Delineating the corporate elite: Inquiring the boundaries and composition of interlocking directorate networks
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Corporate elite studies have for long investigated networks of interlocking directorates to test and corroborate key theoretical expectations regarding the cohesive organization of such an elite and their ability and willingness to act on behalf of general business interests. These studies typically collect data on a list of 50, 100, 200 or 500 corporations ranked by economic size, sometimes stratified in sectors. The sampling approach often follows previous studies in order to increase comparability. These relatively arbitrary sampling practices are problematic because they impact the empirical results and our therefore the conclusions drawn from it. Using a sample of 3251 Canada‐based corporations, we establish that indeed different sampling criteria – that is sample size, proportion of financial firms, inclusion of state‐owned enterprises and so on – significantly impacts network properties of corporate elite networks. We establish rather disturbing differences, especially for smaller sample sizes (<100). Subsequently, we develop alternative demarcation criteria of the corporate elite based on a k ‐core decomposition. We conclude by emphasizing that the sampling decisions in interlocking directorate studies should much more be carefully be thought through in future research on the topic, both in corporate elite studies and beyond.
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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 | 0.001 | 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 | 0.002 | 0.002 |
| 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 it