Rule 2.1 of Ontario’s Rules of Civil Procedure: Responding to Vexatious Litigation While Advancing Access to Justice?
Bibliographic record
Abstract
This article analyzes the first three years of the operation of Rule 2.1 of Ontario’s Rules of Civil Procedure (the “Rule”), which allows a court to very summarily dismiss litigation that is “on its face” frivolous, vexatious, and/or abusive. The author explores the history of and rationale for the Rule, in the context of the access to justice crisis in Ontario, and in light of the perceived inadequacy of alternative mechanisms for addressing the dangers raised by vexatious litigants. He then reviews all 190 Rule 2.1 decisions decided between July 1, 2014 and June 30, 2017, with the goal to provide guidance for future lawyers and judges considering using the Rule. This is followed by an analysis of the effects on access to justice of the Rule, in terms of providing speedy and cost-efficient resolution of actions on their merits. The author concludes by considering how the Rule should be used in the future – doctrinally, institutionally, and ethically. His conclusions are hopeful. The Rule is powerful, and its use should prompt some pause in judges and lawyers. By and large, however, the Rule has been very well employed. It has resulted in immense savings of time and financial expense and many cases model fairness to vulnerable parties. In rare instances where the Rule’s (attempted) use has been inappropriate, costs in terms of delay and financial expense are usually minimal. The Rule is ultimately an inspiring example of how civil procedure can be amended to facilitate access to justice.
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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 | 0.009 | 0.029 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.011 |
| Scholarly communication | 0.009 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.008 | 0.008 |
| Insufficient payload (model declined to judge) | 0.003 | 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".