Free Prior and Informed Consent to mine development in the Yukon: Norms, Expectations, and the Role of Novel Governance Mechanisms
Bibliographic record
Abstract
The adoption of the United Nations Declaration on the Rights of Indigenous Peoples (UNDRIP) has catalyzed Indigenous rights conversations in Canada around Free, Prior and Informed Consent (FPIC). The Yukon territory, where a majority of First Nations have self-government and settled land claims, provides a unique case for assessing how FPIC is being defined and exercised in light of possible mine developments. Findings from semi-structured interviews and document review revealed limited explicit engagement with FPIC by key Yukon governance institutions. This thesis serves to identify and make sense of this situation in an exploratory way, offering three factors: time, treaty implementation priorities, and awaited federal action, to explain the apparent lack of institutional engagement with FPIC. Despite instances of consent-like rights held by First Nations in the Yukon, there remains a lack of clear articulation from a majority of these First Nations about expectations for the meaningful expression of consent. Through a case study with the Little Salmon Carmacks First Nation (LSCFN), this research revealed that although LSCFN’s expectations of FPIC are not fully formed as of yet, they include: early and ongoing engagement, full and accessible information, internal engagement and governance processes, the mitigation of resource barriers, enforceable commitments, contextually relevant and mutually agreed upon processes, appropriate representation, agreed upon definitions, and the mitigation of power imbalances. Given the reticence of the State to acknowledge and implement FPIC this thesis also evaluates the treatment of FPIC by the Initiative for Responsible Mining Assurance (IRMA) standard, and largely confirms the comprehensiveness of that novel governance process relative to LSCFN’s emerging expectations around FPIC.
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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 | 0.040 | 0.039 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.010 | 0.029 |
| Scholarly communication | 0.012 | 0.007 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.001 | 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".