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Record W2618804890 · doi:10.7202/1039831ar

L’architecture constitutionnelle — Dimensions artistiques d’une construction juridique

2017· article· fr· W2618804890 on OpenAlexaffvenueabout
Dave Guénette

Bibliographic record

VenueLes Cahiers de droit · 2017
Typearticle
Languagefr
FieldSocial Sciences
TopicLaw in Society and Culture
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsHumanitiesArtConstitutionPhilosophyPolitical scienceLaw

Abstract

fetched live from OpenAlex

Le concept d’architecture constitutionnelle, incontournable en droit canadien depuis les renvois de 2014 relatifs à la Cour suprême du Canada et au Sénat, offre une représentation nouvelle de la structure de la Constitution du pays. Or, au-delà de sa pertinence juridique, ce concept se démarque également de par ses dimensions de nature créative et artistique. En premier lieu, cette conception jette un regard nouveau sur la structure de la Constitution du Canada à travers le prisme de l’art qu’est l’architecture. Ce faisant, elle offre une image innovatrice de l’organisation constitutionnelle, prenant directement ses racines dans la littérature qui aborde la structure du système juridique par une représentation en réseau. En second lieu, en raison de son utilisation du procédé de la métaphore, l’image de l’architecture constitutionnelle s’inscrit également dans une vaste tendance en droit à se représenter des concepts complexes à l’aide de ce type de figure de style. Elle est ainsi le plus récent exemple de cette tendance.

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)0.002
metaresearch head score (Gemma)0.003
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 score0.242
Threshold uncertainty score0.481

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0100.038
Scholarly communication0.0140.006
Open science0.0010.003
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0110.001

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 head0.010
GPT teacher head0.258
Teacher spread0.248 · 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

Citations1
Published2017
Admission routes3
Has abstractyes

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