Indigenous Land-Based Approaches to Well-Being: The Amisk (Beaver) Harvesting Program in Subarctic Ontario, Canada
Bibliographic record
Abstract
<p>The act of decolonizing knowledge systems involves recovering and renewing traditional, non-commodified cultural patterns, such as the sustenance of intergenerational relationships and traditional practices. A decline in beaver harvesting, which was once an integral part of the <em>Omushkego</em> Cree culture, has resulted in an overabundance of beavers and dams, which has negatively affected communities by increasing the local flooding events and impacting the water quality. The aim of the <em>Amisk</em> (beaver) program was to reconnect the Elders and youth to revitalize traditional on-the-land activities and, in the present case, beaver harvesting and associated activities within the community. The program and evaluation were built using a two-eyed seeing (<em>Etuaptmumk</em>) and community-based participatory research approach. Salivary cortisol, a biomedical measure of stress, was collected before and after participation in the program. Photovoice, along with semi-directed interviews, were employed to identify the key elements of well-being from a First Nations' perspective. For the beaver harvesting activities, the changes observed in the cortisol concentrations were not statistically significant (<em>p</em> = 0.094). However, the act of beaver dam removal was associated with a statistically significant increase in the post-participation cortisol concentration (<em>p</em> = 0.021). It was noteworthy that increased stress during the removal of the beaver dams-as indicated by the elevated post-activity cortisol levels-were not reflected in a decrease in the qualitative measures (semi-directed interviews and photovoice) of well-being from an Indigenous perspective. In fact, there was a noted increase in the subjective well-being of the participants, which highlights the importance of multiple perspectives when assessing well-being, especially in Indigenous peoples. However, the cortisol findings of the present pilot project need to be interpreted with caution, due to the limited sample sizes.</p>
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".