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Record W2946873475 · doi:10.29173/alr2564

Instrumental Rationality and General Deterrence

2019· article· en· W2946873475 on OpenAlexvenueaboutno aff
Colton Fehr

Bibliographic record

VenueAlberta Law Review · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicCriminal Law and Evidence
Canadian institutionsnot available
FundersUniversity of OxfordOffice of National Drug Control Policy
KeywordsArbitrarinessSupreme courtRationalityCharterDeterrence (psychology)LawDeterrence theoryPolitical scienceLaw and economicsSociologyPhilosophyEpistemology

Abstract

fetched live from OpenAlex

The Supreme Court of Canada concluded in R. v. Nur that the use of general deterrence in sentencing is not “rationally connected”to its objective of lowering crime levels. Although this conclusion was drawn in the Charter section 1 context, its logic applies with equal force at the section 7 stage of analysis. As a law bearing no rational connection to its purpose is arbitrary, the author contends that judicial reliance on general deterrence in sentencing runs afoul of section 7 of the Canadian Charter of Rights and Freedoms. This conclusion is significant not only because it would forestall judicial use of general deterrence, but also for what it reveals about the relationship between the instrumental rationality principles. Commentators maintain that the Supreme Court’s “individualistic” approach to instrumental rationality resulted in the arbitrariness principle becoming subsumed by overbreadth. Yet, challenging the general deterrence provisions with overbreadth is not possible given the discretion given to judges to avoid its unnecessary application. The fact that a law can be arbitrary but not overbroad provides support for the Supreme Court’s insistence upon keeping the principles distinct. It also, however, requires that the Supreme Court adjust its position with respect to its method for proving arbitrariness.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.996
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.028
GPT teacher head0.338
Teacher spread0.311 · 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
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

Citations4
Published2019
Admission routes2
Has abstractyes

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