Bibliographic record
Abstract
Norms are one of the most widely studied topics of contemporary International Relations scholarship. Norms scholars have created an extensive theoretical and empirical literature to identify, describe, and analyze the emergence, diffusion, and effect of norms in the international system. However, this scholarship is inconsistent in how it treats state choice and norm diffusion; in particular, it is divided between theories that emphasize continuity and those that allow for change in the process of norm adoption and implementation. This article suggests that the problem can be remedied through a closer examination of the structure of norms themselves. It first shows that the prevailing understanding of contemporary international norms is that they have a tripartite structure, consisting of a problem, a value, and a behavior. These structural components can be combined to create norms as traditionally understood. The article also proposes a new concept — a “norm cluster” — which allows for multiple combinations of conceptually interlinked but distinct values and behaviors, offering multiple acceptable solutions to similar and interlocking problems. The actors that adopt a norm cluster, rather than a single norm or set of norms, may be recognized as a family group: although no cluster adopter need perfectly re-enact the choices of others, the resulting variation in outcomes is accepted as “close enough.” The article argues that focusing on norm components and clusters, rather than on single norms as currently understood, allows for a more precise understanding of how principle-based action diffuses and evolves in the international system.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.009 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.004 | 0.033 |
| Scholarly communication | 0.010 | 0.018 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 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".