Sexual health literacy and access to inclusive education: Investigating disparities between cisgender heterosexual and 2SLGBTQIA+ young adults
Bibliographic record
Abstract
Previous studies have assessed students’ perceived quality of school-based sexual health education (SHE); however, there is a paucity of research on sexual health literacy, especially involving 2SLGBTQIA+ participants. Many school-based programs teach sexual health from a heteronormative lens, which means that 2SLGBTQIA+ youth may not have their educational needs fully met. This study examined SHE experiences, sexual health literacy, sources of sexual health information, and engagement in safer sex practices among young adults (aged 16–24 years) who received SHE in Canada in middle and/or high school. A total of 913 participants were divided into two groups, sexual and gender minority (SGM; n = 392) versus cisgender heterosexual (CH; n = 518). SGM participants reported that the SHE they received was significantly less affirming and inclusive of their identity than CH participants. SGM participants used the internet as a source of information about sexual health significantly more than CH participants; however, the groups did not differ on the other sources. SGM participants scored significantly higher on the sexual health literacy questionnaire. SGM participants reported engaging in safer sex practices significantly more than CH participants for penile–anal intercourse; otherwise, the groups did not differ in safer sex practices. This research contributes to our understanding of the role of identity and SHE in sexual health literacy, which may inform curriculum standards and policies.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| 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".