MétaCan
Menu
Back to cohort

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

2012· article· en· W1971874141 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueBusiness Ethics A European Review · 2012
Typearticle
Languageen
FieldSocial Sciences
TopicCrime, Illicit Activities, and Governance
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsMoney launderingNarrativePerspective (graphical)MetaphorNarrative inquirySociologyOrder (exchange)Law and economicsBusinessPolitical scienceLawPhilosophyFinanceTheologyLinguistics

Abstract

fetched live from OpenAlex

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.

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 imitation

Not 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.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.016
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.539
Threshold uncertainty score0.992

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.016
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.002
Science and technology studies0.0010.002
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.102
GPT teacher head0.368
Teacher spread0.266 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it