Code of ethics quality: an international comparison of corporate staff support and regulation in <scp>A</scp>ustralia, <scp>C</scp>anada and the <scp>U</scp>nited <scp>S</scp>tates
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 objective of this paper is to examine the ‘ C ode of E thics Q uality’ ( CEQ ) in the largest companies of A ustralia, C anada and the U nited S tates. For this purpose, a proposed CEQ construct has been applied. It appears from the empirical findings that while A ustralia, C anada and the U nited S tates are extremely similar in their economic and social development, there may well be distinct cultural mores and issues that are forming their business ethics practices. A research implication derived from the performed research is that the construct provides a selection of observable and measurable elements in the context of CEQ . The construct of CEQ consists of nine measures divided into two dimensions (i.e. staff support and regulation). They should not be seen as a complete list. On the contrary, it is encouraged that others propose and elaborate revisions and extensions. A practical implication of this paper is a structure of what and how to examine the CEQ in a managerial setting. It may assist companies in their efforts to establish, maintain and improve their ethical culture, norms and beliefs within the organization and supporting them in their ethical business practices with different stakeholders in the marketplace and society. The dimensions and measures of the construct may be used as a frame of reference for further research. They may be useful and applicable across contexts and over time using similar samples when it comes to large companies, as small‐ or medium‐sized ones may not have considered all areas nor have the elements in place. This is a research limitation, but it provides an opportunity for further research.
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 | 0.044 | 0.192 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.000 | 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