Strengthening Animal-Human Relationships as a Doorway to Indigenous Holistic Wellness
Bibliographic record
Abstract
Abstract One of the most devastating effects of colonization has been fragmented relations among humans and their more-than-human counterparts. Traditionally, Indigenous peoples positioned animals as equitable partners in interconnected human and more-than human networks, animated with spirit and the ability to act and communicate. Many Indigenous peoples continue to regard animals as sacred and utilize the gifts that they bestow in traditional healing settings. Indigenous understandings of interwoven and reciprocal social networks of human and more-than-human relations must be restored and supported in contemporary health settings in order to “do no further harm” and facilitate Indigenous peoples' healing journeys. Reconciliation across Western and Indigenous contexts requires learning to work together with the more-than-human world and developing ethical spaces for health research in which holistic wellness is appreciated and understood in the context of all our relations. In order to help (re)connect and strengthen human relations with the more-than-human world, a culturally adapted and locally refined animal-human relationship workshop was delivered in a rural Saskatchewan First Nation community where traditional Elders, adults, and youth participants shared stories about the role of animals for their healing and holistic wellness trajectories. The results revealed that animal-human relationships are physical and spiritual in nature, with both domestic and wild animals playing various important person roles in the lives of community members; these person roles are not metaphorical but rather assume all the sentience and agency that the term person implies. The findings have clear practical and policy implications for health services, education, environmental sustainability, and bioresource management.
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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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.005 | 0.008 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.001 | 0.002 |
| 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".