Ending Interjections? The Impact of a Higher Proportion of Women in Canadian Legislatures
Bibliographic record
Abstract
Despite the drama it brings to oft mundane proceedings, heckling is despised by both politicians and the Canadian public. Is it possible that increasing the number of women in politics could change this aspect of our political culture? This project draws on two bodies of literature that would answer this question in opposite ways. The first, critical mass theory, argues that women will be better suited to effect change as they become a larger minority in politics. The second, backlash theory, argues that women will be subject to increased resistance from men and thus less able to effect change as they grow to constitute a larger minority. A quantitative analysis of heckling during Question Period in the Legislative Assembly of British Columbia, the Legislative Assembly of New Brunswick, and the federal House of Commons suggests that critical mass theory is more applicable in the Canadian context. Further, this analysis suggests women experience heckling in unique ways. Overall levels of heckling are highest in the legislature with the fewest women, and women are the targets of heckling most often in the legislature with the fewest women.
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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 | 0.004 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.033 | 0.009 |
| Scholarly communication | 0.008 | 0.002 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.015 | 0.001 |
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".