Changes to Corporate Codes of Ethics: A Twelve-Year Analysis
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.
Bibliographic record
Abstract
The Enron scandal caused companies and their Board of Directors to reconsider how they were utilizing their code of ethics, especially after the legislation of the Sarbanes-Oxley Act of 2002. Enron's Board of Directors provided the CFO, Andy Fastow, with a waiver of the code of ethics to negotiate with himself, while also on behalf of Enron. The issue with this waiver was that, at the time, investors were left in the dark because they did not need to be notified about any changes or exceptions made to the code of ethics. After learning about why codes of ethics and any changes to them needed to be disclosed, I looked at all the changes made to companies' codes of ethics over the last twelve years and classified them. I classified the types of changes into either a waiver, an amendment, a new code of ethics, or other. From the classified data, I was able to discover two main trends: most changes are made during the fourth quarter of the year, and the number of amendments has been decreasing while the number of new codes of ethics is increasing.
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 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 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