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Record W6992119317

Judging in the Time of a Pandemic:The Impact of COVID-19 on Bail and Sentencing in Canada

2021· article· en· W6992119317 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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueLincoln (University of Nebraska) · 2021
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicDispute Resolution and Class Actions
Canadian institutionsnot available
Fundersnot available
KeywordsAgency (philosophy)Public healthChinaGovernment (linguistics)PandemicCoronavirus disease 2019 (COVID-19)Pneumonia
DOInot available

Abstract

fetched live from OpenAlex

At “the end of 2019 the World Health Organization was alerted to several cases of pneumonia in Wuhan, China, caused by an unknown virus. On 7 January 2020, China advised the world that a new coronavirus was the cause, later labelled SARS-CoV-2. It causes the disease known as COVID-19. In mid-January 2020, the Public Health Agency of Canada activated the Emergency Operation Centre in support of Canada’s response to COVID-19. On 22 January 2020, Canada implemented COVID-19 screening requirements for travelers returning from China. On 25 January 2020, Canada confirmed its first case of COVID-19 related to travel from Wuhan, China. On 9 March 2020, Canada recorded its first death related to COVID-19” (see Taylor v. Newfoundland and Labrador, 2020 NLSC 125, at paragraphs 29 to 31).

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.066
Threshold uncertainty score0.220

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 integrity0.0000.000
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 head0.019
GPT teacher head0.222
Teacher spread0.203 · 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