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Record W4387489894 · doi:10.29173/cjs29889

The More Things Change, the More They Stay the Same: The Obdurate Nature of Pandemic Bail Practices

2022· article· en· W4387489894 on OpenAlexaffvenueabout
Nicole M. Myers

Bibliographic record

VenueThe Canadian Journal of Sociology · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicCriminal Justice and Corrections Analysis
Canadian institutionsQueen's University
Fundersnot available
KeywordsPunitive damagesPunishment (psychology)Space (punctuation)LawSociologySuretyProcess (computing)Political scienceLaw and economicsCriminologyPsychologyComputer scienceSocial psychology

Abstract

fetched live from OpenAlex

In an unprecedented move, the criminal courts in Ontario closed on March 20th, 2020 in response to the COVID-19 pandemic. Bail appearances, however, could not be suspended, resulting in the rapid move to virtual appearances. Despite the dramatic change in the modality of court appearances, remarkably little changed in how the bail court operated or processed bail matters. Observations from 80 days of virtual bail court reveal the obdurate nature of well know issues with the bail process, including the culture of adjournment, reliance on surety supervision, and numerous conditions of release. Problematically, the courts are closed to the public and the accused are rendered invisible in the virtual space, leaving them even more dependent on counsel and the court. Differences in access to technology and private space create additional barriers for the most marginalized. Consistent with Feeley’s assessment that ‘the process is the punishment,’ the virtual model has layered new punitive elements onto an already punishing experience.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.781
Threshold uncertainty score0.436

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0170.037
Scholarly communication0.0100.006
Open science0.0010.006
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0030.000

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 head0.054
GPT teacher head0.350
Teacher spread0.297 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations6
Published2022
Admission routes3
Has abstractyes

Explore more

Same venueThe Canadian Journal of SociologySame topicCriminal Justice and Corrections AnalysisFrench-language works237,207