Examining The Effect Of Change In CEO Gender, Functional And Educational Background On Firm Performance And Risk
Bibliographic record
Abstract
The purpose of this paper is to examine, within a succession framework, the impact of the change in CEO gender from female to male on firm performance and probability of bankruptcy. We also examine the impact of change in CEO functional and educational background on firm performance and probability of bankruptcy. We use paired sample t-tests and ordinary least squares regression analysis on 46 CEO successions where the outgoing CEO is a female and the incoming CEO is a male. The results show that a change in CEO gender from female to male is associated with an increase in firm performance and a decrease in the firm probability of bankruptcy. Furthermore, the percentage change in firm performance is negatively related to the change in CEO functional and educational background. The percentage change in firm probability of bankruptcy is positively related to the change in CEO functional and educational background. Firm management and board of directors should be aware that there is such a thing as too much change around a succession event and that it has an adverse effect on firm performance and probability of bankruptcy
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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 | 0.009 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".