Pursuing a Reconciliatory Administrative Law: Aboriginal Consultation and the National Energy Board
Bibliographic record
Abstract
Environmental assessment within the process of regulatory review is recognized as the preferred means for carrying out the duty to consult and accommodate Aboriginal rights in administrative decisions over proposed resource development. Recent evidence suggests that integrating the duty to consult into National Energy Board (NEB) proceedings and subsuming the law of Aboriginal consultation under principles of administrative justice have not advanced the goal of reconciliation. This article considers whether the statutory mandate of the National Energy Board requires it to have sufficient regard to Aboriginal rights in a manner consistent with the adjudication of constitutional issues in administrative law. The article argues, through an examination of the Board’s process and recent decisions of the Federal Court of Appeal, that there is good reason to revisit the Supreme Court of Canada’s jurisprudence on the role of administrative expertise in effecting reconciliation in the NEB context. In particular, it submits that both reconciliatory and administrative objectives would be better served if the NEB were to perform a formal consultative role with Aboriginal claimants in accordance with prescribed constitutional standards. This would help to ensure that administrative actors reach rights-compliant decisions in the first instance and provide a more reliable basis for judicial deference to tribunal findings regarding Aboriginal rights.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.027 | 0.027 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.033 | 0.043 |
| Scholarly communication | 0.020 | 0.007 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.016 | 0.014 |
| 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".