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Record W6983149909

Les droits des minorités et la répartition des compétences dans les Etats fédéraux : essai de synthèse au départ des expériences belge et canadienne

2009· dissertation· en· W6983149909 on OpenAlexaboutno aff

Bibliographic record

VenueDIAL (Catholic University of Leuven) · 2009
Typedissertation
Languageen
FieldSocial Sciences
TopicPolitical Systems and Governance
Canadian institutionsnot available
Fundersnot available
KeywordsConstitutionLegislatureFundamental rightsInterpretation (philosophy)Object (grammar)Perspective (graphical)Order (exchange)State (computer science)
DOInot available

Abstract

fetched live from OpenAlex

This study focuses on the rights of linguistic and religious minorities in federal States.\nFirst, it begins with an exploration of the “internal” (i.e. the protection of fundamental rights in federal States) and “external” (i.e. the status of federal States in international (human rights) law) dimensions of the issue.\nThen, it analyses interactions between minority rights and the division of powers in these States. For this purpose, it relies on two complementary perspectives. The first one focuses on minority rights and shows that they constitute substantial limits to the federal and federate authorities’ exercise of powers. The second perspective concentrates on the constitutional norms dividing legislative powers and emphasizes that the protection of minority rights may represent either the stakes or an object of the division of powers. In the former case, the mere existence of such rights can explain particular aspects of the division of powers, while in the latter the Constitution expressly gives federal authorities the responsibility to protect certain rights.\nThe thesis underlines the various consequences of each of these configurations on the judicial interpretation of minority rights. In order to illustrate these observations, it mainly focuses on two legal orders: Belgium and Canada.

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 categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.735
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0020.002
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.040
GPT teacher head0.302
Teacher spread0.262 · 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 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
Published2009
Admission routes1
Has abstractyes

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