<b>The Reality of Financial Corruption in Kuwait: A Procedure Research According to Corruption Perception Index &amp; Related Rules</b>
Bibliographic record
Abstract
The study aimed at highlighting the reality of financial corruption in accordance with the corruption perception index and some other related rules in the state of Kuwait. The study covered the international and local reports showing the levels of financial corruption in Kuwait and its impacts on the economic development within the period from 2003 to 2019. The results indicated that there is a high indicator of financial corruption in the State of Kuwait that started to increase during the last ten years in all of it aspects including issue of money laundering, bypasses, manipulating the money of sovereign fund to invest in suspicious projects, the real-estate swindle, issues related to investing the money of the Public Institution of Social Insurance (retirement sums) and so on. The researchers got to a group of recommendations and proposals in both penal and Shariaa sides including activating the religious speech in all types of media, tribunes of mosques as well as all religious institutions about the danger of financial corruption on individual and society. It is also by warning people about out God punishment against every spoiler, activating the role of religion members in all attempts of government to fight the financial corruption phenomenon in the state with definitely adherence to the Islamic law principles in all financial issues of the state, agreements and so on. Moreover, it is very necessary to activate the most extreme laws and penalties against perpetrators of financial corruption without and exception.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".