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Record W4416939653 · doi:10.1177/00207020251398109

Guest editors’ introduction: Contending with gendered contradictions and blind spots in Canadian foreign policy

2025· article· en· W4416939653 on OpenAlexaffabout
Leah Sarson, Leigh Spanner, Maya Eichler, Heather A. Smith

Bibliographic record

VenueInternational Journal Canada s Journal of Global Policy Analysis · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicGender, Security, and Conflict
Canadian institutionsMount Saint Vincent UniversityUniversity of Northern British ColumbiaSaint Mary's UniversityDalhousie University
Fundersnot available
KeywordsForeign policyScholarshipRhetoricStatus quoFeminismState (computer science)Economic JusticeEquity (law)

Abstract

fetched live from OpenAlex

Despite the extensive and multisectoral scholarship on Canada's approaches to gender equity in its foreign policy, over two decades have passed since the publication of the last volume on the subject. Mindful of this gap and of retrenched state commitments to gender equity amid a return to more “traditional” diplomatic and security concerns and intransigent antagonism to justice and equity-driven agendas, contributors to this special issue analyze feminist foreign policy in Canada to assess who the policies and rhetoric benefit, how they are conceptualized, and where they are located. The contributions speak to the paradoxes of Canada's feminist foreign policy through the themes of contradictions and blind spots. Canada's renewed commitments to militarism, the instrumentalization of women's representation in the Canadian Armed Forces, and the strategic absence of feminist rhetoric in relation to the war in Ukraine demonstrate the many contradictions of Canada's approach, while explorations of disability, migration, and post-secondary education showcase its blind spots. By emphasizing these contradictions and blind spots, the scholarship in this special issue critiques the contemporary gendered realities of Canada's global policies and actions to imagine alternatives to the status quo and the potential of emancipatory and wholistic feminist foreign policies.

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)0.001
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: none
Teacher disagreement score0.715
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
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 head0.012
GPT teacher head0.318
Teacher spread0.306 · 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
Published2025
Admission routes2
Has abstractyes

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