Finding Feminism(s) in Canadian Political Science Scholarship: Diversity and Resistance in an Era of Global Uncertainty
Bibliographic record
Abstract
It is with great pleasure that we present this special issue showcasing contemporary feminist political research, theories and practices in Canada. In an era characterized by global movements and numerous transformations that range from the economic to the environmental, the political to the cultural, from macro- through to micro-scales, including complex debates about the fluidity of gender, and where “backlash” against the symbols and agents of past feminist activism is rife, this special issue queries where do we find feminism(s) today? The responses to this question, as well as to the interrogation of the place of gender in the discipline of political science more generally, are undoubtedly diverse and contested. The collective efforts contained in this special issue feature a mere taste of the rich range of thought-provoking recent scholarship on feminisms. And even with this necessarily condensed portrayal (the articles in this issue are shorter than is normally the case to allow for more work to be featured), the special issue is ground-breaking in that it marks the first time the Canadian Journal of Political Science/Revue canadienne de science politique has dedicated an entire issue to topics of gender and feminisms.
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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 | 0.018 | 0.031 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.013 |
| Science and technology studies | 0.067 | 0.060 |
| Scholarly communication | 0.036 | 0.009 |
| Open science | 0.003 | 0.014 |
| Research integrity | 0.007 | 0.010 |
| Insufficient payload (model declined to judge) | 0.010 | 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".