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Record W4395659648 · doi:10.24857/rgsa.v18n9-027

State Financial Corruption and its Impact on Development

2024· article· en· W4395659648 on OpenAlexaff
Hendra Karianga

Bibliographic record

VenueRevista de Gestão Social e Ambiental · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicCorruption and Economic Development
Canadian institutionsImpact
Fundersnot available
KeywordsLanguage changeState (computer science)Financial systemBusinessFinanceComputer science

Abstract

fetched live from OpenAlex

Purpose: This research aims to analyze the impact of corruption on individual and community development, economics and politics as well as public sector services. Methode: The type of research used is normative legal research using an analytical approach. Result and Conclusion: The impact of corruption on individual and community development, economics and politics as well as public sector services, namely the Impact of Corruption on Individual and Community Development can trigger people's distrust of the government. This triggers public apathy towards the programs being or will be planned by the government. Eliminating the nature of cooperation between the community and the government. The Impact of Corruption on Economic Development sluggish economic growth and investment, decreasing productivity, low quality of goods and services, decreasing state income from the tax sector, and rising national debt. The impact of corruption on political development hampers the government's function as the guardian of state policy because it hampers the government's role in regulating allocations, equalizing access and assets, and maintaining economic and political stability. The impact of corruption on public sector services causes bureaucracy to become inefficient and causes higher administrative costs.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.817
Threshold uncertainty score0.626

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.023
GPT teacher head0.331
Teacher spread0.308 · 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 designOther design
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

Citations4
Published2024
Admission routes1
Has abstractyes

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