Self-determination and procedural justice in a Yukon climate planning partnership
Bibliographic record
Abstract
Planning for community resilience and climate change requires new forms of engagement that are accountable to Indigenous peoples and the social and cultural upheavals associated with colonial harm. This thesis shows that climate governance requires partnerships and policy actions that reflect needs and priorities of communities in specific geographic, political, and cultural contexts. As a case study, it examines the development of the 2020 Our Clean Future (OCF) strategy by Government of Yukon and Indigenous partners. Through semi-structured interviews and document studies, the research applies a theoretical lens of procedural justice and self-determination to the OCF process. Outcomes from this research offer a set of policy cycle considerations and recommendations for future environmental planning partnerships that include taking a rights-based approach, increasing capacity for collaboration in multiple areas, stronger integration of culturally diverse ways of knowing and doing, and targeted urban Indigenous engagement. Findings suggest OCF can serve as a useful procedural policy tool that supports Indigenous self-determination if lessons learned from the process are carried forward in future environmental planning partnerships.
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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 | 0.008 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.025 | 0.022 |
| Scholarly communication | 0.009 | 0.005 |
| Open science | 0.001 | 0.013 |
| Research integrity | 0.002 | 0.003 |
| 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".