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Record W3029784750 · doi:10.5539/ibr.v13n6p115

Ethical Challenges of Complex Products: Case of Goldman Sachs and the Synthetic Collateralized Debt Obligations

2020· article· en· W3029784750 on OpenAlexvenueno aff
Franklin M. Lartey

Bibliographic record

VenueInternational Business Research · 2020
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic Theory and Institutions
Canadian institutionsnot available
Fundersnot available
KeywordsCollateralized debt obligationBusiness ethicsProduct (mathematics)EconomicsMoral obligationStakeholderShareholderLaw and economicsSociologyBusinessLawPolitical scienceCorporate governanceManagementFinance

Abstract

fetched live from OpenAlex

In analyzing complex products, this study selected the company Goldman Sachs and one of its product offerings, the synthetic collateralized debt obligation (synthetic CDO). The study later analyzed the ethical implications of providing such a complex product to customers. A review of the literature indicates that researchers identified this product and other associated derivatives of the mortgage backed securities as the main causes of the 2008 financial crisis in the United States of America. As such, Goldman Sachs’ offering of the product posed ethical and moral issues. An analysis of the company and its offering was done under the lenses of various ethical theories such as Kohlberg's theory of moral reasoning, the Kantian ethics, the utilitarian perspective, Friedman’s shareholder theory, the stakeholder theory, the market approach to consumer protection, and the contract view of consumer protection. Besides Friedman’s shareholder theory, all other theories judged the product offering morally wrong and unethical. At the end of the study, the author suggested a contribution to knowledge regarding Kohlberg’s theory of moral reasoning in its application to organizations. The author also suggested further research to validate the outcome of Friedman’s shareholder theory regarding this case.

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 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)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.251
Threshold uncertainty score0.349

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.206
GPT teacher head0.353
Teacher spread0.147 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
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".

Quick stats

Citations6
Published2020
Admission routes1
Has abstractyes

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