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Record W2072071869 · doi:10.7202/1000620ar

The Public/Private Distinction in Roncarelli v. Duplessis

2011· article· en· W2072071869 on OpenAlexaffvenueabout
Derek McKee

Bibliographic record

VenueMcGill Law Journal · 2011
Typearticle
Languageen
FieldSocial Sciences
TopicLegal principles and applications
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsPrivate lawState (computer science)LawSociologySubject (documents)Power (physics)DominionDiscretionLiberalismPolitical scienceLaw and economicsPublic lawPublic administrationPolitics

Abstract

fetched live from OpenAlex

Roncarelli v. Duplessis is remembered for the way it imposed limits on public power. But in imposing these limits, it relied heavily on public/private distinctions inherited from nineteenth-century classical liberalism. The judges invoked public/private distinctions to identify the damage Roncarelli suffered, to consider the purposes for which discretion could be validly exercised, and to determine whether Duplessis had exceeded his authority. The author argues that this proliferation of public/private concepts echoes the general indeterminacy of these ideas in liberal legal thought. Although the state/civil society distinction is central to liberal notions of public and private, it coexists with parallel thought structures, such as market/family, civilization/state, and, in Canada, dominion/province. These multiple meanings of the public and the private are mutually reinforcing. They also underwrite myths about the natural, consensual, and neutral nature of the private sphere, making it more difficult to think about controlling the exercise of private power. Although ideas about the public and the private have changed since the late nineteenth century (and since 1959), they display a remarkable persistence. Public/private distinctions can be observed at work in contemporary administrative law, in debates about which bodies are subject to judicial review, and which kinds of decisions are subject to judicial review on grounds of procedural fairness.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
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 score0.981
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0070.000
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 head0.073
GPT teacher head0.297
Teacher spread0.224 · 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.

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

Citations10
Published2011
Admission routes3
Has abstractyes

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