A Meta Analytical Study of Cultural Conditions Moderating the Relationship Between Board Diversity and <scp>CSR</scp> Disclosure
Bibliographic record
Abstract
ABSTRACT Studies on the relationship between board diversity and CSR disclosure have shown mixed results. This study investigates the relationship between board diversity attributes and CSR disclosure, as well as the various cultural conditions influencing board diversity–CSR disclosure relationships through meta‐analysis based on data from 45 empirical studies. We discovered that board diversity attributes such as board gender, age, education, and national diversity have a positive relationship with CSR disclosure. In terms of moderating effects, we discovered that cultural dimensions of (high) uncertainty avoidance, long‐term orientation, and (high) indulgence positively moderate the relationship between board diversity attributes and CSR disclosure, whereas high individualism, masculinity, and power distance scores negatively moderate these relationships. This study highlights the importance of maintaining diversity in terms of age, gender, education, and nationality at the board level in promoting CSR disclosures, even in restraining cultures, suggesting policymakers devise policies that encourage board diversity. Academically, this study extends the previous meta‐work by clarifying the strength and direction of the relationships between board diversity attributes and CSR disclosure, helping to resolve ambiguities in these relationships in the extant literature. In addition, the study explores the moderating effects of cultural dimensions on the relationship between board diversity and CSR disclosure, a factor that was previously overlooked.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.003 |
| 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".