Bibliographic record
Abstract
1. Introduction & Overview. 2. 'The Economist Cases: How Mergers Go Wrong. PART I: GROWTH BY M&A. 3. Henry Manne: Merger & Market for Corporate Control. 4. Michael C Jensen: Take-overs: folklore & science. 5. H Donald Hopkins: Cross Border Mergers & Acquisitions, global & regional perspectives. 6. Bruce Kogut: Joint Ventures and the Option to Acquire. 7. Harry G Barkema & Freek Vermeulen: International Expansion through Start-up or Acquisition, a learning perspective. PART II: MOTIVES AND TARGETS. 8. HG Baumann: Merger Theory, Property Rights and the Pattern of US Direct Investment in Canada. 9. Russell W Coff: How Buyers Cope with Uncertainty when Acquiring Firms in Knowledge-Intensive Industries, caveat emptor. 10. Tomi Laamanen: Option Nature of Company Acquisitions Motivated by Competence Acquisiton. 11. Andrew C Inkpen, Anant K Sundaram & Kristin Rockwood: Cross-Border Acquisition of US Technology Assets. PART III: STRATEGIC PLANNING, TACTICS AND VALUATION. 12. Michael Keenan: Valuation Problems in Service Sector Mergers. 13. Harbir Singh & Cynthia A Montgomery: Corporate Acquisition Strategies and Economic Performance. 14. Roland Calori, Michael Lubatkin & Phillipe Very: Control Mechanisms in Cross-Border Acquisitions. 15. Pedro Gonzales, Geraldo M Vasconcellos & Richard J Kish: Cross-Border Mergers and Acquisitions, the undervaluation hypotheses. PART IV: MERGER PROCESSES. 16. Anthony F Buono, James L Bowditch & John Lewis III: When Cultures Collide, the anatomy of a merger. 17. Piero Morosini, Scott Shane & Harbir Singh: National Cultural Differences and Cross-Border Acquistion Performance. PART V: MANAGERIAL AND SOCIAL CONSEQUENCES OF MERGERS. 18. John J Siegfried and M Jane Bar Sweeney: The social & Political Consequences of Conglomerate Mergers. 19. Deepak K Datta Organisational Fit and Acquistion Performance, effects of post- acquisition integration. 20. Roland Villinger: Post Acquistion Managerial Learning in Central East Europe. PART VI: SUMMARY AND CONCLUSION. 21. Harvard Business Review: Round Table on Making Mergers Succeed. 22. Conclusions.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 teacher head, 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".