Does More Corporate Governance Enhance Managerial Performance? CFO Perceptions And The Role Of Mindfulness
Bibliographic record
Abstract
The results of studies into the effects of enhanced governance structures have been equivocal and there is virtually no literature on the performance effects of individual managers, such as the professional accountant in practice. This paper reports the results of an empirical study designed to assess the relationship of governance structures, specifically the conformance and performance dimensions defined by the International Federation of Accountants (2009), to mindfulness and managerial performance among CFOs in Canadian firms. Organizational theory describing high reliability organizations provides the theoretical framework for specifying and appraising capacity for mindfulness. As predicted, there is no significant direct relationship between governance and managerial performance for the conformance dimension; instead, this relationship is explained by the path through capacity for mindfulness and on to managerial performance, both of which are positively significant. Likewise, there is no significant relationship between governance and managerial performance for the conformance dimension; however, although there is a significant path between the performance dimension and capacity for mindfulness, the path from the latter to managerial performance is insignificant. Implicating the powerful role of the controllability principle in accounting may explain this unexpected finding.
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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 | 0.002 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".