Student-Centered Evaluation Research of Quebec’s Bill 151 – \nAn Act to Prevent and Fight Sexual Violence in Higher Education Institutions
Bibliographic record
Abstract
In late 2017, Quebec passed Bill 151, An Act to prevent and fight sexual violence in higher education institutions, making it mandatory for universities and CEGEPs to adopt a sexual violence policy by January 1st, 2019. Conversely, student advocates expressed serious concern in relation to the lack of student consultation in the development and implementation of Bill 151. Currently, most research related to sexual violence in higher education focuses on university settings, offering minimal insight into the CEGEP sector. \n \nWith the aim of consulting students, and of reducing the knowledge gap, this student-centered research evaluated the sexual violence prevention measures and support services at a public English-speaking CEGEP on the island of Tiohtiá:ke/Montreal. The anonymous online survey asked students about their awareness and opinions of the sexual violence support services and prevention measures available on campus and solicited their suggestions for improvements. \n \nThe results showed that most students did not know how to access, nor had read their college’s sexual violence policy and procedures. Most respondents rated the prevention measures as ‘somewhat effective’ (48.2%), and the support services as ‘helpful’ (43.3%). However, students decidedly expressed the desire for a greater diversity of sexual violence prevention measures and support services on campus, as well as for more in-person interventions. The survey findings were further observed through the intersections of age, gender, sexual orientation and ethnicity. The differences in averages between dominant and marginalized groups were also checked for statistical significance through the application of t-tests.
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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 | 0.046 | 0.063 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.007 | 0.003 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".