Ethical Challenges of Complex Products: Case of Goldman Sachs and the Synthetic Collateralized Debt Obligations
Bibliographic record
Abstract
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.
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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 | 0.007 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.018 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.006 | 0.005 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".