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Record W4410127641 · doi:10.1080/14616742.2025.2486208

Soldier first or loyal military wife? What women in dual-service relationships reveal about the contemporary gendering of militaries

2025· article· en· W4410127641 on OpenAlexafffundabout
Leigh Spanner, Maya Eichler

Bibliographic record

VenueInternational Feminist Journal of Politics · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicGender, Security, and Conflict
Canadian institutionsMount Saint Vincent University
FundersSocial Sciences and Humanities Research Council of CanadaMinistère de la Défense Nationale
KeywordsWifeMilitary serviceDual (grammatical number)Gender studiesService (business)Political scienceSociologyLawBusinessArt

Abstract

fetched live from OpenAlex

Recent and ongoing efforts by the Canadian Armed Forces to recruit and retain more women, promote a more gender equal workplace, and support military spouses suggest that the military’s gender order is potentially being disrupted. In this article, we interrogate the contemporary gendering of militaries by centering the experiences of Canadian women who are both military members and military wives. We show how women in heterosexual dual-service relationships negotiate the tensions between competing gendered demands from military and family: the requirement to be a soldier first and the requirement to be a loyal military wife. These tensions are often reconciled in ways that place greater burdens on women and sustain the military’s heteropatriarchal culture. Our analysis underscores the necessity of empirically and theoretically attending to both public and private elements of the gendering of militaries. This calls for a deeper analytical integration of the feminist literature on military women and the feminist literature on military wives going forward.

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)0.002
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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.370
Threshold uncertainty score0.398

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.071
GPT teacher head0.336
Teacher spread0.265 · 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 designQualitative
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 routes3
Has abstractyes

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