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Record W3117892350 · doi:10.7202/1076197ar

Regendering the Canadian Armed Forces

2021· article· en· W3117892350 on OpenAlexafffundabout
Victoria Tait

Bibliographic record

VenueAtlantis Critical Studies in Gender Culture & Social Justice · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicGender, Security, and Conflict
Canadian institutionsCarleton University
FundersCanadian Armed Forces
KeywordsMilitarismMasculinityGender studiesPolitical scienceMilitary serviceFemininitySociologyPeacekeepingLawPolitics

Abstract

fetched live from OpenAlex

Although feminist scholars agree that there exists a systemic relationship between masculinity and militarism, the exact contours of that relationship are debatable. Most feminists argue that as a primary goal, the women’s movement ought to seek approaches for the abolition of militarism, rather than using women’s participation in the military as a means of enhancing gender equality. Despite admonitions about the dangers of pursuing gender equality through military service, feminists must also weigh these concerns against women’s advances within the military and the use of the military in peacekeeping and humanitarian operations, both of which are essential to the Women, Peace and Security agenda. This article therefore turns a critical feminist lens on theories of military re-gendering. I explore whether military organizations that have traditionally valorized militarized masculinity can be transformed—both at an individual and systemic level—to embrace an egalitarian iteration of masculinity and contribute to a more peaceable international system. To examine the possibility of regendering in the Canadian Armed Forces (CAF), I review 17 interviews that I conducted with members of the CAF from 2017-2018 using theories of military regendering. My analysis indicates that servicemembers are engaging in critical examination of the military’s gender culture, and their position within that culture. By critically engaging with questions about the relationship between gender and militarism, military personnel may be participating in the incremental—and fragile—process of improving the gender culture of the CAF.

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)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.968
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0050.001
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.131
GPT teacher head0.410
Teacher spread0.279 · 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.

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

Citations5
Published2021
Admission routes3
Has abstractyes

Explore more

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