Sandy Lake Health and Diabetes Project: A Community-Based Intervention Targeting Type 2 Diabetes and Its Risk Factors in a First Nations Community
Bibliographic record
Abstract
The Sandy Lake Health and Diabetes Project (SLHDP) was initiated in 1991 as a partnership between Sandy Lake First Nation and researchers interested in addressing the high rates of type 2 diabetes mellitus (T2DM) in the community. Following the expressed wishes of the community, the SLHDP has encompassed a variety of community-wide interventions and activities including: community surveys to document T2DM prevalence and risk factors, the Northern Store program aimed at increasing the availability and knowledge of healthy food options, a home visit program for the prevention and management of T2DM, a local diabetes radio show, a school diabetes curriculum for grades 3 and 4, a community-wide walking trail to encourage increased physical activity, youth diabetes summer camps, and a variety of community events focusing on nutrition and physical activity. Over the 22 year existence of the SLHDP, the community has taken ownership of the program and activities have evolved in alignment with community needs and priorities. This paper discusses the history, implementation, evaluation, and outcomes of the SLHDP and describes its sustainability. The SLHDP is a model of culturally appropriate participatory research that is iterative, with reciprocal capacity building for both key community stakeholders and academic partners.
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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 | 0.000 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.004 |
| 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".