Business groups in the West : origins, evolution, and resilience
Bibliographic record
Abstract
Part I. Concepts and Arguments 1: Asli M. Colpan and Takashi Hikino: Introduction: Business Groups Re-examined 2: Asli M. Colpan And Takashi Hikino: The Evolutionary Dynamics of Diversified Business Groups in the West: History and Theory 3: Ben Ross Schneider, Asli M. Colpan and Weihuang Wong: Politics, Institutions, and Diversified Business Groups: Comparisons Across Developed Countries 4: James R. Lincoln and Matthew Sargent: Business Groups as Networks Part II: National Experiences of Business Groups Group 1. Historical Frontrunners in Europe 5: Geoffrey Jones: Britain: Global Legacy and Domestic Persistence 6: Marco Becht: Belgium: The Disappearance of Large Diversified Business Groups 7: Abe De Jong and Ferry De Goey: The Netherlands: The Overlooked Variety of Big Business 8: Harm Schroeter: Germany: An Engine of Modern Economic Growth 9: Youssef Cassis: France: A Complement to Multidivisional Enterprises Group 2. Catch-up Nations in Europe 11: Mats Larsson and Tom Petersson: Sweden: Tradition And Renewal 12: Andrea Colli and Michelangelo Vasta: Italy: Enduring Logic and Pervasive Diffusion 12: Alvaro Cuervo-Cazurra: Spain: Regulation and Ideology as Drivers for Transformation 13: Alvaro Ferreira Da Silva and Pedro Neves: Portugal: Changing Environment and Flexible Adaptation Group 3. Western Offshoots 14: Takashi Hikino and Marcelo Bucheli: The United States in Historical Perspectives: The Strange Career of Business Groups in Industrial Development 15: David Collis, Bharat Anand and J. Yo-Jud Cheng.: The United States in Contemporary Perspectives: Evolving Forms, Strategy and Performance 16: Simon Ville: Australia: From Family Networks to Boom and Bust Groups 17: Randall Morck and Gloria Tian: Canada: The Rise and Fall and Rise and Fall Again
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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 | 0.002 | 0.013 |
| Scholarly communication | 0.006 | 0.009 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 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".