Gendering Public Policy or Rationalizing Gender? Strategic Interventions and GBA+ Practice in Canada
Bibliographic record
Abstract
Abstract The debate surrounding the transformative potential of gender mainstreaming has revived concerns of co-optation of equality work and resistance first expressed by early feminist public administration scholars. In this article, we explore how gender analysts exercised their agency and carved out spaces within the bureaucracy to articulate and advance a gender focus in policy work. Employing discursive, institutional and relational strategies, gender analysts simultaneously used and pushed back against hierarchical bureaucratic discourses as they operationalized Gender-Based Analysis Plus (GBA+) in the federal public bureaucracy. These micro-level acts of resistance, on their own, do not lead to social transformation. However, by creating spaces for feminist knowledge and activism within the state, these local strategies can contribute to the broader feminist agenda.
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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 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.027 | 0.019 |
| Scholarly communication | 0.011 | 0.002 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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".