Determinants Of Ethical Climate In The Firm: The Role Of Governance Control Systems And Environmental Uncertainty
Bibliographic record
Abstract
Corporate governance mechanisms essentially reside in the control structure/systems of most organizations and provide, theoretically at least, a conduit to support a better organizational ethical climate. This linkage, however, has seldom been portrayed this way in the literature and, correspondingly, there are virtually no empirical studies to offer increased understanding, especially with respect to the professional accountant in practice. Accordingly, this paper empirically assesses the governance mechanisms sanctioned by the International Federation of Accountants (2009) as determinants of an organizations ethical climate based on evidence from a Canadian sample of CFOs/controllers. The ethics/leadership literature relating to ethical climate provides the theoretical underpinnings while organizational contingency theory supports examining the moderating effects of perceived environmental uncertainty (PEU). Increases in corporate governance control mechanisms are found to positively influence ethical climate. A significant relationship persists under both low and high levels of PEU but, as expected, it is much stronger when the level of PEU is low which raises concerns about how to embrace a stronger ethical climate when uncertainty is high. This paper contributes to the governance and ethics literature by providing empirical evidence that normative directives on evaluating and improving governance in organizations from global accounting authorities, such as the IFAC, are effective in shaping firms ethical climates in practice.
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 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 | 0.011 | 0.001 |
| 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 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".