Development of a strategic plan for food security and safety in the Inuvialuit Settlement Region, Canada
Bibliographic record
Abstract
BACKGROUND: Current social and environmental changes in the Arctic challenge the health and well-being of its residents. Developing evidence-informed adaptive measures in response to these changes is a priority for communities, governments and researchers. OBJECTIVES: To develop strategic planning to promote food security and food safety in the Inuvialuit Settlement Region (ISR), Northwest Territories (NWT), Canada. DESIGN: A qualitative study using group discussions during a workshop. METHODS: A regional workshop gathered Inuit organizations and community representatives, university-based researchers from the Inuit Health Survey (IHS) and NWT governmental organizations. Discussions were structured around the findings from the IHS. For each key area, programs and activities were identified and prioritized by group discussion and voting. RESULTS: The working group developed a vision for future research and intervention, which is to empower communities to promote health, well-being and environmental sustainability in the ISR. The group elaborated missions for the region that address the following issues: (a) capacity building within communities; (b) promotion of the use of traditional foods to address food security; (c) research to better understand the linkages between diseases and contaminants in traditional foods, market foods and lifestyle choices; (d) and promotion of affordable housing. Five programs to address each key area were developed as follows: harvest support and traditional food sharing; education and promotion; governance and policy; research; and housing. Concrete activities were identified to guide future research and intervention projects. CONCLUSIONS: The results of the planning workshop provide a blueprint for future research and intervention projects.
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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 | 0.007 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.013 | 0.002 |
| Scholarly communication | 0.006 | 0.001 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".