Things Are Changing: Climate Change, Afforestation, and Indigenous Economic Opportunity in Northern Saskatchewan
Bibliographic record
Abstract
Indigenous communities in Northern Canada face rapid climate change that threatens their local ecosystems, food security, cultural ties to the land, and connections to the rest of Canada. Participating in climate adaptation efforts is crucial for Indigenous wellbeing, self-determination, and economic involvement amid a changing climate. We interviewed a total of 11 people drawn from the Elders, land users, community leaders, Indigenous business owners, and nonprofit staff at Black Lake, Fond du Lac, and Hatchet Lake Denes łin. First Nations in Northern Saskatchewan. For over 40 years, these knowledge holders observed how climate change threatened their communities’ traditional practices and the Denes łin. way of life. They also discussed various adaptive measures that could bolster local economic development. In this paper, we present community perspectives on one specific climate adaptation action: high-latitude tree line afforestation. While community members are concerned that afforestation could harm wildlife (especially barren-ground caribou), be undertaken without local consent and control, and facilitate the spread of invasive species, they also hope that an afforestation project could create jobs, involve youth, support the local economy, and contribute to fighting climate change.
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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 | 0.001 | 0.002 |
| Science and technology studies | 0.012 | 0.004 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".