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DECENTRALIZATION OF THE SYSTEM OF PUBLIC ADMINISTRATION IN UNITARY AND FEDERAL STATES: COMPARATIVE LEGAL ANALYSIS

2023· article· en· W4391391289 on OpenAlexaboutno aff
Sukhrob Alimuxamedov

Bibliographic record

VenueReview of Law Sciences · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicLegal and Policy Issues
Canadian institutionsnot available
Fundersnot available
KeywordsDecentralizationUnitary statePublic administrationInstitutionAdministration (probate law)FederalismState (computer science)Government (linguistics)Central governmentLocal governmentPolitical scienceAdministrative lawPoliticsLaw

Abstract

fetched live from OpenAlex

The article provides a comparative legal analysis of the process of decentralization of the public administration system in unitary and federal states and also reveals its role in increasing the efficiency of local government authorities. The concepts of a unitary and federal state are revealed, as well as the relationship between central government bodies and local executive authorities, taking into account the administrative-territorial division of the state. The development of the institution of decentralization in Anglo-Saxon and continental systems of law is analyzed. The economic and social factors that influence the effectiveness of decentralization of the public administration system in unitary and federal states are revealed. The principles of decentralization of the public administration system and the prerequisites and reasons for the transfer of powers to local government bodies are analyzed, taking into account the unitary and federal administrative-territorial divisions. The development of the institution of decentralization in countries such as France, Japan, Italy, the USA, Canada, and Germany is regulated in detail.

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)0.004
metaresearch head score (Gemma)0.013
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.029
Threshold uncertainty score0.080

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.013
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0060.007
Science and technology studies0.0030.006
Scholarly communication0.0030.004
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.118
GPT teacher head0.429
Teacher spread0.310 · 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 designNot applicable
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
Published2023
Admission routes1
Has abstractyes

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