The power to consent: Indigenous peoples, states, and development projects
Bibliographic record
Abstract
The principle of free, prior and informed consent (FPIC) has become increasingly important in Indigenous peoples’ rights discourse. But continuing debates over the meaning of consent show the need for further clarification. In Part I of the article, I give a brief description of consent’s ‘standard grammar’ as developed in other areas of Western legal and ethical discourse to clarify what those who use the language of consent within that tradition commit themselves to, if they are to do so correctly. I also highlight the features that explain why consent has the potential to diminish coercion in relations of deep asymmetry. I argue that this potential is not related to the existence of an ‘absolute’ veto but, rather, to the specific way in which consent structures the interactions between the parties. In Part II, I turn to the Canadian context and the duty to consult developed by the Supreme Court of Canada. I make two main arguments: first, I show that that language is importantly different from consent and, second, I argue that though the Court in Tsilqoth’in Nation uses consent in a way that is closer to the standard grammar, the significance of this move remains limited. In Part III, I turn toward the UN Declaration on the Rights of Indigenous Peoples to assess whether it presents a better framework for the fulfilment of consent’s promise. I argue that not only is it possible to interpret the Declaration as formulating a conception of consent that follows broadly the standard grammar but also that this reading best fits the Declaration’s basic purposes. However, to develop a functional conception of FPIC, we need to face a challenge for which the grammar of consent has little answer: the often-contested character of Indigenous rights. I conclude by sketching three possible responses to that challenge.
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 | 0.020 | 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".