Extending Time Limits in Sexual Abuse Cases: A Critical Comparative Evaluation
Bibliographic record
Abstract
An issue common to many common law jurisdictions is the question of civil claims based on alleged past sexual abuse brought a long time after the events. Many survivors of such abuse only make the allegations public, if ever, many years after the abuse took place. Each jurisdiction has time limits within which civil claims must be brought. There are generally sound policy reasons for such limits: to discourage lax attempts to enforce or vindicate claims; to respect the right of the defendant to not have stale claims brought; and to allow for a fair trial given the likelihood that the quality of evidence will deteriorate over time. However, it is difficult to impose such regimes on survivors of sexual abuse who come forward much later. The paper explores psychological literature that helps to explain why it is that such victims may only come forward, if ever, many years after the events. It is submitted that legal systems generally need to take a much more flexible approach to extension of time claims in such contexts, and avoid judgments as to when a victim ‘should have’ brought their claim. It will be concluded that the approach of several Canadian provinces, removing the limitation period in such cases, is the preferred approach.
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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 | 0.176 | 0.287 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.021 | 0.020 |
| Science and technology studies | 0.006 | 0.008 |
| Scholarly communication | 0.004 | 0.010 |
| Open science | 0.004 | 0.005 |
| Research integrity | 0.005 | 0.003 |
| Insufficient payload (model declined to judge) | 0.009 | 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".