MétaCan
Menu
Back to cohort
Record W2277446785 · doi:10.7205/milmed-d-14-00447

Intimate Partner Violence in the Canadian Armed Forces: The Role of Family Stress and Its Impact on Well-Being

2015· article· en· W2277446785 on OpenAlexafffundabout
Alla Skomorovsky, Filsan Hujaleh, Stefan Wolejszo

Bibliographic record

VenueMilitary Medicine · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicIntimate Partner and Family Violence
Canadian institutionsDepartment of National Defence
FundersMinistère de la Défense Nationale
KeywordsStressorPsychologyDomestic violenceMilitary personnelInterpersonal communicationPoison controlInterpersonal relationshipOccupational safety and healthSuicide preventionInjury preventionSocial psychologyClinical psychologyMedicineMedical emergencyPolitical science

Abstract

fetched live from OpenAlex

Unique demands of military life (e.g., deployment) can have a significant impact on family life. Although most families cope effectively with military life stressors, some may have difficulty adjusting, experiencing marital conflicts, and violence. Evidence suggests that unmanaged occupational demands may create family stress by interfering with efforts to fulfill family duties. This study examined the effects of work-family conflict and marital satisfaction on intimate violence experienced by Canadian Armed Forces members, and the impact of such violence on their psychological well-being (N = 525). Regression analyses showed that both work-family conflict and marital satisfaction were unique and significant predictors of emotional and physical violence experienced by Canadian Armed Forces members. Moreover, bootstrapping analyses demonstrated that marital satisfaction partially mediated the relationship between work-family and family-work conflicts and intimate partner violence. The results point to the importance of examining the interrelationship between family stress and occupational stressors when exploring interpersonal violence and its psychological impact on military personnel.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.406
Threshold uncertainty score0.785

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.028
GPT teacher head0.338
Teacher spread0.310 · 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 designObservational
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

Citations18
Published2015
Admission routes3
Has abstractyes

Explore more

Same venueMilitary MedicineSame topicIntimate Partner and Family ViolenceFrench-language works237,207