INDIGENOUS KNOWLEDGE, SOCIAL RELATIONSHIPS AND HEALTH: COMMUNITY-BASED PARTICIPATORY RESEARCH WITH ANISHINABE YOUTH AT PIC RIVER FIRST NATION
Bibliographic record
Abstract
Canada’s First Nations youth endure a disproportionate burden of health inequalities. While patterns of First Nation’s youth health point to distinctly social causes (e.g., lacking social support, violence and addiction), research has not adequately explored how the quality of local social environments influence First Nations youth health. Drawing from 19 in-depth interviews with Anishinabe youth, this community-based project utilized an Indigenous Knowledge framework to explore youth perceptions of health, social relationships, and the ways they interact. This research centred around four main objectives including: 1) understanding how Anishinabe youth define health & well-being; 2) exploring youth perceptions of social relationships; 3) examining how social relationships influence health; and, 4) understanding how culture shapes health. Findings suggest that youth definitions of health differ across individual, family and community levels. Youth perceive social relationships as fundamental for the provision of social support, and that good relationships influence healthy behaviours (e.g. youth participation in ceremonies). Over time, it appears that loss of Indigenous Knowledge figures strongly in the declining relationship between health and social relationships of youth (e.g. changing ways of interacting). Despite the loss of knowledge and changing lifestyles of the community however, youth spoke about meaningful connections to the land, and they identified the importance of cultural teachings related to Indigenous knowledge (e.g., moral values such as respect for land/elders) in their everyday lives, social relationships, and health behaviours.
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 | 0.005 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.017 | 0.003 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 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".