Ontario Civil Justice Reform in the Wake of COVID-19: Inspired or Institutionalized?
Bibliographic record
Abstract
On 17 March 2020, Ontario’s courthouses shut their doors as the civil justice system locked down with the rest of the province. Regular court operations were suspended due to the state of emergency caused by the COVID-19 pandemic. This was followed by a flurry of activity as courts drew up plans to resume operations as soon as possible. The “new normal” became virtual hearings, either by video conference, in writing, or by telephone. As Attorney General Douglas Downey said, “We’ve modernized the legal system by about 25 years in 25 days.” Has the revolution arrived? Will the changes made in response to the pandemic become permanent? Will they be sufficient to address the problems of cost and delay that plague the civil justice system? This article will posit that many of these changes are likely to become permanent. However, the extent and effectiveness of change will depend on the ability of “policy entrepreneurs” to use this moment of crisis to overcome institutional inertia in the Ministry of the Attorney General (MAG) and professional resistance in the Bar. This is not the first time that “dramatic innovation[s]” have been made in response to a crisis in the civil justice system, as evidenced by the history of reform in that area. Lasting change will not come easily. Furthermore, while these changes are welcome, they are insufficient to address the crippling backlog facing the courts. A functioning civil justice system is essential to a functioning democracy, and Ontario’s civil justice system is fundamentally broken. The “paradigm shift” needs to go further. We need to entirely change our conception of how courts work, the nature of procedural justice, and our understanding of access to justice and how to facilitate it. The answer I propose, as Richard Susskind and others have, is a system of online courts, where human judges hear evidence and arguments and render decisions by way of an online platform, all within a public dispute resolution (court or tribunal) system. British Columbia’s Civil Resolution Tribunal (BC CRT) is an excellent example. I argue that, as in BC, online courts could be initiated incrementally, alongside the current system, and thereby bypass and address many of the issues facing the current court system. I conclude with some thoughts for the future. Much has been written on the subject of online courts, and the COVID-19 crisis in Ontario has precipitated numerous blogs and online articles.
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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 | 0.006 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.029 | 0.026 |
| Scholarly communication | 0.017 | 0.005 |
| Open science | 0.003 | 0.007 |
| Research integrity | 0.008 | 0.008 |
| Insufficient payload (model declined to judge) | 0.008 | 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".