Process Evaluation of a Cooking Circle Program in the Arctic: Developing the Mukluk Logic Model and Identifying Key Enablers and Barriers for Program Implementation
Bibliographic record
Abstract
This study investigates the implementation of the Nutrition North Canada (NNC)-funded cooking circle program in the Inuvialuit (Inuit) hamlet of Paulatuk, Northwest Territories. The objectives of this study are to co-develop a culturally relevant logic model and to conduct a process evaluation of program implementation to identify and assess key enablers and barriers. The co-developed Mukluk Logic Model played an instrumental role in the conceptualization of the process evaluation. The process evaluation results indicated that the long-standing sustainability of the program is related to the consistency of program funding, engaging facilitation practices, and creative utilization of the multi-purpose space for program activities. However, significant barriers limit program sustainability. These include funding amounts and distribution, space and equipment limitations, and human resources challenges. This study illustrates the utility of qualitative process evaluation research in a Canadian Arctic community context and generates important place-based knowledge and insights to better support northern community-based food preparation programs.
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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 | 0.055 | 0.037 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".