Power and possibility: an intersectional perspective of campus sexual violence disclosure
Bibliographic record
Abstract
Sexual violence on higher education campuses represents a global public health crisis that threatens students' safety, well-being, and academic success. Despite increasing awareness and available supports, most students who experience sexual violence do not disclose their experiences. This perspective article critically explores the disclosure process through an intersectional lens, revealing how institutional barriers, systemic oppressions including racism, ableism, and transphobia, and power structures shape students' decisions to seek support after sexual violence. Drawing on firsthand insights as a social worker and researcher in a Canadian campus sexual violence support office, I explore the often-overlooked risk of further harm during or following disclosure. The discussion provides a globally relevant perspective on the shared challenges student survivors face across various cultural and institutional contexts. I challenge one-size-fits-all response models and advocate for transformative, student-centered approaches that prioritize student survivor choice, justice, and equitable care. By exploring the systemic impacts of disclosure and its nuanced complexities, this perspective contributes to global conversations on campus sexual violence and identifies critical gaps in research. It demonstrates how intersectional frameworks are essential to developing ethical, responsive, and empowering practices that reduce harm and uphold student survivors' agency. Ultimately, it calls for a fundamental reimagining of support systems that honor diverse student experiences, validate both disclosure and non-disclosure, and confront the realities of sexual violence in academic environments.
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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 | 0.011 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.023 | 0.082 |
| Scholarly communication | 0.024 | 0.021 |
| Open science | 0.003 | 0.026 |
| Research integrity | 0.005 | 0.012 |
| 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".