Directors’ Perceptions of Board Effectiveness and Internal Operations
Bibliographic record
Abstract
We contribute to the growing literature on the effectiveness of corporate boards by examining the effect of two insights that have been largely unexplored in prior studies that use public data. First, since boards’ responsibilities are wide-ranging, more holistic performance measures may better capture the full range of their duties than specific public actions and outcomes (e.g., disclosure of risk management processes, financial restatements, acquisition returns, CEO turnover). And second, because corporate boards share many characteristics of other types of teams, their effectiveness is likely to be influenced by their internal operations. To examine the performance effects of these insights, we use data from 577 directors of U.S. public firms that responded to a survey we conducted in 2015–2016 and qualitative data from interviews of 75 directors. Our study establishes a strong relation between director perceptions of board performance effectiveness and internal board operations. Further, by highlighting the critical role of internal operations, identifying areas of relative strength and weakness in boards’ effectiveness in various activities, and probing director perceptions of their primary responsibilities, we are able to offer concrete suggestions for future research on board effectiveness. This paper was accepted by Shiva Rajgopal, accounting.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 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".