Water-based ecology: A First Nations' proposal to repair the definition of a forest ecosystem
Bibliographic record
Abstract
First Nations Elders are very concerned about whether enough clean drinking water will exist for future generations. Three highly respected Elders from the Southern Interior of British Columbia helped the author investigate First Nations water-based ecology: Mary Thomas from the Secwepemc (Shuswap), Millie Michell from the Nlaka'pamux (Thompson), and Mary Louie from the Syilx (Okanagan) Nation. This paper follows on from the author's previous examination of First Nations' spiritual and ecological perspectives on water (BC Journal of Ecosystems and Management 1(1): 54–68). The Elders' vision of the relationships between water, land, and animals highlights an apparent shortcoming in Western science's definition of an ecosystem. In this paper, the author encourages a shift towards water-based ecosystem management, proposing to repair of the definition of forest ecosystems in a way that interweaves First Nations' philosophy with Western science's ecosystem-based management approach.
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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 | 0.001 |
| Science and technology studies | 0.005 | 0.027 |
| Scholarly communication | 0.006 | 0.009 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.004 | 0.006 |
| 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".