HIV risk, systemic inequities, and Aboriginal youth: widening the circle for HIV prevention programming.
Bibliographic record
Abstract
BACKGROUND: In Canada, Aboriginal people are overrepresented in the HIV epidemic and infected at a younger age than non-Aboriginal people. This paper discusses some of the ways Aboriginal youth in Toronto understand HIV/AIDS risk and the relevance of their comments for HIV prevention education. This research is part of a larger study conducted with Ontario youth through the Gendering Adolescent AIDS Prevention (GAAP) project. METHODS: We conducted 11 GAAP focus groups with Ontario youth. This paper focuses primarily on the four groups of Aboriginal youth. A modified grounded theory approach guided analyses. Data were coded using Nud*ist qualitative data management software. FINDINGS: Aboriginal youth were more aware of HIV/AIDS and the structural inequities that contribute to risk than their non-Aboriginal counterparts. In addition, they were the only group to talk about colonialism in the context of HIV in their community. Aboriginal youth were, however, more likely to hold a fatalistic view of their future and to blame their own community for high infection rates. INTERPRETATION: We argue for incorporating structural factors of risk, including the legacy of colonialism, in HIV prevention programs for all youth. This may help to eradicate the stigma and self-blame that negatively impact on Aboriginal youth while allowing other youth populations to distance themselves from the disease.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.005 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".