Understanding disclosures of sexual violence in Canadian postsecondary institutions: a scoping review protocol
Bibliographic record
Abstract
INTRODUCTION: Sexual violence remains a critical and under-reported issue in postsecondary institutions, impacting student health, well-being and academic outcomes. In Canada, over 90% of incidents are not disclosed to institutions; similar patterns are observed in the USA. Despite growing awareness of the issue, no comprehensive review has synthesised how Canadian evidence understands the disclosure of sexual violence in postsecondary settings. This scoping review addresses the question: 'what are the perceptions and experiences of disclosure processes of sexual violence in Canadian postsecondary institutions?'. The review will: (1) characterise existing perceptions of disclosure within Canadian postsecondary sexual violence evidence; (2) identify key sources and perspectives informing the evidence; (3) synthesise reported impacts of disclosure for students and (4) highlight gaps and research priorities to support the development of more effective, equitable and trauma-informed disclosure processes. The findings will inform student survivor-centred policies and practices in Canadian postsecondary institutions. METHODS AND ANALYSIS: This review follows Arksey and O'Malley's five-step scoping review framework, incorporating enhancements by Levac and colleagues. The methodology includes: (1) identifying relevant evidence through searches in PsycINFO, ERIC, Sociological Abstracts, Criminal Justice Abstracts and SCOPUS; (2) iterative evidence selection by two independent reviewers; (3) data extraction, abstract screening and full text review; (4) synthesising findings using reflexive thematic analysis guided by Braun and Clarke's framework and (5) summarising and reporting the results. Eligible sources include peer-reviewed and grey evidence published from December 2014 onward that focus on sexual violence in Canadian postsecondary contexts. ETHICS AND DISSEMINATION : Ethical approval is not required as this study reviews existing literature. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews checklist will be used to guide translation of findings. Results will be disseminated through peer-reviewed journals and presented at conferences via abstract and presentation.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.091 | 0.094 |
| Meta-epidemiology (narrow) | 0.004 | 0.005 |
| Meta-epidemiology (broad) | 0.009 | 0.010 |
| Bibliometrics | 0.024 | 0.021 |
| Science and technology studies | 0.007 | 0.006 |
| Scholarly communication | 0.009 | 0.006 |
| Open science | 0.006 | 0.006 |
| Research integrity | 0.007 | 0.005 |
| Insufficient payload (model declined to judge) | 0.049 | 0.008 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".