How States Persuade: An Account of International Legal Argument Upon the Use of Force
Bibliographic record
Abstract
This Article presents a theory of the sociology of argument in international law and considers how persuasion, through international legal argument, shapes legal change and influences notions of compliance. Commonly, international law is portrayed as a medium for debate. Within the resulting debates, persuasion is understood as a tool to induce compliance. Yet this is only one side of the conversation. Persuasion is a two-way discourse. Efforts to alter the behavior of a “non-compliant” state through cogent communication are often met with or preempted by legal arguments put forth by the state. This is perhaps most apparent in the deliberative environments that accompany the use of force and the conduct of warfare. Built around a series of case studies in which states offer legal arguments in support of actions that, prima facie, extend beyond the limits of legal permissibility, this Article presents a theory of persuasion and legal communication that differs from how legal argument and international law are commonly under-stood. This Article offers a detailed and theorized account of the processes through which the non-compliant state argues, persuades, and employs international law. By mapping and conceptualizing persuasive techniques, I suggest that international law must be considered both in compliance and in violation. Switching emphasis and considering the actions and arguments offered by the “non-compliant” state facilitates a novel and complete understanding of the diplomatic, informal, and daily interactions that more commonly and more consequentially define how international law is understood, practiced, and altered.
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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 | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.010 | 0.027 |
| Scholarly communication | 0.015 | 0.019 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.008 | 0.007 |
| Insufficient payload (model declined to judge) | 0.008 | 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 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".