MétaCan
Menu
Back to cohort
Record W4285359999 · doi:10.51325/ijbeg.v4i3.83

<b>Legal Frameworks for Financial Corruption in the State of Kuwait </b><b></b>

2021· article· en· W4285359999 on OpenAlexaff
Melfi Mohammad Al Azemi, Mohammad M. Alazemi

Bibliographic record

VenueEuroMid Journal of Business and Tech-innovation (EJBTI) · 2021
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicIslamic Finance and Banking Studies
Canadian institutionsCouncil of Ministers of Education
Fundersnot available
KeywordsMoney launderingLanguage changeSeriousnessFinanceBusinessGovernment (linguistics)Financial institutionAccountingPolitical scienceLaw

Abstract

fetched live from OpenAlex

The study aimed to identify the legal frameworks shaping financial corruption in Kuwait. Corruption is a serious disease, rapid in contagion and spread, and slow in diagnosis and treatment, and it requires considerable effort, time, and cost to combat and reduce it. It does not require only specific steps, but rather it necessitates the existence of legitimate and legal foundations. Thus, this study deals with the legal foundations for financial corruption in Kuwait from two perspectives, namely, the legal frameworks for financial corruption and the scope of criminalization of financial corruption in Kuwait. The qualitative approach was used by analyzing official reports, collecting data and figures through a range of means such as interviews and observations, and measuring the corruption index during the past ten years in Kuwait. The results of the research found a high level of a financial corruption index in Kuwait, which has been intensifying during the past ten years through various manifestations, such as money laundering, manipulation and abuses of sovereign funds to invest in suspicious projects, real estate fraud against citizens, and issues related to the investment of the Public Institution for Social Security’s funds (pension funds), etc. Finally, the research concluded with a set of recommendations and proposals at the criminal level about the seriousness of financial corruption on the individual and society level, in addition to the required development and the government's efforts to address the phenomenon of the spread of financial corruption in this country.

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 categoriesMeta-epidemiology (narrow)
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 score0.555
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.004
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
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 head0.015
GPT teacher head0.228
Teacher spread0.213 · 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.

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

Explore more

Same venueEuroMid Journal of Business and Tech-innovation (EJBTI)Same topicIslamic Finance and Banking StudiesFrench-language works237,207