Exploring Healthy Eating Perceptions, Barriers, and Facilitators among Urban Indigenous Peoples in Saskatchewan
Bibliographic record
Abstract
Urban Indigenous populations encounter distinctive challenges in maintaining traditional dietary practices, compounded by the complexities of socio-economic and environmental factors and the modern urban lifestyle. This qualitative study explores the perceptions of healthy eating, along with the facilitators and barriers to such practices, among urban Indigenous peoples in Saskatoon, Regina, and Prince Albert. Through virtual interviews, we engage 14 participants from these cities. Utilizing NVivo for thematic coding, we apply inductive thematic analysis to reveal relevant themes. The study highlights a preference for nutrient-rich, natural, and minimally processed foods, with a significant emphasis on incorporating traditional Indigenous foods into diets. These preferences are deeply entwined with cultural identity and underscore the importance of traditional foods in maintaining cultural heritage and promoting well-being. Despite the intrinsic value of these traditional foods, participants face several barriers to healthy eating, including economic constraints, limited access to traditional foods, and the psychological impacts of historical trauma. Nevertheless, facilitators such as community and family support, engagement in traditional food practices, and a growing awareness of nutritional knowledge are identified as being crucial in supporting healthy dietary choices. This research underscores the complex interplay of cultural, economic, and environmental factors in shaping the dietary practices of urban Indigenous peoples.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".