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Record W2588787282 · doi:10.60082/2563-8505.1339

"Chartering" in the Shadow of Lochner: Guindon, Goodwin and the Criminal-Administrative Distinction at the Supreme Court of Canada

2016· article· en· W2588787282 on OpenAlexaffabout
Steven Penney

Bibliographic record

VenueSupreme Court law review · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicCriminal Law and Evidence
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsWrongdoingSupreme courtLawPolitical scienceAdministrative lawStatutory lawShadow (psychology)State (computer science)Criminal lawPower (physics)Psychology

Abstract

fetched live from OpenAlex

The distinction between criminal and administrative wrongdoing plays a key role in Canadian public law. Though it functions somewhat differently across domains, the upshot is the same: the state is presumptively entitled, as a principle of statutory and constitutional interpretation, to more favourable procedures for establishing administrative wrongdoing than criminal offending. Conversely, people accused of administrative infractions are presumptively entitled to less protection against state power in the investigative and adjudicative process than those charged with crimes (or in many cases, regulatory offences). The criminal-administrative distinction has a long pedigree, but has taken on heightened importance since the Charter. The entrenchment of the Charter’s “legal rights” provisions emboldened lawyers to claim the same procedural protections for persons accused of non-criminal wrongdoing that statute and common law had typically (but not universally) provided to criminal defendants. With few exceptions, these claims have failed. Despite long-standing criticism of its doctrinal coherence and policy justifications, the Supreme Court of Canada has repeatedly confirmed the distinction’s vitality and applied it to deny Charter challenges by persons deemed to be operating in the administrative sphere. The Court has been far more willing, in contrast, to find Charter violations in the criminal context.

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)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.911
Threshold uncertainty score0.643

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.054
GPT teacher head0.323
Teacher spread0.269 · 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.

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

Citations1
Published2016
Admission routes2
Has abstractyes

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