Rooting natural climate solutions in <i>Wahkohtowin</i> through Indigenous guardianship: insights from a youth-led initiative in Northern Ontario, Canada
Bibliographic record
Abstract
In recent years, increasing attention has been directed to “natural climate solutions” to mitigate climate change through the protection, restoration, and improved management of carbon-storing ecosystems. In practice, Indigenous Peoples have been implementing natural climate solutions for millennia through land stewardship. As Indigenous nations and communities in Canada reassert stewardship roles through Indigenous Guardians programs, the question arises: what possibilities emerge when natural climate solutions are driven by Guardians, guided by multifaceted community priorities and Indigenous knowledge? This paper responds to this question, drawing upon collaborative research with Wahkohtowin Development, a social enterprise based in Treaty 9 territory (Ontario, Canada), made up of Chapleau Cree First Nation, Missanabie Cree First Nation, and Brunswick House First Nation. We engaged youth Guardians in workshops that generated insights on the role of youth, cross-cultural collaboration, and holistic conceptualizations of climate action rooted in Indigenous ontologies (such as the Cree philosophy of wahkohtowin, embodying kinship and interconnectedness). Our analysis reveals that Indigenous Guardians are well positioned to advance natural climate solutions and to do so in an integrative manner that addresses intersecting challenges—with benefits for communities, ecosystems, climate action, and reconciliation.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.031 | 0.011 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.001 | 0.003 |
| 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".