Bibliographic record
Abstract
À l’heure où l’expertise de l’AIEA est à nouveau au centre des tractations, cet article montre les logiques parfois contradictoires qui pèsent sur le travail d’expertise de l’Agence. En interrogeant le rôle de l’enquête de l’AIEA en Iran dans les négociations visant à réguler les activités nucléaires iraniennes (2003-2013), cet article permet d’éclairer les enjeux contemporains de la mise en œuvre des garanties en Iran. À partir d’entretiens avec des diplomates et des fonctionnaires de l’AIEA, cet article fait l’hypothèse d’une politisation de l’enquête de l’AIEA, c’est-à-dire d’une intensification des échanges de « coups » entre des secteurs politique et technique. Cette conceptualisation structurale de la politisation du dossier nucléaire iranien permet de démontrer comment l’enquête de l’AIEA constitue à la fois un processus technique autonome et un carburant de la négociation pour la définition des activités nucléaires iraniennes (in)acceptables.
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 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.012 | 0.020 |
| Scholarly communication | 0.007 | 0.008 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.016 | 0.002 |
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".