‘This is what's going to heal our kids’: bringing the Sexy Health Carnival into Indigenous cultural gatherings
Bibliographic record
Abstract
The Sexy Health Carnival is a peer-developed Indigenous health initiative designed to provide culturally-relevant health information for Indigenous youth. The Carnival takes a strengths-based, holistic approach to address topics in fun and interactive ways. As part of the study described here, the Carnival was taken to 6 First Nations, 3 Métis, and 2 Inuit cultural gatherings in Canada. Due to complex histories of colonialism, bringing sexual health and harm reduction programming to cultural gatherings remains controversial. Interviews were conducted with 10 Carnival leaders. Transcripts were transcribed verbatim and inductively coded using NVivo. There was strong support for bringing the Carnival into cultural spaces because (a) teachings on health, sexuality, and reproduction are sacred and belong in cultural spaces, (b) doing so was requested by the communities themselves, (c) the Carnival holds potential to challenge harmful stigma, and (d) the Carnival supported a peer-led initiative. Facilitators also described several challenges encountered including (a) resistance to discussing stigmatised subjects, (b) issues of safety and (c) the intensive physical and emotional demands of the Carnival's implementation. The Carnival aids in re-imagining what culturally safe health promotion can look like when it is led by and for Indigenous youth. While the Carnival contributes to Indigenous cultural resilience and resurgence, further support is needed to enhance sustainably.
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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 | 0.010 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.029 | 0.014 |
| Scholarly communication | 0.007 | 0.007 |
| Open science | 0.003 | 0.013 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.006 | 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".