Towards a Jurisprudential Articulation of Indigenous Land Rights
Bibliographic record
Abstract
As expert analysis concentrates on indigenous rights instruments, particularly the long fought for 2007 UN Declaration on the Rights of Indigenous Peoples, a body of jurisprudence over indigenous land and resources parallels specialized standard-setting under general human rights treaties. The aim of the present article is to provide a practical and comparative perspective on indigenous land rights based on the process of jurisprudential articulation under such treaties, principally in the Inter-American and African contexts. While specialized standards inevitably generate a view of such rights (and, indeed, indigenous rights more generally) as a set of entitlements separate from general human rights, judicial and quasi-judicial practice as it exists or is being developed within regional and global human rights systems is effectively shaping up their content and meaning. I argue that indigenous land rights jurisprudence reflects a distinctive type of human rights discourse, which is an indispensable point of reference to vest indigenous land issues with greater legal significance. From a practical standpoint, focussing on human rights judicial and quasi-judicial action to expand existing treaty-based regimes and promote constructive partnerships with national courts, though not a panacea to all the intricacies of indigenous rights, does appear to offer a more realistic alternative to advocacy strategies primarily based on universally binding principles (at least at this stage) or the disengagement of domestic systems from international (human rights) law.
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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 | 0.007 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.005 | 0.022 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".