Bibliographic record
Abstract
Under Canadian common law, the limitation principle of discoverability applies to errors of fact, but not to errors of law. This error-of-law exception is a problematic doctrine. It appears to resurrect the ostensibly defunct fact/law distinction in civil claims. It stands in contrast to contemporary English precedent on the discoverability of mistakes of law. It controverts the Supreme Court of Canada’s claim that discoverability is a “general rule” for the interpretation of limitation periods on causes of action. And it considerably curtails the reach of the discoverability principle and the potential for plaintiffs labouring under an error of law to benefit from an extended limitation period. In practice, the error-of-law exception may overly curtail rights by protecting those who make legal rules while impeding those who have been harmed by unjust laws. This article develops a revised understanding of the error-of-law rule that strikes a better balance between protecting past reliance interests and vindicating plaintiffs’ rightful positions.
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 | 0.023 | 0.053 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.005 | 0.047 |
| Scholarly communication | 0.008 | 0.014 |
| Open science | 0.005 | 0.006 |
| Research integrity | 0.013 | 0.013 |
| Insufficient payload (model declined to judge) | 0.002 | 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".