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PW 0417 A three-step gendered latent class analysis on dating victimization profiles: correlates with family and peer contextual risk factors, injuries and mental health

2018· article· en· W2893782506 on OpenAlex

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.

Bibliographic record

VenueAbstracts · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicIntimate Partner and Family Violence
Canadian institutionsUniversité LavalUniversité du Québec à Montréal
Fundersnot available
KeywordsLatent class modelMental healthPsychologyClass (philosophy)Clinical psychologyDevelopmental psychologyPsychiatryComputer scienceMachine learningArtificial intelligence

Abstract

fetched live from OpenAlex

The purpose of this study was to identify patterns of teen dating victimization among boys and girls and examine their association with family and peer contextual risk factors and injuries and mental health indicators. As part of the population-based <i>Youths’ Romantic Relationships Project</i>, 8 230 high school students were questioned about their victimization experiences. Latent class analysis was used to identify classes for both girls and boys. Latent class analysis identified a best fitting model of three classes for girls: Low victimization (61% of girls), Sexual and psychological violence (27%) and Multiple victimization (12%). Similarly for boys, three classes were identified including a Low victimization (84% of boys), a Multiple victimization (9%) and an Unwanted sexual contacts and psychological violence (7%). Associations between class membership and family and peer contextual risk factors and mental health indicators revealed more distinctive features among classes for girls than for boys. Confirming our hypothesis, both genders in the Multiple violence class reported experiencing the most injuries (e.g., bruise or cut, pain the next day or need of a medical appointment). A history of childhood interpersonal traumas was significantly related to classes of dating victimization, suggesting that different forms of child abuse (neglect, exposure to interparental violence, physical or sexual abuse) are associated with a heightened risk of revictimization in the context of their first romantic relationships. Our findings suggest that child sexual abuse may act as a specific vulnerability factor for more pervasive forms of TDV for girls. The findings highlight the utility of a person-oriented approach to enhance our understanding of the diversity of victimization experiences in the context of teen romantic relationships. Results also underscore the importance of tailoring prevention efforts to efficiently tackle teen dating violence and the relevance of trauma-informed practices.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.029
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 studies0.0010.000
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 head0.027
GPT teacher head0.308
Teacher spread0.281 · 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