A “Consultation Dance” for Legitimacy: The Supreme Court and The Duty to Consult in B.C.’s Environmental Assessment Process
Bibliographic record
Abstract
The duty to consult is an Aboriginal right under s. 35 of Canada’s Constitution Act, 1982. Under the duty, the Crown must consult with Indigenous nations if their asserted or recognized rights may be negatively impacted by a proposed Crown action. The Supreme Court of Canada (SCC) has explained that all parties in consultation need to act in good faith and that the Crown is expected to act honourably in order to discharge the duty. This dissertation posits a framework to evaluate whether the Crown upholds its honour throughout decision-making. The framework of input, throughput, and output legitimacy can demonstrate whether the Crown is acting legitimately towards Indigenous peoples’ and their concerns throughout various stages of decision-making. The dissertation then applies this framework to B.C.’s Environmental Assessment (B.C. EA) process in order to assess how the duty to consult is implemented. I find that the Crown does not attain some key aspects of input, throughput, and output legitimacy. In particular, Indigenous parties perceive that they do not have adequate resources to participate effectively in consultation activities; there is a lack of accountability and transparency regarding the Crown’s decision-making throughout the EA process; and the Environmental Assessment Office does not sufficiently explain how its preferred course of action provides superior protection for Aboriginal rights over alternative actions. The Crown exhibits these shortcomings because it prefers to fulfill the duty in a way that is least disruptive to existing norms and practices, even when doing so increases the risk of Indigenous peoples pursuing litigation to challenge the Crown. Consequently, contentious politics and expensive, time-consuming legal challenges continue, ultimately casting doubt on the duty to consult’s ability to advance reconciliation between the Crown and Indigenous peoples.
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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 | 0.023 | 0.057 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.053 | 0.097 |
| Scholarly communication | 0.031 | 0.013 |
| Open science | 0.003 | 0.014 |
| Research integrity | 0.014 | 0.022 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".