Board diligence, independence, size, and firm performance: Evidence from Saudi Arabia
Bibliographic record
Abstract
The aim of this paper is to examine the possible association between the effectiveness of Board of Directors (BOD) and firm performance (FP). For the purpose of this analysis, data is derived from firms listed in the materials sector of the Saudi Exchange Market’s Tadawul All Share Index (TASI). Using pooled OLS regression analysis and the dependent variables of ROA and ROE as a proxy for FP, while board meetings (BMEET), independence and board size (BSIZE) are used as explanatory variables, the results reveal that frequent BMEET may not lead to improved FP. Moreover, the results show that BMEET frequency is negatively associated with FP. Independent members do not provide additional efficiency leading to better FP. As for the BSIZE, the findings indicate that larger boards are associated with lower FP. Such findings offer insights into the effect of BSIZE on FP. The results are of interest to decision makers, policymakers and investors.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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 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".