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Record W7047679060

How Has Dunsmuir Worked? A Legal-Empirical Analysis of Substantive Review of Administrative Decisions after Dunsmuir v. New Brunswick: Findings from the Courts of Nova Scotia, Quebec, Ontario and Alberta

2017· article· en· W7047679060 on OpenAlexaboutno aff

Bibliographic record

VenueeYLS (Yale Law School) · 2017
Typearticle
Languageen
FieldPhysics and Astronomy
TopicMagnetic confinement fusion research
Canadian institutionsnot available
Fundersnot available
KeywordsSupreme courtAdministrative lawNova (rocket)Work (physics)State (computer science)
DOInot available

Abstract

fetched live from OpenAlex

This is the final article of a three part series1 examining the impact of New Brunswick v. Dunsmuir, on how lower courts undertake substantive review of administrative action. While several later Supreme Court cases have amplified and expanded the Dunsmuir approach, the 2008 decision of Dunsmuir is regarded as the template for substantive review of administrative decision making.

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)0.066
metaresearch head score (Gemma)0.218
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.206
Threshold uncertainty score0.921

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0660.218
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0050.009
Science and technology studies0.0290.025
Scholarly communication0.0180.005
Open science0.0060.005
Research integrity0.0070.009
Insufficient payload (model declined to judge)0.0040.000

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 head0.047
GPT teacher head0.315
Teacher spread0.268 · 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 designObservational
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 routes1
Has abstractyes

Explore more

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