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Record W2885242752 · doi:10.1080/23337486.2018.1494883

Sexual (mis)conduct in the Canadian forces

2018· article· en· W2885242752 on OpenAlexaffabout
Marcia Kovitz

Bibliographic record

VenueCritical Military Studies · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicGender, Security, and Conflict
Canadian institutionsJohn Abbott CollegeCegep de ThetfordDawson CollegeCegep de Trois-Rivieres
Fundersnot available
KeywordsMandateHarassmentMilitary justiceHostilityCriminologyHarmSexual misconductResistance (ecology)Political scienceMisconductState (computer science)LawSociologyDisciplineOrganizational cultureSocial psychologyPublic relationsPsychology

Abstract

fetched live from OpenAlex

This essay compares findings of Marie Deschamps’ 2015 report on sexual harassment and assault in the Canadian Armed Forces (CAF) with my earlier 1990s study of gender integration in the CAF. Both demonstrate that CAF culture is sexualized and misogynistic. Deschamps argues that changing this culture is a pre-requisite for addressing sexual misconduct. But is such cultural change possible if the CAF’s mandate and principal organizational features remain unchanged? I argue that (1) gendered military culture is grounded in the CAF’s hierarchal social structure, disciplinary system, and conditions of service designed to achieve operational effectiveness; and (2) the CAF’s normalized atmosphere of sexualized hostility to women soldiers originates in tensions within the military’s internal relations of domination designed to preclude soldiers’ resistance and ensure that they enter harm’s way to execute the military’s mandate of state-sponsored lethal violence. As long as these hold, the problem of sexual misconduct may remain intractable.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.101
Threshold uncertainty score0.733

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0050.007
Science and technology studies0.0260.010
Scholarly communication0.0040.002
Open science0.0010.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0050.000

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 head0.166
GPT teacher head0.419
Teacher spread0.253 · 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 source (direct Gemma or distilled Codex), 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

Citations16
Published2018
Admission routes2
Has abstractyes

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