Is the Canadian administrative state committed to engaging in meaningful dialogue with Indigenous Peoples of Canada?
Bibliographic record
Abstract
Abstract Despite pledging to engage in two-sided dialogues during resource consultations with Indigenous Peoples ( Haida Nation 2004 , para 44), the administrative Canadian state often defaults to one-sided reasoning, emphasizing the project’s necessity and managing evidential gaps in the project’s assessments by giving the benefits of doubt to the industry while promising Indigenous communities adaptive management programs to mitigate all potential adversaries. Such reasoning strategies raise doubts about Canada’s genuine commitment to administering the promised meaningful dialogue in Indigenous consultations. The lack of normative criteria for assessing the meaningfulness of dialogue within the Canadian administrative system further complicates the evaluation of government officials’ commitment. This article applies Walton’s dialogue system to evaluate how government agencies engage in consultative exchanges with Indigenous Peoples, focusing on their reasoning as commitments. It differentiates between dialogical and procedural elements in controlled exchanges across three contentious projects — the Mackenzie Valley, Trans Mountain, and Site C projects — theorizing the differences between one-sided, two-sided, and collapsed dialogues in Indigenous consultations. The article reveals that officials’ actions in these dialogues often leveraged their institutional authority and statutory discretion to impose compliance costs on epistemically diverse communities ( Pimenova 2025 ). This strategy sometimes weakens these communities’ capacity to challenge project developments by subordinating their diverse testimonial credibility to the dominant argumentative discourse centered on consumption, mitigation, and epistemic ignorance.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".