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Record W2143540452 · doi:10.1177/0886260507309340

Violence in Young Adolescents' Relationships

2007· article· en· W2143540452 on OpenAlexaff
Wendy Josephson, Jocelyn Proulx

Bibliographic record

VenueJournal of Interpersonal Violence · 2007
Typearticle
Languageen
FieldSocial Sciences
TopicIntimate Partner and Family Violence
Canadian institutionsUniversity of ManitobaUniversity of Winnipeg
Fundersnot available
KeywordsPoison controlHuman factors and ergonomicsSuicide preventionInjury preventionOccupational safety and healthMedical emergencyPsychologyMedicine

Abstract

fetched live from OpenAlex

A structural equation model based on social cognitive theory was used to predict relationship violence from young adolescents' knowledge, self-efficacy, attitudes, and alternative conflict strategies (n = 143 male and 147 female grade 7-9 students). A direct causal effect was supported for violence-tolerant attitudes and psychologically aggressive (escalation/blame) strategies on physical violence against dating partners and friends. Knowledge and self-efficacy contributed to using reasoning-based strategies, but this reduced violence only in boys' friendships. Knowledge reduced violence-tolerant attitudes, thus reducing escalation/ blame and physical violence. Attitudes toward male and female dating violence (ATMDV and ATFDV) were indicators of general attitudes toward violence among non-dating students but ATFDV affected physical violence and ATMDV affected psychological aggression for both dating boys and girls.

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)0.001
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.014
Threshold uncertainty score0.027

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.328
Teacher spread0.301 · 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 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

Citations66
Published2007
Admission routes1
Has abstractyes

Explore more

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