Bibliographic record
Abstract
[T] he Council takes the view that the section on Financial Intelligence Units must be strengthened. The Parliamentary Assembly of the Council of Europe The national FIU is one of the main components of the global AML system. Established by individual countries, the national FIU is an expectation of the internationally agreed FATF standards. The collective group of FIUs are supported by the Egmont Group – a global semi-official organisation whose secretariat is in Canada. The number of FIUs has grown from 12 members in 1995 when it began, to 164 in 2020, as a way to generate mutual knowledge. As a depository for AML/CFT data, FIUs have gained importance thanks to increasing need for suspicious transactions or suspicious activities to be reported. Sending such reports directly to law enforcement is impractical, due to the vast size and varying levels of quality and scope. Sometimes it can also be a lack of trust in law enforcement's ability to deal with SARs sensitively or even sensibly, that has triggered a country's FIU to become the first ‘port of call’. Yet, it is here, in the FIU, where the details received can then be analysed and decisions made as to whether to take further action. The FIU acts as a buffer between law enforcement and the provider of the SAR. Still, the anticipation involved in sending a SAR to an FIU is like that of throwing a stone into a well and waiting for it to reach the bottom. Only in this instance, seldom do you ever hear the sound of any contact no matter how big the stone. As the Egmont Group highlights, for effective collection and disclosure of financial intelligence related to money laundering derived from corruption, the most important requirement is the need for FIU operational independence and autonomy. Yet for those FIUs run by law enforcement personnel, independence and autonomy can be far from realistic. Still, according to the Egmont Group there are four models of FIUs: (1) the Judicial Model which permits seizing funds, freezing accounts, conducting interrogations, detaining people and conducting searches; (2) the Law Enforcement Model that exists within law enforcement systems; (3) the Administrative Model, which is a centralised, independent, administrative authority, which receives and processes information and disseminated accordingly; and (4) the Hybrid Model that provides a disclosure intermediary and a link to both judicial and law enforcement authorities.
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 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 | 0.031 | 0.123 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.007 |
| Science and technology studies | 0.007 | 0.029 |
| Scholarly communication | 0.029 | 0.075 |
| Open science | 0.006 | 0.014 |
| Research integrity | 0.017 | 0.014 |
| Insufficient payload (model declined to judge) | 0.065 | 0.017 |
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".