Honouring the stories of student-survivors: trauma informed practice in post-secondary sexualized violence policy review
Bibliographic record
Abstract
Rape culture permeates the landscape of post-secondary education throughout Canada. In recent years, student-survivors and advocates have been influential in the creation of provincial legislation mandating colleges and universities to develop stand-alone sexualized violence policies. In British Columbia these policies are to be institutionally reviewed every three years, but there is no clear legislative direction as to how these reviews should be conducted, or how survivors and advocates voices will be included. My thesis examines the impacts of campus sexualized violence and the integral role that student-survivors and their stories play in transforming rape culture. Through the voices of nine University of Victoria student-survivors and five community-based service providers, I demonstrate that student-survivors and those who support them act as both change-agents and subject matter-experts regarding campus rape culture; as such, their inclusion in policy development and review is essential. However, my thesis also demonstrates that student-survivors and advocates navigate an increasingly corporatized post-secondary environment, whereby the stories of student-survivors are considered dangerous to the campus brand and reputation. In taking seriously the trauma associated with sexualized violence and the consequences of the corporate campus, my thesis offers a Trauma Informed Consultation Guideline. This guideline provides a trauma-informed and community based approach to consulting student-survivors in policy review with the intention of creating safer opportunities for story to inform future policy directions.
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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 | 0.132 | 0.332 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.010 | 0.011 |
| Science and technology studies | 0.008 | 0.008 |
| Scholarly communication | 0.016 | 0.012 |
| Open science | 0.007 | 0.012 |
| Research integrity | 0.011 | 0.010 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".