The creation of an unethical work environment: organisational outcome‐based control systems
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
While research on outcome‐based control systems (and rewards) have been shown to lead to unethical behaviour, the same cannot be said when the research focuses on specific outcome‐based control systems. Both the positive and negative research focused on the effects of moderators on the outcome‐based control system and unethical behaviour link. The relationship was dependent on ethical climate, personality traits, and internal communications. While research yielded a slightly positive result, it was shown that ethical climate was likely a stronger contributor to ethical behaviour. The influence of client fee expectations, the influence of an audit program and unethical auditor behaviour was examined. Further research was necessary to see how people of different ages responded in terms of ethics. While the empirical research did not provide a complete positive link between outcome‐based control systems and unethical behaviour, it did show that the relationship could exist and was dependent often upon other factors, such as the ethical environment of the organisation. The purpose of this article was not to show that outcome‐based control systems are always going to drive employees to behave unethically, but that these systems can lead to unethical behaviour.
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 | 0.005 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it