Participatory Methods for Inuit Public Health Promotion and Program Evaluation in Nunatsiavut, Canada
Bibliographic record
Abstract
Engaging stakeholders is crucial for health promotion and program evaluations; however, understanding how to best engage stakeholders is less clear, especially within Indigenous communities. This thesis research used participatory methods to: (1) co-develop a whiteboard video as a public health promotion tool in Rigolet, Nunatsiavut, and (2) develop and validate an evaluation framework for Inuit public health initiatives in Nunatsiavut, Labrador. Data were collected through interactive workshops, community events, interviews, focus-group discussions, and surveys. Results indicated the whiteboard video was an engaging medium for sharing public health messaging due to incorporation of contextually relevant elements. Inuit participants identified four foundational evaluation framework components to conduct appropriate evaluations, including: (1) community engagement, (2) collaborative evaluation development, (3) tailored evaluation data collection, and (4) evaluation scope. This research illustrates stakeholder participation is critical to develop public health initiatives including their evaluations in Nunatsiavut, Labrador and should be considered in other Indigenous communities.
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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 | 0.137 | 0.070 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.018 | 0.006 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.004 | 0.008 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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".