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Record W609296528

Financial Misconduct, Settlement Penalties and Corporate Governance Accountability

2014· article· en· W609296528 on OpenAlexaff
Matthew P. Ponsford

Bibliographic record

VenueuO Research (University of Ottawa) · 2014
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicInsurance and Financial Risk Management
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsMisconductAccountabilityRedressSettlement (finance)Corporate governanceDuty of careWrongdoingLawBusinessContext (archaeology)CorporationAccountingStatuteLiabilityShareholderPolitical scienceFinancePayment
DOInot available

Abstract

fetched live from OpenAlex

Recently, JPMorgan Chase paid over $20 billion in settlement penalties, including $1.7 billion for violating the United States' Bank Secrecy Act, 1970 (BSA; "the Act") which required the corporation to report suspicious financial activity related to Bernard L. Madoff -a man who orchestrated the largest Ponzi scheme in history.Key study questions: (1) Is JP Morgan Chase legally responsible through common law principles of duty of care, in the larger framework of negligence?(2) Is the duty of care contained in the BSA?(3) If duties requiring banks to alert authorities of suspicious activity are breached through governing statute, does the Act impose personal liability for executives?Do shareholders have adequate means for redress or are they "helpless victims"?METHODOLOGY Examination of Misconduct Reports Examination of Corporate Disclosures & Deferred Prosecution Agreement Analysis of Relevant Jurisprudence  International

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 imitation

Not 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.

metaresearch head score (Codex)0.012
metaresearch head score (Gemma)0.078
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.063

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0120.078
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0030.010
Scholarly communication0.0040.005
Open science0.0010.003
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0100.001

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.

Opus teacher head0.083
GPT teacher head0.254
Teacher spread0.171 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

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".

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Citations0
Published2014
Admission routes1
Has abstractyes

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