Using Traditional Knowledge to Adapt to Ecological Change: Denésoliné Monitoring of Caribou Movements
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The Chipewyan Dene or Denésoliné have long been dealing with variability in the movements of barren-ground caribou (Rangifer tarandus). Many generations ago, Denésoliné hunters learned that by observing caribou at key water crossings during the fall migration, they could obtain critical information about caribou health, population, and movement patterns. Systematic observation of these indicators by hunters strategically organized along the tree line enabled the Denésoliné to adapt their harvesting practices, including the location of family camps, to maximize harvest success. While this system of observation was developed for traditional subsistence harvesting, its techniques could be usefully applied today to other natural resource management contexts. In particular, such monitoring might help us understand how new bifurcation points created by mineral resource development may be affecting the Bathurst caribou herd. As governments, communities, and academics search for ways to include traditional knowledge in decision making for resource management, this paper recognizes that the Denésoliné and other indigenous peoples have their own systems of watching, listening, learning, understanding, and adapting to ecological change.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it