Just how did David Defeat Goliath? The Application of Tactics of Warfare to Asymmetrical Peacetime Negotiations
Bibliographic record
Abstract
Under what conditions are small states able to gain in a negotiation more than would be expected based on international relations theory given their relative share of power, influence and capabilities? Power asymmetries at the bargaining table occur frequently in today’s world, and while common sense would suggest that strong states should be able to ‘flex their muscles’ and get their way, small states emerge from asymmetric negotiations victorious quite often. To explain this phenomenon, scholars in the field have proposed three primary theories that, while effective in their ability to provide explanations for weak state success in some cases, fail to account for many others. This thesis argues that, in addition to the existing “soft-balancing”, “acceptance” and “coalition building” asymmetric negotiation theories, it proves useful to turn to the theories advanced in the asymmetric wartime literature to provide explanations for currently unaccounted for cases. The applicability of these wartime theories, including relative resolve, resolve signaling and attacking multiple fronts, is tested through an analysis of three distinct asymmetric negotiations in which weaker parties experienced significant success: the 1985-1987 Canada and United States free trade agreement negotiation, the 1951-1953 Indonesia and United States aid negotiation, and the 1980-1987 Syria and Turkey Euphrates River negotiation. I argue that, in each of these cases, the way in which the weaker party was able to leave the bargaining table victorious is best explained through applications of asymmetric military strategies. The implications of these findings provide insight into how the arsenal of tactics for weaker parties in negotiations may be larger than originally thought, and how the application of military strategies in times of peace can yield extremely beneficial results, notwithstanding an unbalanced playing field.
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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 | 0.001 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".