Bibliographic record
Abstract
The volume produces new findings about the concept of power and about its applications in negotiations. Rejecting the notions of power as a resource and power as an ability, the work defines power as an act that is designed to cause another party to move in a desired direction, thus separating the concept both from its source and from its effects and leaving it open to much more detailed analysis. At the same time, this book examines perceived power on the basis of which symmetries and asymmetries in the relations between parties can be identified. \n\nAs I. William Zartman and Jeffrey Rubin argue, negotiations between countries that are not equal in power tend to be more efficient and effective than during symmetrical negotiations. When weaker and stronger parties are negotiating, each knows its role and is able to get appropriate benefits in the agreement. In cases of symmetry or near symmetries the countries, whether equally weak or equally strong, tend to spend most of the time maintaining their status and allowing inordinate amounts of time to pass before reaching an agreement. These conclusions run counter to the most accepted wisdom of negotiations they do confirm evidence from careful experiments. \n\nThe volume looks at negotiations with clear asymmetry (the Canada-U.S. free trade agreement, U.S.-Egyptian aid, U.S.-Indonesian aid, E.C.-Andorra trade association, Nepal-India water resource agreement, and the North-South coalitions at the United Nations Conference on Environment and Development), two cases of symmetry (the Mali-Burkina Faso armistice negotiations and the U.S. Chinese armistice negotiations in Korea), and one mixed situation (Arab-Israeli peace negotiations). The book concludes with a careful examination of lessons for practice and lessons for theory.
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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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.009 | 0.025 |
| Scholarly communication | 0.015 | 0.013 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.025 | 0.004 |
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".