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Record W7043376697

Situating Feminist Progress in Professional Military Education

2020· article· en· W7043376697 on OpenAlexfundaboutno aff

Bibliographic record

VenueJournals @ The Mount (Mount Saint Vincent University) · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicGender, Security, and Conflict
Canadian institutionsnot available
FundersMinistère de la Défense NationaleCanadian Defence Academy
KeywordsGovernment (linguistics)PretextCircumstantial evidenceSubject (documents)DerogationWork (physics)
DOInot available

Abstract

fetched live from OpenAlex

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.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.822
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.033
GPT teacher head0.301
Teacher spread0.268 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2020
Admission routes2
Has abstractyes

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