A Cognitive Approach to Diversity: Investigating the Impact of Board of Directors’ Educational and Functional Heterogeneity on Innovation Performance
Bibliographic record
Abstract
Boards’ diversity has been studied mainly through the prism of ethics, which translated into a focus on characteristics such as gender and ethnicity. However, when the goal is to explain organizational outcomes, the cognitive approach seems more pertinent. Thus, rooted in a resource dependency perspective, this paper investigates the potential impact of directors’ deep level diversity (functional and educational diversity) on innovation performance based on an international sample of 97 firms for a total of 1027 directors. The findings highlight the negative effect of functional diversity (measured by diversity in the sectors of expertise), and on the opposite, the positive impact of educational diversity (measured by diversity in the fields of study) on innovation performance. This study also shows that the environment in which organizations evolve, both at the internal and external level, is crucial when it comes to innovation performance. These results are robust in that they remain consistent after addressing some potential endogeneity issues and have critical implications for both the professional and academic world.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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".