Justice without science? Judging the reliability of forensic science in Canada
Bibliographic record
Abstract
A compelling body of scientific research demonstrates that the validity of many forensic sciences is uncertain and that courts have been ineffective in safeguarding the reliability of forensic science. While this research has had some impact in the US and UK, Canadian law and institutional arrangements have largely failed to acknowledge and respond to scientific developments. This article explores these issues through the example of fingerprint comparison. This identification evidence has been accepted in Canadian courtrooms for more than 100 years. However, its reliability and limitations were never subjected to serious scrutiny in a Canadian court until the BC Supreme Court trial in R v Bornyk, 2017 BCSC 849. Tracing the course of the Bornyk litigation reveals systemic problems with the production and evaluation of forensic science evidence within the Canadian criminal legal system.
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 | 0.077 | 0.253 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.010 | 0.009 |
| Science and technology studies | 0.028 | 0.029 |
| Scholarly communication | 0.023 | 0.007 |
| Open science | 0.006 | 0.011 |
| Research integrity | 0.006 | 0.009 |
| 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".