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Record W4399867351 · doi:10.1177/0095327x241257515

“I Just Don’t Want to Be Part of It Anymore”: How Harm and Betrayal Erode Cohesion in the Aftermath of Military Sexual Misconduct

2024· article· en· W4399867351 on OpenAlex
Stacey Silins

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueArmed Forces & Society · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicGender, Security, and Conflict
Canadian institutionsDepartment of National Defence
Fundersnot available
KeywordsBetrayalHarmCriminologySexual misconductMisconductCohesion (chemistry)Political sciencePsychologySocial psychologyLaw

Abstract

fetched live from OpenAlex

This study addresses the nature of harm and betrayal following sexual misconduct from the perspective of military personnel and veterans with lived experience, and its impact on military cohesion. A total of 67 semistructured interviews were originally conducted to explore experiences seeking related support in the Canadian Armed Forces (CAF). A secondary analysis revealed descriptions of interpersonal and institutional betrayal, which damaged their trust and regard for the organization and weakened organizational commitment and connection. Participants framed these impacts in relation to their peers, their leaders, and the organization more broadly, demonstrating that harm from poor organizational responses destabilizes the fundamental bonds that support military cohesion on multiple levels. These findings provide insight into the subjective experience of betrayal associated with sexual misconduct and highlight how organizational responses can substantially mitigate or exacerbate this harm.

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.

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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.060
Threshold uncertainty score0.492

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.068
GPT teacher head0.322
Teacher spread0.254 · 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