“Be proactive not reactive”: Understanding gaps in student sexual consent education
Bibliographic record
Abstract
A growing number of universities are providing sexual violence prevention programs to students in recognizing the need for this programming. While universities favour programs on singular topics aimed at preventing sexual violence, scholars have argued that comprehensive sexual health education should begin prior to entering university to better ensure safer campus communities. Further, students have expressed unmet needs regarding the sexual health education they received prior to attending university. Therefore, the current study sought to explore gaps in sexual health education as identified by university students. Participants ( N = 444) were asked to describe the consent definition they were taught in high school and from their parents, and how the sexual health education they received could have been improved. An inductive thematic analysis was used to identify six themes from the data: back to consent education basics, you have the power to set boundaries, staying safe in sexual situations, take a sex-positive approach with sex education, wholistic education on consent-based relations, and practical recommendations for providing sex education. Findings highlight that participants desired a more wholistic approach to their sexual health education that included practical components on healthy sexuality. Notably, participants relayed how proper sexual health education may have prevented experiences of sexual violence they had. Thus, it is essential to continue exploring how best to provide comprehensive sexual health education to adolescents.
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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 | 0.066 | 0.083 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.016 | 0.027 |
| Scholarly communication | 0.012 | 0.021 |
| Open science | 0.004 | 0.017 |
| Research integrity | 0.006 | 0.009 |
| Insufficient payload (model declined to judge) | 0.003 | 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".