MétaCan
Menu
Back to cohort
Record W4406244495 · doi:10.1155/hbe2/9091296

Rape Myth Acceptance in the Digital Age: The Effects of Using Dating Apps and the Moderation Role of Gender

2025· article· en· W4406244495 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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueHuman Behavior and Emerging Technologies · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicSexual Assault and Victimization Studies
Canadian institutionsnot available
Fundersnot available
KeywordsModerationPsychologyPsychological interventionSample (material)MythologySocial psychologyDevelopmental psychology

Abstract

fetched live from OpenAlex

Rape myth acceptance (RMA) is a crucial predictor of rape proclivity. It has been extensively analyzed for its gender differences to aid in designing clinical interventions and health programs. Although it is well known that males generally exhibit higher levels of RMA than females, the impact of digital devices, the Internet, and dating apps on RMA and how this impact differs between genders remain understudied. This study addresses these gaps by examining a sample of 647 Chinese‐speaking college students in Canada. The findings indicate that the use of dating apps is positively associated with higher RMA; male students exhibited greater RMA levels than female students; and gender moderates the impact of dating app usage, with a more elevated effect on RMA observed in male students compared to female students. The study’s limitations are discussed, including the specificity of the sample (Chinese college students in Canada) and caution against generalizing to broader populations, along with the research and policy implications of the study.

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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.668
Threshold uncertainty score0.516

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 studies0.0010.001
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 head0.039
GPT teacher head0.354
Teacher spread0.314 · 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