Mergers and acquisitions in North America, Latin America, Asia and the Pacific : selected issues and jurisdictions
Bibliographic record
Abstract
The thirty-second edition of the Comparative Law Yearbook of International Business comprises two volumes, each dealing broadly with issues relating to crossbordermergers and acquisitions. Volume Aprovides 16 chapters and examines mergers and acquisitions in Europe. Volume B provides 16 chapters and treats mergers and acquisitions in North America, Latin America, and Asia and the Pacific. Each consists of national reports and treatments of selected issues within the respective regions. Volume B, Mergers and Acquisitions in North America, Latin America, Asia and the Pacific, Selected Issues and Jurisdictions, reviews the Australian Takeovers Panel, joint ventures in China, and employment issues in New Zealand, as well as national reports on Brazil, Canada, Chile, China, Colombia, India, Indonesia, Israel, Japan, Nigeria, The Philippines, Sri Lanka, and Trinidad and Tobago.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".