Community governance of the Kahnawake Schools Diabetes Prevention Project, Kahnawake Territory, Mohawk Nation, Canada
Bibliographic record
Abstract
Health promotion emphasizes the importance of community ownership in the governance of community-based programmes, yet little research has been conducted in this area. This study examined perceptions of community ownership among project partners taking responsibility for decision-making related to the Kahnawake Schools Diabetes Prevention Project (KSDPP). Project partners were surveyed cross-sectionally at 18 months (T1) and 60 months (T2) into the project. The perceived influence of each project partner was assessed at T1 and T2 for three domains: (i) KSDPP activities; (ii) KSDPP operations; and (iii) Community Advisory Board (CAB) activities. Project staff were perceived to have the greatest influence on KSDPP activities, KSDPP operations and CAB activities at both T1 and T2. High mean scores of perceived influence for CAB members and community researchers, however, suggests that project decision-making was a shared responsibility among multiple community partners. Although academic researcher influence was consistently low, they were satisfied with their level of influence. This was unlike community affiliates, who were less satisfied with their lower level of influence. In keeping with Kanien'kehaka (Mohawk) culture, the findings suggest a participatory democracy or shared decision-making as the primary mode of governance of KSDPP.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| 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".