Interlocking directorates and corporate networks
Bibliographic record
Abstract
This chapter provides an introduction to the literature on interlocking directorates and corporate networks. It first traces the historical roots of the field back to the early 20th century, when researchers on both sides of the Atlantic started expressing concern about the threat to democratic process posed by the emergent corporate form, the potential for collusion allowed by the growing practice of interlocking directorate, and the general concentration of power in the hands of large firms and banks. It then outlines the major theoretical approaches employed, that focus on the corporate network as a set of both interorganizational and interindividual relationships. Third, it summarizes the main findings on the cohesiveness of the corporate community, the hegemonic position of banks, and historical changes and longitudinal dynamics of the network. Finally, it discusses most recent debates on the globalization, the emergence of a European corporate network, and the decline and recomposition of the corporate community.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.010 |
| Scholarly communication | 0.007 | 0.010 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".