’électorat affecte un large éventail de processus démocratiques et ses résultats. C’est particulièrement vrai au niveau local des gouvernements municipaux au cours des nombreuses fusions des dernières années. Cet article, examine dans quelle mesure la taille de l’électorat affecte la façon dont les conseillers municipaux communiquent avec les électeurs afin d’en apprendre davantage sur les besoins et préférences de ces derniers. Notre hypothèse de base est que les conseillers face à l’augmentation de la taille de l’électorat utilisent moins des méthodes de communication face-à-face au profit d’une utilisation accrue de forme de communication médiatisée, y compris les médias sociaux. S’appuyant sur les données de l’enquête et des entrevues avec les conseillers municipaux, nous constatons que ces derniers ont tendance à se fier à des réunions face-à-face, des appels téléphoniques et des courriels pour communiquer avec les électeurs. Ils sont donc moins susceptibles d’utiliser les médias sociaux. Toutefois, nous n’avons trouvé aucune preuve à l’appui de l’hypothèse d’une relation entre la taille de l’électorat et le type de communication utilisé pour communiquer avec les électeurs.
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.009 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".