Norm Robustness and Contestation in International Law: Self-Defense against Nonstate Actors
Bibliographic record
Abstract
Using the example of the right to self-defense under customary international law, we engage with questions concerning the linkage between norm robustness and legality. We draw out important differences between validity contestation and applicatory contestation within law. In so doing, we connect the international relations (IR) debate over norm robustness with our framework of interactional international law, bringing together constructivist insights into social normativity and a theory of international legality. We hypothesize that norms that meet the requirements of legality and are upheld by practices of legality enjoy “validity” and “facticity” (as defined by Deitelhoff and Zimmermann) and are “robust.” This model reveals that law operates through a continuing process of contestation. The requirements of legality impose a discipline, such that legal contestation will normally be applicatory contestation. Through practices of legality, therefore, legal norms can be maintained or shifted. However, legal norms may decay when practices of legality weaken or when challenges amount to validity contestation. The currently heightened contestation surrounding the circumstances under which the right to self-defense can be exercised against nonstate actors allows us to explore and illustrate of these dynamics.
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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 | 0.026 | 0.037 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.007 | 0.087 |
| Scholarly communication | 0.011 | 0.014 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".