Bibliographic record
Abstract
This paper examines the effect of key board distinctiveness on managerial risk-taking behaviour. Using a total sample of 121 firms made up of 1,166 corporate directors and 847 firm-year observations, the study finds robust evidence across the three stages of estimation that suggests power separation in terms of CEO non-duality is negatively associated with executive risk-taking due to enhanced board assertiveness and independence. Board size is inversely associated with the variability of market value measure both within and at inter-firm levels. With average board membership in the study sample made up of 10 directors, the study finds crucial empirical evidence that points to the key benefits of large board configuration including the social capital, diversity of thoughts, knowledge, and experience, effectiveness and vigilance which curtails executive entrenchment. In contrast, the paper records positive association between the presence of foreign directors and corporate risk-taking. Due to their wealth of experiences, foreign directors tend to have more strategic sense of purpose and are likely not to hesitate in taking appropriate risk decisions when it really matters. While the paper finds little evidence that suggests a within-firm positive relationship between board independence and managerial risky propensities, there was no evidence found to indicate that board quality and ethnic diversity affects corporate risk-taking.
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 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 | 0.001 | 0.010 |
| 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 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".