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Record W2790346416 · doi:10.3917/come.104.0097

The Russian arms sales to Iran and their (in)consequences on Russia-Israel military-industrial relations

2018· article· fr· W2790346416 on OpenAlexaff
Erik Burgos

Bibliographic record

VenueConfluences Méditerranée · 2018
Typearticle
Languagefr
FieldSocial Sciences
TopicMiddle East and Rwanda Conflicts
Canadian institutionsUniversité du Québec à Montréal
Fundersnot available
KeywordsPolitical scienceHumanitiesPhilosophy

Abstract

fetched live from OpenAlex

En dépit d’un développement fructueux ces deux dernières décennies, la coopération militaro-technologique entre la Russie et Israël demeure un sujet récurrent de débat pour la stratégie de sécurité de cette dernière, notamment en raison de l’assiduité des ventes d’armements russes à l’Iran. Cet article vise à démontrer que la logique de pérennisation commerciale joue un rôle fondamental dans la légitimation de l’architecture coopérative mise en place par les industriels russes et israéliens de la défense. Après avoir passé en revue l’historique et les fondements de ce rapprochement sectoriel, l’article aborde les paradoxes liés aux liens entretenus par la Russie avec deux États ennemis. Aucune conséquence majeure n’est attendue de cette double évolution.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.003
Scholarly communication0.0030.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0080.000

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.

Opus teacher head0.075
GPT teacher head0.304
Teacher spread0.229 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2018
Admission routes1
Has abstractyes

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