Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
A continuing debate in feminist scholarship on gender, security, and the military has been whether militaries can facilitate feminist progress and be forces for good. Feminists committed to working outside of militaries note that gender perspectives have often been used to advance the military’s goals of winning wars rather than commitments to feminist social transformation of military institutions and societies. However, influences from international normative frameworks on Women, Peace and Security; Canada’s feminist foreign policy; and an emphasis on diversity and inclusion within Canada’s Defence Policy have presented the Canadian Armed Forces with a solid platform from which it has begun to make change. The central tenets of this broad feminist platform have begun to permeate Canadian Professional Military Education (PME) through the collective efforts of educators, staff, and military students at Canada’s defence colleges. Drawing on a review of policy and programmes as well as a qualitative analysis of interviews with educators, staff, and military students, the article demonstrates that feminist transformational change by military members is possible by exploring its nascent reality. The article highlights the challenges and benefits of incorporating feminist perspectives in Canadian PME and demonstrates how and under what conditions military graduates with this education have begun to apply gender and cultural learning to make local feminist interventions both within and outside their institution. Ultimately, this research shows that collective efforts toward localized and incremental changes by military members are paving the way for meaningful feminist progress within the military.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it