Are Women More Likely to Seek Advice than Men? Evidence from the Boardroom
Bibliographic record
Abstract
It is commonly believed that women are more likely to seek advice than men; for example, on aspects of health or asking for directions when lost. This paper investigates whether women’s relatively greater propensity for advice seeking extends to important business decisions, specifically those involving corporate takeovers. Consistent with the evidence from other contexts, we show that the presence of female directors on target boards is positively and significantly associated with target boards seeking advice from top-ranked financial advisors. In contrast, we do not observe any significant association between the presence of female directors on bidder boards and their engagement of top-ranked financial advisors. We argue that the presence of a gender effect for target boards but not for bidder boards is consistent with less overconfident female versus male directors on bidder boards initiating fewer bids, higher litigation risk facing target boards for accepting too little, and the different type of advice sought by bidders and target firms.
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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) | 0.000 | 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".