Tribunal administration and the duty to consult: A study of the National Energy Board
Bibliographic record
Abstract
In this study, the authors present evidence that the National Energy Board (NEB) does not evaluate whether the duty to consult has been met by applicants or the Crown for the purposes of regulatory approval. While NEB panels do draw conclusions about the sufficiency of consultation, they are not premised on the legal requirements established by the Supreme Court of Canada or subsequent case law. On the contrary, the authors discover that the NEB has approved nearly 100 per cent of the applications in which consultation remains an issue but it relies on three types of justifications for still recommending approval: (i) that it lacks the jurisdiction to consider the consultation at issue; (ii) that outstanding consultation can be addressed through ongoing consultation; and/or (iii) that there are no impacts on rights. Based on these findings, the authors argue that courts should attend to differences over legality and institutional rationality in guiding tribunal authority. In doing so, courts will be in a better position to identify the effect of these differences on tribunal findings, to understand how courts and governments already rely on these findings irrespective of their quality, and to compel transparency for their generation and use.
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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 | 0.016 | 0.052 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.012 | 0.008 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.011 | 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".