Women in the House: The Impact of Elected Women on Parliamentary Debate and Policymaking in Canada
Bibliographic record
Abstract
This study examines the impact of elected women in Canada on patterns and processes of parliamentary debate and policymaking from 1968 to 2015. It argues that women’s presence in parliament matters for the substantive representation of women, particularly under conditions of threat to women’s equality. The study refines core concepts in the literature on women’s political representation to explain how the substantive representation of women occurs in Canadian parliamentary institutions. It disaggregates the concept of substantive representation and expands the scope of the critical actors framework to include actions that defend women’s equality against regressive policy initiatives. Building on these refinements, the study argues that gender is a key factor in determining whether an MP will represent women in parliamentary debate, but the institutional role MPs occupy and the political context in which they operate influence the mechanisms they use to advocate for women’s equality in policymaking and their chances of success. Through an automated analysis of the content of nearly 50 years of parliamentary debate, the study finds that women MPs, regardless of party affiliation, are consistently more likely than their male colleagues to make representative claims about women. Using supervised and unsupervised machine learning to analyse the content of these representative claims, the study finds that parliamentary speeches about women focus almost entirely on issues relating to women’s equality and autonomy. The analysis of parliamentary debate shows that the number of speeches about women spiked during parliaments when governments initiated policies that threatened women’s equality. Qualitative case studies examine these two instances of policymaking, focusing on the actors involved, the processes through which they advocated for women, and the impact of their actions. The study finds that women MPs led the charge against hostile government policy initiatives but their varying ability to influence policy outcomes was shaped by their institutional positions and the political conditions under which they operated. The study concludes by suggesting the presence of women in Canadian politics matters as a tool for guarding against policies that would roll back previous equality gains. Efforts to increase women’s presence in electoral politics in Canada therefore remain important.
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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 | 0.001 |
| 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) | 0.000 | 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".