“Because we have really unique art”: Decolonizing Research with Indigenous Youth Using the Arts
Bibliographic record
Abstract
Indigenous communities in Canada share a common history of colonial oppression. As a result, many Indigenous populations are disproportionately burdened with poor health outcomes, including HIV. Conventional public health approaches have not yet been successful in reversing this trend. For this study, a team of community- and university-based researchers came together to imagine new possibilities for health promotion with Indigenous youth. A strengths-based approach was taken that relied on using the energies and talents of Indigenous youth as a leadership resource. Art-making workshops were held in six different Indigenous communities across Canada in which youth could explore the links between community, culture, colonization, and HIV. Twenty artists and more than 85 youth participated in the workshops. Afterwards, youth participants reflected on their experiences in individual in-depth interviews. Youth participants viewed the process of making art as fun, participatory, and empowering; they felt that their art pieces instilled pride, conveyed information, raised awareness, and constituted a tangible achievement. Youth participants found that both the process and products of arts-based methods were important. Findings from this project support the notion that arts-based approaches to the development of HIV-prevention knowledge and Indigenous youth leadership are helping to involve a diverse cross-section of youth in a critical dialogue about health. Arts-based approaches represent one way to assist with decolonization for future generations.
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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 | 0.016 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.025 | 0.017 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".