Bibliographic record
Abstract
The right of self‐determination of indigenous peoples within states often branches in two directions: (1) a drive for more autonomy for indigenous nations and (2) a demand for greater participation in the decision‐making institutions of the state. These two branches of indigenous self‐determination appear to fit very closely with the twin pillars of federalism ‐ self‐rule and shared‐rule. There are many aspects of federalism that can provide a context for accommodating the self‐determination of indigenous peoples within federal states. The drive for greater autonomy, or self‐rule, can be accommodated through a public form of government where indigenous people are the demographic majority in a region, or through the exercise of the aboriginal right of self‐government and the negotiation of intergovernmental agreements. The demand for greater participation in the decision‐making institutions of the state, or shared‐rule, can be met by guaranteed representation for indigenous peoples in the legislatures of federations, in the creation of Aboriginal parliaments, in the creation of state dispute resolution mechanisms to address the needs of indigenous peoples, in the development of treaty‐making and treaty‐renewal processes, and through indigenous participation in the intergovern‐mentalrelations of federal states.
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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.015 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.009 | 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".