Bibliographic record
Abstract
Citation (2015), "List of Contributors", Advances in Mergers and Acquisitions (Advances in Mergers and Acquisitions, Vol. 14), Emerald Group Publishing Limited, Bingley, pp. vii-viii. https://doi.org/10.1108/S1479-361X20150000014013 Publisher: Emerald Group Publishing Limited Copyright © 2015 Emerald Group Publishing Limited Fadi Alkaraan Dublin City University Business School, Dublin City University, Dublin, Ireland Nima Amiryany Department of Information, Logistics and Innovation, VU University Amsterdam, Amsterdam, the Netherlands Cary L. Cooper Manchester Business School, University of Manchester, Manchester, England Sydney Finkelstein Tuck School of Business, Dartmouth College, Hanover, NH, USA Terrill L. Frantz Peking University HSBC Business School, Shenzhen, China Kamal Ghosh Ray Vignana Jyothi Institute of Management, Hyderabad, India Sangita Ghosh Ray Management Consultant, Hyderabad, India John A. Howard High Rock Partners, Raleigh, NC, USA Jochem T. Hummel Department of Information, Logistics and Innovation, VU University Amsterdam, Amsterdam, the Netherlands Alexei Koveshnikov Aalto University School of Business, Helsinki, Finland Rebecca Lund Aalto University School of Business, Helsinki, Finland Sigmar Malvezzi Institute of Psychology, University of São Paulo, São Paulo, Brazil Kenneth H. Marks High Rock Partners, Raleigh, NC, USA Mitchell Lee Marks College of Business, San Francisco State University, San Francisco, CA, USA Katty Marmenout Ecole Hôtelière de Lausanne, Lausanne, Switzerland Muriel Mignerat Telfer School of Management, University of Ottawa, Ottawa, ON, Canada Philip H. Mirvis Private Consultant, MA, USA Ladislau Ribeiro do Nascimento Institute of Psychology, University of São Paulo, São Paulo, Brazil Janne Tienari Aalto University School of Business, Helsinki, Finland Book Chapters Advances in Mergers and Acquisitions Advances in Mergers and Acquisitions Advances in Mergers and Acquisitions Copyright Page List of Contributors Introduction Managing the Precombination Phase of Mergers and Acquisitions Why is Gender not Debated in M&A? Configuring Management Buyouts to Ensure Value Fairness Strategic Investment Decision-Making Perspectives Optimizing Private Middle-Market Companies for M&A and Growth Leveraging Social Networks in Mergers: A Roadmap for Post-Merger Integration Post-Merger Integration: Looking under the Haziness of Culture Conflict Identity: An Instrument for Mergers and Acquisitions Determinants of Acquisition Performance: A Multi-Industry Analysis
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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 | 0.003 | 0.028 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.013 | 0.008 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.737 | 0.743 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".