Sound Science, Careful Policy Analysis, and Ongoing Relationships: Integrating Litigation and Negotiation in Aboriginal Lands and Resources Disputes
Bibliographic record
Abstract
Until recently, both courts and dispute resolvers have viewed negotiation and adjudication as two separate processes. What occurred in one process was considered largely irrelevant to what went on in the other. Recently, however, there has been a growing recognition that both processes must work together to resolve disputes over Aboriginal lands and resources. This paper weaves together the emerging trends in court decisions with the new thinking on dispute system design to set out a framework that maximizes the strengths of each process. In this framework, the courts are responsible not only for adjudicating on the substance of Aboriginal and treaty rights, but also for establishing standards for the negotiation process itself, thereby increasing the likelihood of a fair and durable resolution.
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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 | 0.072 | 0.070 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.019 | 0.118 |
| Scholarly communication | 0.033 | 0.024 |
| Open science | 0.003 | 0.016 |
| Research integrity | 0.017 | 0.011 |
| Insufficient payload (model declined to judge) | 0.003 | 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".