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Record W1555448376

The Unfitness of the Concept of Sovereignty to Understand Federalism

2010· article· en· W1555448376 on OpenAlexaff
Hugo Cyr

Bibliographic record

VenueSSRN Electronic Journal · 2010
Typearticle
Languageen
FieldSocial Sciences
TopicPolitical Theory and Influence
Canadian institutionsUniversité du Québec à Montréal
Fundersnot available
KeywordsSovereigntyFederalismNormativePoliticsArgument (complex analysis)Political scienceLaw and economicsPopular sovereigntyState (computer science)EpistemologyLawSociologyPhilosophyComputer science
DOInot available

Abstract

fetched live from OpenAlex

Since Jean Bodin, has been taken as the defining feature of the State. Nonetheless, there always has been dissenting voices challenging the general usefulness of that concept for understanding any political entity to which one might be tempted to apply it. Sovereignty has also been under attack on various normative grounds. This paper does not aim at making a general argument against the concept of sovereignty but rather attempts to demonstrate that, whatever its usefulness to understand other political entity, the concept of sovereignty is unfit to enter any explanation of the federation. In particular, this paper examines three types of strategies developed in the hope of being able to reconcile the concept of sovereignty and the political and legal phenomenon that we call federalism. The first two types attempt such reconciliation through radical changes in the meaning of one or the other of the terms while the third type of attempts hope to solve the riddle by introducing a third term that would mediate between the unity entailed by the concept of sovereignty and the multiplicity that defines federalism. This paper shows why all such attempts are doomed to fail. Ultimately, this means that we either have to no longer think of federal entities as States – and option that I reject – or that we have to reconsider what makes a State a State.

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)0.003
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: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.060
Threshold uncertainty score0.711

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.010
GPT teacher head0.291
Teacher spread0.281 · 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

Citations0
Published2010
Admission routes1
Has abstractyes

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