The moral discourse of banks about money laundering: an analysis of the narrative from <scp>P</scp>aul <scp>R</scp>icoeur's philosophical perspective
Why this work is in the frame
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Bibliographic record
Abstract
In this paper, we will use R icoeur's philosophy in order to present money laundering as a metaphor and a narrative. We will firstly analyze the corporate moral discourse of 10 banks about money laundering. We have selected 10 banks that have codes of ethics and a corporate moral discourse about money laundering. The banks come from six countries: U nited S tates (2), C anada (2), S witzerland (2), S pain (2), G ermany (1), and B elgium (1). We will see how their moral discourse about money laundering contributes to deepen the understanding of money laundering as a narrative. Then, we will see to what extent R icoeur's philosophy could help us to better understand the moral discourse of banks. We will describe the main components of money laundering as a narrative.
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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 | 0.005 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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