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Record W4408071622 · doi:10.1177/0095327x251316266

Sexual Misconduct in the Military: The Impact of Situational Factors on Bystander Intervention Strategies

2025· article· en· W4408071622 on OpenAlexaffabout
Sara Rubenfeld, Manon Mireille LeBlanc, Deanna Messervey, Glen T. Howell, Simon A. Houle

Bibliographic record

VenueArmed Forces & Society · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicSexual Assault and Victimization Studies
Canadian institutionsUniversité du Québec à Trois-RivièresStatistics CanadaDepartment of National Defence
Fundersnot available
KeywordsBystander effectSexual misconductPsychological interventionSituational ethicsIntervention (counseling)PsychologyMisconductWarrantSocial psychologyCriminologyPolitical sciencePsychiatryBusinessLaw

Abstract

fetched live from OpenAlex

Intervening is frequently encouraged to prevent or respond to sexual misconduct. However, due to the characteristics of military organizations (e.g., hierarchical structure), intervening may be challenging in military contexts. The aim of this study is to examine situational factors present in militaries (e.g., bystander’s rank relative to the perpetrator’s) that may impact the use of direct or indirect intervention strategies. A sample of Canadian Armed Forces members completed a scenario-based experiment. The results revealed that rank of the bystander, gender of the target, and severity of the situation impacted the use of direct intervention strategies, and the bystander’s rank relative to the perpetrator’s, gender of the target, and severity of the situation impacted the use of indirect intervention strategies. These findings highlight where direct and indirect interventions are unlikely to occur and situations that warrant greater focus in training programs and in communications from leadership.

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)0.000
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 score0.058
Threshold uncertainty score0.999

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 head0.051
GPT teacher head0.394
Teacher spread0.344 · 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

Citations1
Published2025
Admission routes2
Has abstractyes

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