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Record W3107770851 · doi:10.3138/utlj.2020-0056

A unified model of public law: Charter values and reasonableness review in Canada

2020· article· en· W3107770851 on OpenAlexaffvenueabout
Richard Stacey

Bibliographic record

VenueUniversity of Toronto Law Journal · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicJudicial and Constitutional Studies
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsCharterSupreme courtAdministrative lawProportionality (law)JurisprudenceLawNormativeJudicial reviewPolitical scienceConstitutional lawLaw and economicsSociology

Abstract

fetched live from OpenAlex

The Supreme Court of Canada concluded in its 2012 judgment in Doré that the rational connection test and the less restrictive means inquiry from the Oakes analysis are not useful when assessing the justifiability of administrative decisions limiting Charter rights. The Court instead articulated a ‘robust’ conception of proportionality that requires administrative decision makers to demonstrate only that any rights limitations that their decisions impose are proportionate ‘in the strict sense.’ This article argues that Charter values should be understood as part of a normative hierarchy of ‘justificatory resources’ to which administrative decision makers can refer in justifying rights-limiting decisions as proportionate in the strict sense. It argues further that the robust, reasons-first conception of reasonableness that the Court described in Vavilov affirms Doré’s logical architecture, marking a shift in Canadian jurisprudence toward a ‘culture of justification.’ In adopting the same approach to constitutional decisions affecting Charter rights and administrative decisions that do not engage the Charter, Doré and Vavilov construct a unified model of public law in which all public decisions must be shown to be justified by their congruence with a hierarchy of norms which has Charter values at its apex. In this unified model of public law, in which a robust conception of reasonableness is central, it is not clear what room, or need, is left for correctness review.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.924
Threshold uncertainty score0.262

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)0.0000.000

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 head0.040
GPT teacher head0.229
Teacher spread0.188 · 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 designTheoretical or conceptual
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

Citations2
Published2020
Admission routes3
Has abstractyes

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