Climate change and water at Stellat'en First Nation, British Columbia, Canada: Insights from western science and traditional knowledge
Bibliographic record
Abstract
Insights from both western science and traditional knowledge were applied to identify, and begin to address, climate change and water impacts at Stellat'en First Nation, British Columbia, Canada. Qualitative data from interviews and surveys of Stellat'en community members were compiled and compared with air temperature, precipitation, and hydrometric data from meteorological stations and proximal rivers. Community Elders noted changes to river water levels and shifts in fish populations. The quantitative data revealed a 2.3 °C rise in air temperature, 5 percent increase in precipitation, and 10 percent decline in snowfall over a 40‐year period. Results from these analyses were reported in two knowledge intersection workshops at Stellat'en First Nation, and information sharing took place to: facilitate discussion and awareness between traditional and western knowledge holders, gain insights on the community's views of climate change and water, and identify strategies for action. Recommendations formulated and implemented by Stellat'en First Nation include improved policies, and community and individual actions. Les changements climatiques et les ressources en eau dans la Première nation Stellat'en, Colombie‐Britannique, Canada : les connaissances issues de la science occidentale et des savoirs traditionnels Le recours aux connaissances issues de la science occidentale et des savoirs traditionnels a permis d'identifier, puis d'aborder les répercussions des changements climatiques sur les ressources en eau dans la Première nation Stellat'en, Colombie‐Britannique, Canada. Les données qualitatives obtenues au moyen d'entrevues et d'enquêtes menées auprès de membres de la communauté Stellat'en ont été colligées et comparées à des données de température de l'air, de précipitations et d'hydrométrie recueillies de stations météorologiques et de rivières des environs. Les sages de la communauté ont observé des changements des niveaux d'eau de la rivière ainsi que des variations dans les populations de poissons. Les données quantitatives mettent en évidence une hausse de 2,3 °C de la température de l'air, une augmentation des précipitations de l'ordre de 5 pour cent, et une réduction des chutes de neige de l'ordre de 5 pour cent sur une période de 40 ans. Les résultats qui ressortent de ces analyses ont été présentés au cours de deux ateliers d’échanges sur les savoirs dans la Première nation Stellat'en. Les informations ont ainsi été partagées afin de rendre plus aisées la discussion et la sensibilisation entre les détenteurs de savoirs traditionnels et occidentaux, d'accroître les connaissances sur les opinions de la communauté au sujet des changements climatiques et les ressources en eau, et de fixer des stratégies d'action. L'amélioration des politiques et les actions à l’échelle communautaire et individuelle comptent parmi les recommandations formulées et mises en œuvre par la Première nation Stellat'en.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.024 | 0.012 |
| Scholarly communication | 0.008 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| 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".