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Record W4414240183 · doi:10.22329/cjpp.v10i1.8451

The State of Court Administration in Ontario: A Preliminary Analysis of the Post-COVID Environment in the Ontario Court of Justice

2023· article· en· W4414240183 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueCanadian Journal of Practical Philosophy · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicLegal Education and Practice Innovations
Canadian institutionsYork University
Fundersnot available
KeywordsAdministration (probate law)Economic JusticeState (computer science)Administration of justiceFederal courtQuality (philosophy)Court decision

Abstract

fetched live from OpenAlex

Canadian courts have been struggling with delay and backlog for decades. Unnecessary and excessive delay in courts is an ethical issue which results in suffering by litigants and witnesses and dilutes the quality of justice. When the COVID-19 pandemic hit, the situation became dire. Now that the pandemic has been declared over, we have an opportunity to take note of where things stand. This article looks at the current state through an analysis of the Ontario Court of Justice, and the decision in R. v C.L. As will become apparent, judges are doing all they can under the circumstances and any solution to the current conditions requires a renewed discussion of alternative models of court administration and judicial independence. The paper concludes with the suggestion that it is time to take a fresh look at the recommendations found in Masters in their own house and Administering Justice For the Public.

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.

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)0.004
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.622
Threshold uncertainty score0.991

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.066
GPT teacher head0.350
Teacher spread0.283 · 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