Grounding Our Meals on Wheels Program in Community Voice: Exploring Food Practices and Perceived Wholistic Health in Wahta Mohawk Territory
Bibliographic record
Abstract
Introduction: Food practices and wholistic health are two concepts that have been altered by the colonization of Indigenous peoples living in Canada. Research literature exploring the relationship between current food practices and wholistic health among Indigenous older adults remains sparse. Purpose: To address the community-identified need of understanding how the community Meals on Wheels (MOW) program can nourish the perceived wholistic health of the older adults it serves on-reserve in Wahta Mohawk Territory. Methods: A community-based participatory research (CBPR) approach was adopted in harmony with an Indigenous epistemological stance of the Two Row paradigm and guidance from Wahta’s Community Health and Cultural Healing principles. Storytelling sessions were held via telephone with 10 older adults living in Wahta who subscribe to the MOW program. Data Analysis: A reflexive thematic analysis was undertaken to identify emerging themes from the data following Braun and Clarke’s (2021) steps to a reflexive thematic analysis. Results: From the storytelling sessions, four prominent themes emerged: 'Evolving Food Practices in Wahta', 'With Age Come Changes in Life', 'Sourcing Food Locally in Wahta' and 'Continuing to Gather with Food' and their related sub-themes. Discussion: A community-based conceptual model grounded in the resultant themes is presented and discussed as symbol of a community-grounded MOW program that nourishes the perceived wholistic health of the older adults in Wahta Mohawk Territory.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.009 | 0.004 |
| Scholarly communication | 0.002 | 0.002 |
| 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".