Bibliographic record
Abstract
Purpose The purpose of this paper is to explain how current security market regulations in Japan have evolved following Japan’s corporate governance reforms, which began in the 1990s after the bursting of a massive financial bubble. As part of the reform, Japan aimed to introduce US-style corporate governance mechanisms. Design/methodology/approach This paper first explains the process behind Japan’s corporate governance reforms using the theory of selective adaptation. By doing so, the various changes that have taken place in the regulations of security markets are also explained. The paper concludes with a discussion of the limitations of transplanting US-style corporate governance mechanisms in Japan and the implications for the functioning of Japan’s security markets. Findings While applying a selective adaptation framework to Japan’s efforts to transplant US-style corporate governance mechanisms to its own markets, the author found that certain Japan-specific business practices, such as its heavy reliance onkeiretsucorporate groupings, may interfere with the market-based business practices and free competition which characterize the US system. This in turn places limitations on the functioning of US-style security markets in Japan. Originality/value This paper explains the limitations of government regulation on security markets in Japan, which may be of interest to both public and private sector analysts. This paper focusses on Japan’s experience of transplanting US-style corporate governance mechanisms to Japan. The author expect that Japan’s experience will be of much interest to China, South Korea and other countries in East Asia, where pyramidal and other types of business groups play important roles in their economies.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.009 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".