BARRIERS TO REPORTING SEXUAL VIOLENCE IN HIGHER EDUCATION: POWER DYNAMICS AND ANTICIPATED COSTS
Bibliographic record
Abstract
Campus sexual victimization is associated with multiple physical and psychological consequences.It can affect the ability to pursue academic or professional activities at the university and foster feelings of institutional betrayal towards the university.The use of university services can sometimes help reduce negative consequences associated with sexual victimization.However, very few victims disclose sexual violence and use available resources in their institution.Studies that have explored reporting barriers have mostly been conducted on undergraduate students' samples.They also generally lack an intersectional perspective on violence and power relations, which acknowledges individuals' overlapping political and social identities.We conducted a mixed methods study in Quebec to explore the reasons behind the choice to not report sexual violence to university authorities or resources.First, we analyzed 88 testimonies of individuals who had experienced sexual violence and had not disclosed the situation to their institution.Second, we used a sample of 202 university community members who had been sexually victimized and had not reported it to conduct quantitative analyses.The results revealed a tendency to minimize the acts of violence, a negative perception of the institutional response and various fears of reprisals (e.g., social, professional, or academic repercussions).These findings allow us to reflect on the importance of fears for oneself and others, the assessment of anticipated costs and the potential benefits of disclosure, and the influence of power dynamics.Results can raise awareness among those likely to receive a report and, if necessary, to initiate appropriate institutional actions.The study confirms the need for awareness-raising messages that could improve victims' trust in academic institutions.
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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 | 0.003 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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.
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".