The Nominating Committee Process: A Qualitative Examination of Board Independence and Formalization
Bibliographic record
Abstract
The nominating committee (NC) of the board identifies and nominates individuals for board service, thus establishing the board's composition. Despite this important role, relatively little is known about the NC process, including NC members' actions and thought processes. Based on interviews of 20 U.S. public company NC members, including 16 chairs, we focus on two primary questions: (1) what is the extent of influence that the Chief Executive Officer (CEO) has over committee processes, and (2) to what extent are committee processes formalized (i.e., framed and acted upon in a mechanistic way)? We find that there is continuing recognition of CEO influence in the director nomination process, the level of which varies widely by company. Also, there is considerable variability in the formalization of the director nomination process (e.g., some NCs use search firms and a matrix/grid approach to assessing director skill sets across the board, while others do not). Finally, we find that many interviewees have professional or personal ties to the CEO and that nearly all of the NCs focus on “chemistry” and comfort in the director nomination process, where the often‐stated goal is to enhance the board's ability to function effectively and to reduce risk in the director nomination process. The overall message of the interviews perhaps is best captured by one interviewee, who described a “strange little dance.” Throughout the interviews, we find evidence that the NC must “dance” through a complex decision landscape.
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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 | 0.005 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.004 |
| 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".