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Record W3167930728 · doi:10.6000/1929-4409.2021.10.107

The Effectiveness of Gratification Arrangements as Part of Corruption Crimes in Indonesia: A Theoretical Study in Talcott Parsons Perspective

2021· article· en· W3167930728 on OpenAlexvenueno aff
Teddy Asmara

Bibliographic record

VenueInternational Journal of Criminology and Sociology · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicIndonesian Legal and Regulatory Studies
Canadian institutionsnot available
Fundersnot available
KeywordsGratificationLanguage changeNormativePerspective (graphical)Law and economicsLawPolitical scienceSociologyPositive economicsEconomicsPsychologySocial psychologyComputer science

Abstract

fetched live from OpenAlex

This research aims to examine the crime of gratification as part of the criminal act of corruption, which will be seen in Talcott Parson's perspective. Corruption today is a problem for developing countries and has become a world problem that requires integral and transnational handling. One of the most disclosed forms of corruption today is corruption in the form of gratuities. This research method uses normative juridical research with the approach of laws, concepts, and principles and collects primary legal material in the form of Law 20 of 2001 concerning Amendments to Law Number 31 of 1999 concerning Eradication of Corruption Crimes. The results of this study found that the Cybernetics Theory, which Talcott Parsons coined, views the problem of alleged gratification as being strongly influenced by the economic sub-system, this is because a decision that is made has a significant impact on anyone, so it is not surprising if there is a lot of price bargaining. Moreover, the least impact is the cultural sub-system because this sub-system is only the economic sub-system's impact.

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)0.002
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 score0.546
Threshold uncertainty score0.685

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.002
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 head0.039
GPT teacher head0.368
Teacher spread0.329 · 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

Citations2
Published2021
Admission routes1
Has abstractyes

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