Exploring the Perceptions of and Experiences with Traditional Foods among First Nations Female Youth: A Participatory Photovoice Study
Bibliographic record
Abstract
Traditional foods contribute to the health and well-being of Indigenous Peoples. Many Indigenous Peoples within Canada have expressed a desire to consume more traditional foods; however, there are a number of barriers to doing so. Southern and urban communities face unique challenges associated with traditional food consumption. To address these concerns and build on community interests in a Haudenosaunee community in Southern Ontario, a participatory research project was initiated. This community-based study utilized Photovoice methodology to explore the perceptions of and experiences with traditional foods among local youth. Participants ranging in age from 15–22 (n = 5) took photos of their local food environments, including locations where foods were acquired, consumed, prepared, or shared during two seasons of the year. Semi-structured interviews were conducted to collect participants’ stories behind 8–10 self-selected images. A thematic analysis was subsequently utilized to identify patterns and themes illustrated by the photos and interview content. The youth conveyed contextual understandings of traditional foods and a preference for these items, despite their limited consumption, preparation or harvesting of these foods. The youth also identified the important influence of families and communities on their individual perceptions and experiences with traditional foods. Recommendations to reduce barriers to traditional food choices among youth are made.
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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 | 0.005 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".