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Record W2525117583 · doi:10.5539/jpl.v9n8p1

Legal Analysis of the Role of Islamic Urban and Rural Councils in Administrative Decentralization and Local Democracy in Iran

2016· article· en· W2525117583 on OpenAlexvenueno aff
Mohammad Zadeh Asl Mohammad, Manoochehr Tabatabei Motameni, Heibatollah Najandimanseh, Hoseein Masudniya, Manoochehr Tavasoli Naini

Bibliographic record

VenueJournal of Politics and Law · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicLocal Government Finance and Decentralization
Canadian institutionsnot available
Fundersnot available
KeywordsDecentralizationIndependence (probability theory)Public administrationDemocracyPolitical scienceIslamLawGeographyPolitics

Abstract

fetched live from OpenAlex

Administrative decentralization is one of the most marvelous achievements of public laws in current age. Obviously, based on the title of the book namely Islamic Councils, we mean a certain type of local decentralization is shaped by geographical areas. In modern administrative laws, decentralization is raised in two geographical and technical aspects. Local councils are objective sign of geographical decentralization and legal figures of public laws such as universities are instances of technical decentralization. In this concept, decentralization is shaped by two concepts of “managerial independence” and “elective decision making authority”. In modern administrative system, decentralization means to increase the authorities of elected officials whose proficiencies are assignable only in a region of the country. Before getting familiar with such great achievement, we should address the philosophy governing decentralization and its status in modern democracies.

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)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.067
Threshold uncertainty score0.133

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0040.008
Scholarly communication0.0030.002
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.000

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 head0.012
GPT teacher head0.274
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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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
Published2016
Admission routes1
Has abstractyes

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