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Record W1568784917 · doi:10.24908/fg.v11i1.5392

Efficiency in the Multinational Federal Republic

2014· article· en· W1568784917 on OpenAlexvenueno aff
J. P. Grégoire

Bibliographic record

VenueFederal Governance · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicLocal Government Finance and Decentralization
Canadian institutionsnot available
Fundersnot available
KeywordsPluralism (philosophy)FederalismAppealLaw and economicsSketchPoliticsAutonomyIdeal (ethics)UtilitarianismPolitical scienceSociologyEconomicsLawEpistemologyComputer sciencePhilosophy

Abstract

fetched live from OpenAlex

The paper is divided in three sections. In the first section, I question the use of the statist redistributive paradigm in federalism. In the second section, I argue that efficiency is a moral principle and that it has a strong normative appeal, especially in contexts of diversity. I show that adopting efficiency as a guiding principle to think of the role of the state, especially in contexts of pluralism, as in MNF, allows us to consider the division of competences in a way that is yet unexplored in political philosophy. Furthermore, I argue that embracing efficiency allows us to avoid the moral problems that other moral approaches encounter, especially as I will defend a non-utilitarian conception of efficiency. That also allows me to show that if one opts for the view that pictures federalism as an efficiency maximizing enterprise, it does not lead to a libertarian conception of federalism. Finally, I try to briefly sketch a possible connection between the principle of efficiency and republican ideal of ‘non-domination’ (Pettit 2012). More specifically I suggest that the pursuit of ‘non-domination’ is totally compatible with the pursuit of efficiency in MNF. In other words, the federal government can interfere to resolve government failures at the sub-unit level, for instance externalities, without being or becoming a dominating agent. The ideal of non-domination supports the sort of strong government interventions defended by egalitarians without having to compromise on the autonomy of federated entities. The combination of efficiency and non-domination ends with a defense of asymmetrical federal arrangements, without sacrificing the equality that states ought to preserve.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.897
Threshold uncertainty score0.471

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.014
GPT teacher head0.272
Teacher spread0.258 · 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
Published2014
Admission routes1
Has abstractyes

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