Who’s at the table: an exploration of community-based food security initiatives and structures in a north-central Canadian context
Bibliographic record
Abstract
Abstract This article examines food security initiatives and actors specific to a rural, remote and northern Canadian community, a context found throughout the world. Using a ‘snowball technique’ to identify experts and practitioners in local food security, we employed qualitative engagement methods to map initiatives, actors and gaps in regional food security. We identified concerns around the ability of the region to be food secure; we also found a lack of cross-sector communication and planning, challenges with a small group of committed actors facing isolation and burnout and a need to more broadly engage the community and political entities with limited awareness of rural and remote cultures and concerns. Facilitating better collaborations across multiple food security-related activities while honouring current and supporting current initiatives could enable those who know their communities, to address food insecurity collectively and collaboratively in a rural, remote and northern context.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.046 | 0.015 |
| Scholarly communication | 0.010 | 0.003 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 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".