Lawyering compliance with international law: Legal advisers in the ‘War on Terror’
Bibliographic record
Abstract
Abstract According to rationalists and constructivists, compliance with international law occurs to the extent that states see non-compliance as unreasonable or wrong, respectively. An alternative account of compliance points to the practical difficulty of deciding to act contrary to international law. Here non-compliance is blocked rather than morally or instrumentally deterred. This article advances an organisational-process theory of this third kind. The explanatory mechanism lies in the constitutive rules of foreign policymaking, and points to the institutional function of legal advising. Under certain structural conditions (namely, lawyerised decision-making) legal advisers operate as the principal ‘agents of compliance’ within the state, bringing international law into the policymaking process and thus bridging the gap between foreign policy and legal expectations. The theory is applied to the interrogation programme implemented by the United States in the early years of the ‘War on Terror’ (2001–5). While initially violative of international legal standards, the programme eventually shifted towards compliance. Using process tracing, the case study provides fine-grained evidence that corroborates the explanatory power of organisational factors, in general, and legal advising, in particular.
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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 | 0.014 | 0.030 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.030 |
| Scholarly communication | 0.008 | 0.007 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.007 | 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".