Denésoliné (Chipewyan) Knowledge of Barren-Ground Caribou (<i>Rangifer tarandus groenlandicus</i>) Movements
Bibliographic record
Abstract
Semi-directed interviews relating to the traditional knowledge (TK) of barren-ground caribou (Rangifer tarandus groenlandicus) movements were conducted with elders and hunters from the Denésoliné (Chipewyan) community of Lutsël K’é, Northwest Territories, Canada. The objective was to document Denésôliné knowledge of past and present caribou migration patterns and record their explanations for perceived changes in movements. Elders recognized expected and unusual levels of variation in caribou movements. Local narratives show that Denésoliné communities have a fundamental awareness of caribou migration cycles. Most elders thought fire frequency and intensity had increased over their lifetimes and that caribou numbers and distribution had been affected. The majority of Lutsël K’é elders thought mining development was affecting caribou movements in some way. Elders believe that disturbance around traditional migration corridors and water crossings and disturbance of “vanguard” animals might be forcing caribou to use less optimal routes and influencing where they overwinter. Elders also believe that a lack of respect for caribou will cause the animals to deviate from their “traditional” migration routes and become unavailable to the people for a period of time. Wildlife management practices may need to further accommodate aboriginal perspectives in the future.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".