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Record W3207141996 · doi:10.3138/cpp.2021-015

Imagining Resilient Courts: from COVID-19 to the Future of Canada’s Court System

2021· article· en· W3207141996 on OpenAlexvenueaboutno aff
David Matyas, Peter Wills, Barry Dewitt

Bibliographic record

VenueCanadian Public Policy · 2021
Typearticle
Languageen
FieldHealth Professions
TopicMedical Malpractice and Liability Issues
Canadian institutionsnot available
Fundersnot available
KeywordsCoronavirus disease 2019 (COVID-19)Resilience (materials science)Political scienceReflexivityDemocracyEconomic JusticePandemicWork (physics)Business as usualLawSociologyLaw and economicsPublic administrationEconomicsManagementPoliticsEngineeringSocial scienceMedicine

Abstract

fetched live from OpenAlex

The coronavirus disease 2019 (COVID-19) pandemic has challenged an array of democratic institutions in complex and unprecedented ways. Little academic work, however, has considered the pandemic's impact on Canada's courts. This article aims to partially fill that gap by exploring the Canadian court system's response to COVID-19 and the prospects for administering justice amid disasters, all through the lens of resilience. After taking a forensic look at how the court system has managed the challenges brought on by COVID-19, we argue that features of resilience such as self-organization, flexibility, learning, and reflexive planning can contribute to the administration of justice during future shocks. We propose that the business of judging during shocks can become more integral to the business as usual of court systems. Imagining such a resilient court can be a way to step from COVID-19 to the future of Canada's court system.

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)0.001
metaresearch head score (Gemma)0.012
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: none
Teacher disagreement score0.829
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.012
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.042
GPT teacher head0.386
Teacher spread0.344 · 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
GenreCommentary

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

Citations11
Published2021
Admission routes2
Has abstractyes

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