Through the lens of our cameras: children's lived experience with food security in a <scp>C</scp>anadian <scp>I</scp>ndigenous <scp>c</scp>ommunity
Bibliographic record
Abstract
BACKGROUND: The related issues of food security and obesity among North American Indigenous children are serious public health concerns. This community-based participatory study sought to gain deeper understanding of young First Nation children's lived experience with food and to learn, from their perspective, about food security issues in their community. METHODS: In this Photovoice investigation 26 young children attending a rural reserve school in Canada were asked to take photographs of the food they ate. Nine high school students from the same school were trained as co-researchers: they interviewed the younger students, helped identify emerging themes and contributed to knowledge translation. Data analysis incorporated conventional content analysis, grounded theory's constant-comparative method, and examination of photos and texts. RESULTS: Five primary findings emerged from photographs and interviews: (1) children had a dualistic understanding of healthy vs. unhealthy foods; (2) packaged, quick-preparation foods played a dominant role in children's everyday food experiences; (3) families were critical to children's food-related experiences; (4) although traditional foods are viewed as central to Aboriginal health, few were depicted in the photographs; and (5) photos do not tell the whole story - despite the smaller numbers of fruits and vegetables in photos, children like to eat these foods when they are available at home. CONCLUSIONS: The study improved understanding of children's everyday food-related experiences, provided insight into community food security, and demonstrated the contribution of children and youth as experts on their lives and matters affecting them. A photobook representing findings provided a rich, visual tool for communicating the food-related experiences of children and messages about healthy eating within the school and to community members and leaders. Intervention efforts can build on participants' understanding of healthy versus unhealthy foods and on the critical role of family for healthy eating.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.014 | 0.011 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.004 |
| 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".