Supporting food security for Indigenous families through the restoration of Indigenous foodways
Bibliographic record
Abstract
Indigenous families are overrepresented among those within Canada who experience food insecurity. Studies have largely focused on northern populations, with less attention paid to southern and urban communities, including the social, cultural, and geographic processes that challenge food security. In this study, we present findings from a decade‐long community‐based study with the Southwest Ontario Aboriginal Health Access Centre (London, Ontario) to examine family perspectives related to the social determinants of food security. These topics were explored through qualitative interviews (n = 25) and focus groups (n = 2) with First Nation mothers with young children from the city of London, and a nearby reserve community. Interviewees from both geographies identified a number of socio‐economic challenges including household income and transportation. However, some interviewees also shed light on barriers to healthy eating unique to these Indigenous contexts including access issues such as a lack of grocery stores on‐reserve; loss of knowledge related to the utilization of traditional foods; and the erosion of community, familial, and social supports. Resolving these unique determinants of food security for urban and reserve‐based First Nation families will require a range of economic and culturally specific interventions, particularly those that support development and uptake of Indigenous foodways.
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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 | 0.001 | 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 | 0.011 | 0.005 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".