Bibliographic record
Abstract
O n September 13, 2007, the United Nations General Assembly voted to adopt the UN Declaration on the Rights of Indigenous Peoples, a historic development more than two decades in the making. Though its genealogy is complicated, the origins of the Declaration can be traced at least to the 1982 founding of the Working Group on Indigenous Populations (WGIP) through the UN Economic and Social Council. The process was, by any measure, a slow one. Even after it was approved by the UN Sub-Commission on the Prevention of Discrimination and Protection of Minorities in 1994, twelve more years passed before the then-“Draft” Declaration was adopted by the UN Human Rights Council in June 2006, a step necessary before it could be put before the General Assembly for ratification. In the end, a clear majority of member states voted for adoption of the Declaration. While eleven of those with representatives present for the vote abstained, more noteworthy was the circumstance that the only four votes cast against adoption came from settler states with large Indigenous populations: Australia, Canada, New Zealand, and the United States. Notwithstanding this, however, the Declaration is widely regarded as a watershed development signaling a qualitative change in the fraught history of relations between Indigenous peoples and states at the global level. These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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 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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.445 | 0.221 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".