The Japanese Business and Economic System: History and Prospects for the 21st Century.
Bibliographic record
Abstract
PART ONE: INTRODUCTION PART TWO: ECONOMIC GROWTH AND INDUSTRIAL RELATIONS Japan's Economic Growth: Past and Present Comments Participatory Employment Practices in Japan Comments Kudoka and the Japanese Worker Comments PART THREE: TRANSFER OF JAPANESE TECHNOLOGY TO ASIA AND NORTH AMERICA Technology Transfer in Asia in Transition: Case Studies of Japanese Companies Comments Japanese Auto Suppliers in North America: A Review of the Literature and Prospects for Research PART FOUR: TECHNOLOGY IN JAPANESE ECONOMIC HISTORY Japanese Technological Development: A Technology Gap Hypothesis and Its Implications Comments Osaka and Tokyo Comments PART FIVE: US-JAPAN RELATIONS AND THE JAPANESE ECONOMY Equity Markets, Political Markets and the Changing Framework of US-Japanese Economic Relations Global Duopolistic Competition of Fujifilm and Kodak: Corporate Strategy and Business-Government Relations Comments Comments on the Kodak-Fuji Dispute, the WTO and Trade and Competition Policies PART SIX: JAPANESE BUSINESS PRACTICES Japan's Business Groups Japanese Corporate Governance and Macroeconomic Problems Comments Environmental Issues and Japanese Firms PART SEVEN: CONCLUSION
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.007 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 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".