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Record W4413244070 · doi:10.3138/ccar.v14i2.421

A Statutory Solution to Ontario’s Environmental Class Action Problem: Section 99(2) of the <i>Environmental Protection Act</i>

2019· article· en· W4413244070 on OpenAlexaboutno aff
J. R. Boyd

Bibliographic record

VenueCanadian Class Action Review · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicEnvironmental law and policy
Canadian institutionsnot available
Fundersnot available
KeywordsPlaintiffClass actionCertificationEnvironmental lawEnvironmental justiceAppealStatutory lawClass (philosophy)Action (physics)Section (typography)LawLaw and economicsBusinessPolitical scienceSociologyComputer scienceAdvertising

Abstract

fetched live from OpenAlex

Abstract: Despite the immense promise of the Class Proceedings Act, 1992 as a tool to facilitate claims for environmental harms, the landscape for environmental class actions in Ontario is bleak. The seminal environmental decisions involving the Act (Hollick v Toronto and Smith v Inco) have saddled victims of environmental harms with difficult precedent to overcome at both the certification and merits stages of litigation. However, the decision in Midwest v Thordarson, in which the Court of Appeal affirmed the existence of the cause of action in section 99(2) of the Environmental Protection Act, provides plaintiffs with a new path to success in environmental class actions. The section 99(2) cause of action is versatile and powerful, and may be asserted for different types of environmental harms, by different types of plaintiffs, against different types of defendants. Section 99(2) claims can also overcome common obstacles that have prevented environmental class actions from receiving certification. Finally, section 99(2) offers a likelihood of greater success at a trial as compared to the typical common law causes of action for environmental harms. With section 99(2), plaintiffs can achieve the promise of class actions as a tool for seeking justice for widespread environmental harms.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.873
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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.

Opus teacher head0.028
GPT teacher head0.261
Teacher spread0.233 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2019
Admission routes1
Has abstractyes

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