The Development and Implementation of a Type 2 Diabetes Prevention Program for Youth in the Algonquin Community of Rapid Lake, Quebec
Bibliographic record
Abstract
The Canadian Aboriginal population has experienced a recent increase in chronic diseases. Type 2 diabetes prevalence rates have been recorded to be 3–5 times greater in Aboriginal populations than in non-Aboriginal populations. Childhood obesity, one of the most significant modifiable risk factors for developing type 2 diabetes, is often preventable with healthy lifestyle choices including exercise and diet. The main goal of this study was to develop and implement a locally and culturally adapted diabetes prevention program for youth in Rapid Lake, an Algonquin community in Quebec, Canada. Using focused ethnography and participatory research principles, the study progressed in four phases. Data collection involved interviews, focus groups, and observations. Thematic analysis was iterative. Findings include three main themes: 1) There was a contradiction between adult assumptions about what youth knew and what youth really knew about diabetes; 2) youth were highly receptive to interactive programming; and 3) youth took on the role of teacher for adult community members. Challenges and rewards to program development were also identified. The participatory approach employed during this project resulted in local Aboriginal youth and community worker empowerment, and will hopefully ensure the continuation of primary prevention diabetes program development and implementation within the community.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".