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Record W2782556559 · doi:10.47678/cjhe.v47i2.187967

Sexual Violence on Religious Campuses

2017· article· en· W2782556559 on OpenAlexaffvenueabout
James R. Vanderwoerd, Albert Cheng

Bibliographic record

VenueCanadian Journal of Higher Education · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicSexual Assault and Victimization Studies
Canadian institutionsRedeemer University
Fundersnot available
KeywordsSexual violenceExploratory researchHigher educationPsychologyDemographyCriminologySocial psychologySociologyPolitical scienceSocial scienceLaw

Abstract

fetched live from OpenAlex

Religious colleges and universities make up a substantial segment of the higher education landscape in North America, but the incidence of sexual violence on these campuses remains understudied. This study estimates the incidence of sexual violence on independent Christian campuses using a sample of part-time and full-time undergraduate students (N = 668) from eight private Christian colleges in Ontario, Canada. Using two widely used measures of sexual violence enabled comparisons with studies of self-reported incidents at secular and public colleges and universities. The findings show that 18% of women at religious colleges reported experiencing unwanted sexual contact within the past year, compared to studies of self-reported rates on secular campuses ranging from 21.4% to 31.4%. Exploratory investigation of factors related to victimization suggests that religious colleges may provide a “moral community” that could reduce the risk of sexual violence.

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)0.000
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.821
Threshold uncertainty score0.356

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.001
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 head0.040
GPT teacher head0.369
Teacher spread0.328 · 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 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

Citations15
Published2017
Admission routes3
Has abstractyes

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