Bibliographic record
Abstract
Under the principled approach, hearsay evidence is admissible if it is necessary and reliable. In Khelawon, the Supreme Court of Canada has reoriented the reliability inquiry around the question of whether the hearsay evidence in question should be admitted because, in the circumstances, the inability of the adverse party to test the evidence is not of great concern. Usually, the concern about testing the evidence can be allayed by the inherent reliability of the evidence or by the presence of substitutes for cross-examination before the trier of fact. In this comment, I argue that although this approach is generally consistent with the principled approach to the admissibility of evidence, it also creates some uncertainty about how trial judges are to assess threshold reliability. Although the question to be asked is now reasonably clear, Khelawon sets no particular limits on the factors that may be considered in answering that question. While this flexibility may seem consistent with the principled approach, there is a danger that it will lead to voir dires that either recapitulate the main trial or are limited on an ad hoc basis. Based in part on a discussion of four appellate decisions on the principled approach decided after Khelawon, I suggest that the further development of the principled approach to hearsay will require an approach to threshold reliability that limits the relevant factors to those bearing on the testimonial qualities of the hearsay declarant.
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 | 0.030 | 0.042 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.011 | 0.037 |
| Scholarly communication | 0.012 | 0.011 |
| Open science | 0.005 | 0.005 |
| Research integrity | 0.020 | 0.031 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".