Bibliographic record
Abstract
Purpose – The purpose of this paper is to describe philosophical positions about money laundering activities, depending on the way one looks at ethics and law. Design/methodology/approach – The paper analyzes four philosophical positions about money laundering activities, given that one accepts/refuses to make connections between ethics and law. It explores the pitfalls of each philosophical position. Findings – The sceptical way (ethical relativism) asserts that there cannot be any intrinsic notion of good/evil. The legally focused way (legal positivism) presupposes that ethics is irrelevant, when lawmakers are doing their job. The distorting way (legal moralism) takes for granted that lawmakers are deciding what is moral/immoral. The ethically focused way (normative ethics) means that ethics say something different than law. Each of the four philosophical positions about money laundering has its own pitfalls. Practical implications – The four philosophical positions could influence the way ethical concerns are institutionalized in the organizational setting. Managers could better distinguish ethical discourse and legal/judicial realm. Ethical training sessions could be used to make organizational members circumscribing their moral duties, as to the detection/prevention of money laundering activities. Qualitative surveys could help to better understand if such philosophical positions are relevant for decision-making processes and philosophical questioning about ethical issues. Originality/value – The paper addresses the issue of money laundering, from both a legal and moral perspectives. It is at the edge of ethics and philosophy of law.
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 | 0.015 | 0.043 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.043 |
| Scholarly communication | 0.010 | 0.010 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.008 | 0.008 |
| Insufficient payload (model declined to judge) | 0.005 | 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".