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Record W2966409791 · doi:10.1080/17525098.2019.1635708

Physical assault perpetration and victimisation among Chinese university students

2019· article· en· W2966409791 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

VenueChina Journal of Social Work · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicSexual Assault and Victimization Studies
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsVictimisationPsychologyCriminologyHuman factors and ergonomicsPoison controlMedical emergencyMedicine

Abstract

fetched live from OpenAlex

This study applies the ecological conceptual model in examining the rates and risk factors of both severe and minor physical assault perpetration and victimisation among university students in Hong Kong, Taiwan and Mainland China. Data were from the International Dating Violence Study. The analysis employed a generalised mixed effect model. Findings showed the rates of minor physical assault perpetration was 34.1% among the participants; minor victimisation was 16.2%; severe perpetration was 23.9%; and, severe physical assault victimisation was 12.5%. Female students were more likely to report minor and severe physical assault perpetration compared to males [aOR = 2.48 (1.80, 3.43), and 2.89 (1.83, 4.56), respectively, p values<0.05]. Controlling for all variables, if sexual relations were part of the dating relationship, the odds of minor and severe violence perpetration and victimisation were 1.98 and 2.23 (p values<0.05). Good anger management was associated with a 60 to 70% decrease in the odds of physical assault.

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)0.000
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 score0.079
Threshold uncertainty score0.578

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.009
GPT teacher head0.302
Teacher spread0.293 · 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