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Record W2585227310 · doi:10.29173/mlj996

Reforming and Resisting Criminal Law: Criminal Justice and the Tragically Hip

2017· article· en· W2585227310 on OpenAlexaffabout
Kent Roach

Bibliographic record

VenueManitoba Law Journal · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicLaw in Society and Culture
Canadian institutionsUniversity of Toronto
FundersBerkeley Charitable Foundation
KeywordsImprisonmentLawNormativeInnocenceCriminal lawCriminal justiceLife imprisonmentPresumption of innocencePolitical scienceCriminologySociologyEconomic JusticePrison

Abstract

fetched live from OpenAlex

This paper examines two Tragically Hip songs, 38 Years Old and Wheat Kings, with a view to understanding how they can be interpreted as a call both to reform and resist criminal law.In a reformist spirit, 38 Years Old can be interpreted as an imaginary hypothetical that suggests that judges should be able to devise exemptions from all mandatory sentences, including life imprisonment for murder.The song can also be interpreted as a demonstration that imprisonment must be resisted and endured by offenders and their families because it will always be violent and destructive.Wheat Kings similarly can be interpreted as a call to reform remedies for the wrongly convicted and to make legal determinations of innocence.At the same time, Wheat Kings exonerated David Milgaard in 1992 long before the Canadian legal system did.In doing so, it illustrates how art, like media and science, can resist the coercive conclusions of the criminal law and can make normative conclusions that can be seen as a form of law.

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)0.002
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.826
Threshold uncertainty score0.346

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0200.038
Scholarly communication0.0070.003
Open science0.0010.004
Research integrity0.0030.004
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 head0.315
Teacher spread0.261 · 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 designQualitative
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

Citations3
Published2017
Admission routes2
Has abstractyes

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