The development of the buyout industry: U.S.-Japan comparisons
Bibliographic record
Abstract
Initially developed in the United States, the buyout industry is finally emerging in Japan. The earliest U.S. firms to enter the field began operations more than a quarter century ago, and some of these firms pioneered techniques now standard in the industry. Yet virtually no buyout activity took place in Japan until the late 1990s, and Japan's distinctive economic and social arrangements clearly are shaping the way the buyout industry is developing in Japan as compared to the United States and other Western countries. The emergence of the Japanese buyout industry naturally raises a number of important questions. When and why, for example, did buyout activity finally get started in Japan? How does the operation of the buyout industry in Japan compare with that of the United States and other Western countries? What are the key determinants of the future course of the Japanese buyout industry, and what roles will buyout firms based in Japan and abroad play in its development? To explore these and related issues, the Program on Alternative Investments of the Center on Japanese Economy and Business at Columbia Business School organized a seminar with two leading buyout practitioners, one American and the other Japanese, to share their views with an audience drawn from the academic and business communities. The first speaker was Mr. Joseph L. Rice III, Chairman of Clayton, Dubilier & Rice, Inc., a leading New York-based buyout firm, and was followed by Mr. Tsutomu Yoshida, Senior Vice President of Mitsui & Co. (U.S.A.), Inc., a large Japanese trading firm that also has participated in the buyout field. This report presents highlights of the seminar, held on April 7, 2005, at Columbia University in New York, and moderated by Dr. Mark Mason, Director of the Program on Alternative Investments.
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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 | 0.003 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".