The Vital Role of Dehcho Dene Knowledges in Climate Change & Permafrost Thaw Adaptation in Jean Marie River First Nation NWT
Bibliographic record
Abstract
Across the globe climate change has become an issue of growing concern for both Indigenous and non – Indigenous peoples alike. In Northern Canada this narrative is no different. For Indigenous groups such as the Jean Marie River First Nation (JMRFN) anthropogenic climate change is not only a reality but is visible through their daily interactions with the environment around them. Additional insight pertaining to these climatic changes and their impacts can be found through analyzing the traditional knowledge systems of the JMRFN and how these before mentioned interactions have changed over time. This two-year participatory research project has investigated these observed changes to the environment, there impacts on traditional cultural activities and the overall health of the JMRFN community. The analysis of these climatic changes have been done in hopes of better understanding how local Dene knowledges, values and culture can be applied to create an effective climate change adaptation strategy for JMRFN. Additionally, this research hopes to demonstrate why current non – Indigenous, top-down approaches to environmental management and climate change adaptation planning can be ineffective and culturally irrelevant for Indigenous peoples.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.019 | 0.009 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".