Women in Political Science: A History of the Canadian Political Science Association’s Women’s Caucus
Bibliographic record
Abstract
Abstract Since its establishment in 1979, the Women’s Caucus of the Canadian Political Science Association (CPSA) has served an important networking, mentoring and advocacy role for women political scientists. While small and informal in its early days, over time the Caucus has become increasingly more formalized and structured in the support it provides to women within the discipline. Drawing on CPSA documents, scholarship on women in the discipline and interviews with several caucus participants, this article identifies the factors leading to the establishment of the CPSA’s Women’s Caucus and traces its development and history over the past five decades. It identifies four distinct periods within the Caucus’s history (1970–1979, 1980–1992, 1993–2005 and 2006 to the present) and argues that as women’s role in the academy has changed, the Caucus has taken on a wider range of priorities and tasks, reflecting the changing composition of the discipline.
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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 | 0.008 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.005 | 0.009 |
| Science and technology studies | 0.052 | 0.032 |
| Scholarly communication | 0.012 | 0.004 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.009 | 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".