The Predicament of Expertise in the Revival of Indigenous Legal Traditions
Bibliographic record
Abstract
In this chapter, the author shares lessons he learned about the nature of expertise and its power to communicate and produce just outcomes in his efforts to support the Indigenous Cross Lake Cree community in Manitoba, Canada, which was engaging in a type of ‘inherent jurisdiction’ lawmaking to recoup money owed to it by the Crown corporation Manitoba Hydro. The author comments on how his academic qualifications automatically granted him a degree of credibility that he was able to leverage to the benefit of the Cross Lake Cree community. Ultimately, the author felt that the best way he could mobilize his anthropological expertise was to reach out to sympathetic audiences both locally and internationally to lend credence to the public statements made by councillors of the Band, whose credibility might otherwise be called into question. The author hopes that by practising an advocacy-oriented anthropology of law and focusing on restorative justice, the profitable translation of the languages of state and Indigenous legal expertise across the boundaries of their jurisdictions can be achieved.
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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 | 0.005 | 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 | 0.009 | 0.064 |
| Scholarly communication | 0.010 | 0.009 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.004 | 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".