Been There, Done That: The History of Corporate Ownership in Japan
Bibliographic record
Abstract
Japan's corporate sector has, at different times in recent history, been organized according to every major model. Prior to World War II, wealth Japanese families locked in their control over large corporations by organizing them into pyramidal groups, called zaibatsu, similar to structures currently found in Canada, France, Korea, Italy, and Sweden. In the 1930s, the military government imposed a centrally planned command economy, with private property rights retained as little more than a legal fiction. The American occupation force replaced this with a widely held corporate sector similar to that of the United Kingdom and United States. A bout of takeovers and greenmail ensued. To defend their positions, Japanese top executives placed small numerous blocks of stock with each others' firms, creating dense networks of small intercorporate blocks that summed to majority blocks in each firm. These networks, called keiretsu, halted hostile takeovers completely. Although their primary functions were to lock in corporate control rights, both zaibatsu and keiretsu were probably also rational responses to a variety of institutional failings. Successful zaibatsu and keiretsu were enthusiastic political rent-seekers, raising the possibility that large corporate groups are better at influencing government than free standing firms. In the case of keiretsu especially, this rent seeking probably retarded financial development and created long-term economic problems.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.005 | 0.006 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".