Disguised Foreign Controlled Companies and the Facilitation of Transnational Criminal Activities in Thailand
Bibliographic record
Abstract
The primary objectives of the study are to examine the role of a business using Thai nationals as nominee shareholders in foreign-controlled companies in the facilitation of the transnational criminal groups’ activities in the tourist destinations, and their social and economic impacts on the country. Nominee shareholder appointment in a legal entity has commonly been recognized as one of the techniques employed by criminal groups to launder and obscure the ownership of their illegal assets. However, this study points out that this type of company also performs other functions in providing resources and a platform for criminal groups to further their goals. The study used mixed methods by gathering qualitative data through conducting in-depth interviews and focus groups with 55 participants from relevant government agencies and private sectors, and by gathering quantitative data through conducting public surveys consisting of 1,160 participants from six provinces across five different regions in Thailand. The study concluded that there is a strong need for the country to improve monitoring mechanisms through legal changes, and collaborations among public, private and civil society as the practice of nominee shareholder appointment, although perceived as a normal practice in the global field of business, such a practice can invite unintended consequences, which can be a serious cause of concern due to the links with illegal activities operated under the umbrella of transnational organized crime.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.006 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.000 | 0.004 |
| Research integrity | 0.001 | 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".