To what extent does the United Nations facilitate self-determination and Indigenous rights to participate in decision making?
Bibliographic record
Abstract
The United Nations has witnessed an increasing level of recognition of Indigenous rights since the adoption of the Declaration in 2007. This thesis examines the extend to which the United Nations facilitates the recognition of Indigenous rights to self-determination in this emerging area of international law and assesses its impact domestically within settler-states. Specifically, it assesses the capacity for Indigenous advocacy at the United Nations to influence colonial-settler states’ recognition of Indigenous rights to self-determination, as asserted in the Declaration on the Rights of Indigenous Peoples and seeks to identify means to increase its efficacy. The study draws a comparative analysis from four settler-states, Canada, the United States of America, New Zealand and Bolivia, to highlight lessons that may inform the Australian context. The research aims to assess settler Governments’ responsiveness and capacity within the United Nations framework to better facilitate the recognition of self-determination and avenues for adjudication, reparation and redress for Indigenous Peoples. The thesis implements a Transformative Indigenous Rights Theory which privileges Indigenous voices and enacts a decolonizing intent. Methodologically, the thesis draws on interviews with Indigenous leaders involved in UN processes and an action-based praxis approach, which highlighted the correlation between local and global advocacy.
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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 | 0.010 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.018 |
| Scholarly communication | 0.007 | 0.008 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".