Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Purpose – This study aims to develop a newer, revised model of money laundering of general application, and to apply that updated laundering model to the use of cash in Canada. A wide-ranging analytical tool for identifying money laundering is described, which demands a comparative evaluation of available financial choices against choices made, concentrating on factors which matter most to economic enterprises: speed, cost and security. The model is applied to bulk cash money laundering and the use of cash in the Canadian context, a mature economy where cash is predominantly used for micro-payments. The inference of criminality to be drawn from bulk use of cash is explored, as is any need for continued circulation of large denomination banknotes. Design/methodology/approach – Extensive criminal investigative experience is juxtaposed with practices of legitimate commerce. As to patterns of transactional conduct, a review is undertaken of publications from financial institutions including the Bank of Canada. Findings – The model may be applied generally. In light of modern banking realities, strong inferences of criminality arise from the bulk use of cash. Research limitations/implications – Documented standards of legitimate commerce and proven laundering behaviours provide more reliable evidence than voluntary disclosures from surveys. Practical implications – The model promotes an objective analysis of financial conduct either in conjunction with, or independent of extrinsic evidence, and can augment historic lists of laundering indicators and identify new laundering typologies. Originality/value – The speed, cost and security model moves towards a renewed paradigm for understanding laundering, beyond traditional cash-based models. This instructive model applies to the full spectrum of laundering, from frauds to cash-based street crimes. By examining the inherent characteristics of financial choices, investigations may proceed without tipping off targets. The model maximizes the investigative value of know-your-customer information.
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.
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it