Can free, prior and informed consent support reconciliation between indigienous peoples and the state in multicultural societies
Bibliographic record
Abstract
The United Nations Declaration on the Rights of Indigenous Peoples has been hailed as a ‘framework for reconciliation’ on which states and indigenous peoples can build harmonious relationships. However, during the negotiations of UNDRIP’s text, some argued that its impact would be constrained by the adoption of a cultural rights framework over an unambiguous recognition of the right to self-determination. This thesis investigates the implementation of a key provision of UNDRIP: the requirement on states to consult with indigenous peoples in order to obtain their consent before approving measures or policies that would impact on indigenous rights, asking whether weak interpretations of indigenous self-determination under a multicultural model of rights are constraining the reconciliatory potential of prior consultation. It provides a theoretical analysis of prior consultation, drawing from indigenous critiques of human rights based multiculturalism and western theories of dispute resolution, and applying a decolonial theoretical framework. The theoretical analysis is grounded in case studies that illustrate how prior consultation is being implemented in Peru and Canada. This thesis concludes that two different conceptualisations of FPIC have emerged: the ‘general rule’ approach, which is based on the right to self-determination and generally favoured by indigenous peoples; and the ‘multiculturalist approach’, which views FPIC as a facet of multicultural democracy. This latter approach is generally favoured by states, whose practice in this regard will shape the future development of FPIC as an international legal norm. However, this ‘multiculturalist approach’ is unlikely to lead to reconciliation because it constrains indigenous self-determination within a colonial imbalance of epistemic, political and economic power that overwhelmingly benefits the state. In contrast, this thesis puts forward a dispute resolution approach which reimagines prior consultation as a duty to forge consensus. Such an approach, based on mutual respect and collaboration between peoples, may be more likely to contribute to reconciliation because it sidesteps commonly-held concerns that indigenous consent will be wielded as a unilateral right of veto, and recognises indigenous self-determination more fully. Viewing prior consultation through the lens of dispute resolution also suggests that mediation may offer a range of tools to counterbalance structural disadvantages that indigenous peoples face within the prior consultation process and encourage a more genuine intercultural dialogue.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.014 | 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".