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Record W2605427376

The Court and Administrative Law: Models of Rights Protection

2017· article· en· W2605427376 on OpenAlexaffabout
Paul Daly

Bibliographic record

VenueSSRN Electronic Journal · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicJudicial and Constitutional Studies
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsProportionality (law)DeferenceCharterUltra viresPolitical scienceAdministrative lawLawJudicial reviewJudicial deferencePublic lawCommon lawConstitutional lawLaw and economicsEconomicsDoctrine
DOInot available

Abstract

fetched live from OpenAlex

My goal in this essay is to identify the models of rights protection that have existed in Canadian judicial review of administrative action, to assess their advantages and disadvantages, and to suggest future pathways for the development of rights protection in Canadian public law. I identify three current and past models: the vires model, from the pre-Charter era; the proportionality model, from the early-Charter era; and the deference model, which is currently in use. Assessing the advantages and disadvantages of these models allows me to set out an alternative model – the public law model – which draws on the strengths of both administrative law and constitutional law to provide enhanced judicial protection for rights. In the public law model, the proportionality model is retained, such that the Oakes test is applied to assess the proportionality of infringements of the Charter, but the vires model is enhanced to strengthen the protection of rights, such that the animating concern of the deference model – that administrative law be given a proper role in rights protection – is taken into account. The lesson of my survey of models of rights protection is that the vires model, the proportionality model and the deference model all have some advantages but also have disadvantages. A consideration of their relative merits leads to the conclusion that a public law model, with its combination of ex ante and ex post controls, would provide superior protection to Charter rights liable to be infringed by administrative decisions.

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)0.011
metaresearch head score (Gemma)0.018
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.380
Threshold uncertainty score0.756

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.018
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.005
Science and technology studies0.0050.038
Scholarly communication0.0160.014
Open science0.0050.004
Research integrity0.0050.005
Insufficient payload (model declined to judge)0.0120.001

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 head0.041
GPT teacher head0.318
Teacher spread0.277 · 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 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

Citations0
Published2017
Admission routes2
Has abstractyes

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