Bibliographic record
Abstract
In Delgamuukw, then Chief Justice Lamer described the courts’ function in the trial of an indigenous title claim as “the determination of the historical truth”. This does not mean that history is an immutable thing which can be proven in the courtroom with scientific certainty. When historical facts are relevant in litigation, they can provide fertile ground for interpretation and opinion, and thus the subject matter of expert evidence. In Van der Peet, Lamer C.J. noted the challenges posed by “proving a right which originates in times where there were no written records of the practices, customs and traditions engaged in.” In spite of these challenges, the courts must tackle daunting task of reaching conclusions on historical matters on the record before them. As Justice Binnie noted in Marshall, they “… are handed disputes that require for their resolution the finding of certain historical facts. The litigating parties cannot await the possibility of a stable academic consensus. The judicial process must do as best it can.” Expert evidence can play a key role in making such findings. While addressing issues in the distant past demands flexibility in the receipt of evidence, the Supreme Court has cautioned that “[t]here is a boundary that must not be crossed between a sensitive application and a complete abandonment of the rules of evidence”. Given the important role of experts in such cases, the courts’ “gatekeeping” function of determining admissibility of expert evidence provides a critical filter. Among the relevant considerations in assessing such evidence is “the distracting and time-consuming thing that expert testimony can become”. The purpose of this paper is to examine the rules governing the admissibility of expert evidence as applied to the kinds of historical issues raised in indigenous rights and title cases. Expert evidence can increase cost and lengthen trials. To advance claims resolution in the face of the dual roadblocks of costly and time-consuming litigation and a largely unsuccessful treaty negotiation process, a recent article in this Journal has proposed an impartial non-judicial body for mapping indigenous title areas. Such innovations may assist in finding a way forward. To the extent that litigation will relied upon as an alternative for resolving these disputes, expert evidence which is tailored to conform with the requirements set out by the courts can contribute to a more efficient and effective resolution process.
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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 | 0.051 | 0.064 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.019 | 0.052 |
| Scholarly communication | 0.019 | 0.030 |
| Open science | 0.004 | 0.009 |
| Research integrity | 0.024 | 0.021 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".