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Record W2752573267 · doi:10.1002/pad.1809

The Impact of Power and Civic Engagement in the Decentralized Management of Natural Resources: The Case of Turkey

2017· article· en· W2752573267 on OpenAlexfundno aff
Zeynep Kadirbeyoğlu

Bibliographic record

VenuePublic Administration and Development · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicTurkey's Politics and Society
Canadian institutionsnot available
FundersExxonMobil Research and Engineering CompanyMcGill University
KeywordsDemocratizationDecentralizationArgument (complex analysis)Natural resourcePower (physics)DemocracyPolitical scienceDistribution (mathematics)InequalityResource (disambiguation)Economic systemSociologyDevelopment economicsPoliticsEconomicsLawBiology

Abstract

fetched live from OpenAlex

Summary Decentralization is an extensively discussed topic within academic and institutional circles worldwide. While a common argument for decentralization is that it fosters democratic deepening, counterarguments cautiously point to unequal access to resources and distribution of power as factors that inhibit democratization. This study contributes to the literature on the relationship between decentralization and democratization through a comparative study of Water User Associations in two provinces of Turkey and shows in line with the literature that resource and power inequalities hamper the link between decentralization and democratization. However, as this article shows, civic engagement can generate “countervailing power” that can overcome the negative impact of such inequalities. Copyright © 2017 John Wiley & Sons, Ltd.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.054
Threshold uncertainty score0.108

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0050.005
Scholarly communication0.0030.002
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.041
GPT teacher head0.362
Teacher spread0.321 · 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

Citations12
Published2017
Admission routes1
Has abstractyes

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