The Common Law Trust as a Liable Party: The Panama Case
Bibliographic record
Abstract
The economic development and evolution of globalization has brought with it the need to adopt legal-administrative measures from an intergovernmental level to prevent money laundering and the financing of terrorism. Regulators and legislators must pay special attention to those figures that allow acting on behalf of third parties without having the possibility to know who – whether a physical person or legal person – that is actually behind the legal business. The common law trust shares these characteristics and is a corporate vehicle specially monitored for having inherent money laundering risks. Roman law does not govern this legal figure, but there are similar instruments that must be considered as such and, in short, as liable parties to whom the money laundering regulations apply. It is important to highlight the case of Panama, a jurisdiction under the common law system where these instruments are frequently used to carry out not only local but also international transactions.
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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 | 0.005 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.015 | 0.012 |
| Scholarly communication | 0.010 | 0.011 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.012 | 0.010 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".