Bibliographic record
Abstract
Les enjeux de sécurité au Moyen-Orient sont protéiformes. Partant de la définition de Buzan et Waever, nous entendons démontrer que, face aux menaces portées par le milieu « cyber » contre la sécurité nationale, les États du Moyen-Orient trouvent des réponses conformes à leur identité stratégique traditionnelle. Le cas de l’Arabie saoudite est particulièrement intéressant dans la compréhension des logiques du sous-système régional du golfe Arabo-Persique quant à l’intégration de la variable « cyber » dans la démarche de sécurisation, du fait de sa posture stratégique dominante. Dès lors, deux questions se posent à l’égard de cette analyse : la première relève du volet strictement théorique et interroge la lecture culturaliste des stratégies mises en place devant la montée des enjeux de cybersécurité au Moyen-Orient. La seconde s’intéresse aux dynamiques du complexe régional et aux tensions systémiques procédant de la confrontation entre l’interdépendance des acteurs étatiques et leur recherche de sécurité nationale.
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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.009 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".