North American Corporate Directors and Educational Affiliations: A Geographical Analysis
Bibliographic record
Abstract
The importance of the modern corporation, as an employer, customer, charitable donor, developer, investment venue, and simply as a community member, means that the processes by which it is governed are of importance to society as a whole. One key element of this governance system is the corporation’s board of directors. Boards have come under increased scrutiny in recent years because of a variety of scandals and bankruptcies where boards have played, or should have played, key roles. A vast literature has developed around corporate boards, but one area in which research has been lacking relates to the geography of boards and board membership. This paper attempts to close this gap by exploring the boards of directors of Canadian and American companies and analyzing the geography of a key component of their social networks, their educational affiliations. The study examines the universities and university cities that are most central to the North American interlocking network, investigates the differences in university alumni network behavior that exist between the two countries, and focuses particularly on the very few cities that host the most elite of universities. The results of this research demonstrate that a very few universities and university cities have influential positions within the North American directorate network, that by comparison with the US the Canadian director network is more diverse and international in outlook in terms of its in its selection of directors, and that Boston is alone among the top university cities in having a wide-spread influence in terms of local alumni placed with top boards across North America. The study interprets these results and calls for further research into corporate governance and networking.
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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 | 0.011 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.009 | 0.043 |
| Science and technology studies | 0.011 | 0.037 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.004 |
| 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; both teacher heads agree on what is shown here.
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".