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Record W1606825656

Can There Be Too Much Context In Administrative Law? Setting the Standard of Review in Canadian Administrative Law

2014· article· en· W1606825656 on OpenAlexaffabout
Andrew Green

Bibliographic record

VenueTSpace · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicCriminal Law and Evidence
Canadian institutionsUniversity of Toronto
FundersUniversity of Cambridge
KeywordsSupreme courtStandard of reviewLegislatureJudicial reviewContext (archaeology)Political scienceLawCategorical variableAdministrative lawOrder (exchange)Perspective (graphical)Judicial opinionLaw and economicsSociologyEconomicsComputer science
DOInot available

Abstract

fetched live from OpenAlex

The Supreme Court of Canada has periodically altered its approach to judicial review in order to make it more coherent and easier for courts and litigants to understand. Central to judicial review is the choice of the standard of review a court is to apply in a particular case. The standard of review determines how deferential the court is to be to the executive decision-maker. The Court has shifted over time from a formal to a contextual approach to this choice and, most recently, at least partly towards a categorical approach. This most recent approach has been criticized as overly formalistic, neglecting important aspects of the context of particular decisions. This paper examines this shift in the process for choosing the standard of review from an institutional perspective. It discusses the factors that are important in selecting an approach to choosing the standard of review in a particular case. These factors include both the implications for the actual decision at issue as well as the effect on the decisions of other executive decision-makers, lower courts, individuals seeking to challenge decisions and the legislature.

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)0.002
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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.920
Threshold uncertainty score0.364

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.092
GPT teacher head0.429
Teacher spread0.337 · 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

Citations3
Published2014
Admission routes2
Has abstractyes

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