Continual change and gradual warming: A summary of the North Slave Métis Alliance’s recorded cultural knowledge on climate and environmental change
Bibliographic record
Abstract
The Geological Survey of Canada and Carleton University led a project on the role of climate and land-use change in the transport and fate of metal(loids) in areas of high resource potential and contaminant loads in northern Canada. The North Slave Métis Alliance (NSMA) contributed to this collaborative project through a traditional knowledge study. The study details Métis traditional knowledge about variation in climate and environmental conditions in the Northwest Territories. Data was obtained from interviews conducted with NSMA members. It was also taken from primary and secondary literature that is relevant to Métis historical experience. Traditional knowledge of climate change provided by NSMA members is rooted in applied knowledge of historical climate and environmental conditions. This includes special practices related to those conditions. It also involves observation and analyses of recent shifts away from historical norms. This traditional knowledge suggests that in addition to variability in weather and environmental conditions to be anticipated year to year, climate change is producing an overall warming. This has impacts on seasonality, precipitation, water levels, and ice quality. As a result, the health, behaviour, and distribution of fish and wildlife are also affected. The results of the NSMA study will be combined with western science knowledge. The outcome will be a collection of knowledge on climate and environmental change that will include human contextual experience. This approach is expected to provide insight into past climate dynamics that cannot be identified by approaches that only look at the ecology of fossil plants and animals.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".