The Woodlands School Litigation and Settlement: Further Complications for Historical Abuse Claims
Bibliographic record
Abstract
September 19, 2011 marked the deadline for survivors of abuse at the Woodlands School (“Woodlands”) in New Westminster, British Columbia to apply for compensation under the Woodlands School Settlement Agreement (the “Settlement Agreement”) approved by the British Columbia Supreme Court. The Settlement Agreement was the culmination of a lengthy litigation process over abuse of children and adults with disabilities at Woodlands, a residential facility operated by the province. Two aspects of the litigation and the Settlement Agreement terms are particularly significant for historical abuse claims. The first is the province’s use of crown proceedings legislation to create a cut-off that restricts recovery to those claimants who suffered abuse after August 1, 1974 – the commencement date of British Columbia’s Crown Proceedings Act (CPA). The second is the fact that the Settlement Agreement terms allow survivors to seek compensation for sexual and non-sexual abuse even though the limitation period for the non-sexual abuse claim has expired for many, if not most, of the claimants. Considered more broadly in the context of other challenges that historical abuse survivors face in bringing their claims, these features of the Woodlands litigation process suggest it may be becoming increasingly difficult for survivors to successfully bring a claim, particularly against the Crown.
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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 | 0.019 | 0.053 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.042 | 0.012 |
| Scholarly communication | 0.016 | 0.008 |
| Open science | 0.003 | 0.010 |
| Research integrity | 0.014 | 0.017 |
| Insufficient payload (model declined to judge) | 0.013 | 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".