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Record W3008493269 · doi:10.3917/strat.121.0347

La fiabilité des engagements de défense de l’OTAN envers les pays baltes

2020· article· fr· W3008493269 on OpenAlexaff
Lukas Milevski

Bibliographic record

VenueStratégique · 2020
Typearticle
Languagefr
FieldEconomics, Econometrics and Finance
TopicDefense, Military, and Policy Studies
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsHumanitiesPolitical sciencePhilosophy

Abstract

fetched live from OpenAlex

La problématique de la fiabilité de l’OTAN en tant qu’alliance militaire, et en particulier de sa clause de défense collective, l’article 5, est redevenue un sujet de préoccupation important, notamment dans le contexte de la défense balte. Dans ce cas, il est essentiel de reconnaître que l’engagement est de défendre, et non de dissuader ou de prétendre à dissuader. La fiabilité elle-même est difficile à déterminer car il s’agit d’une caractéristique interne qui ne peut être interprétée que par d’autres comme une crédibilité, mais dont l’essentiel est la volonté politique intrinsèque plutôt que toute mesure purement militaire. On peut comparer les expériences des États membres de l’OTAN depuis 2014 en ce qui concerne les actions visant à renforcer la défense balte et les relations entre les États et la Russie. Sur la base de la politique des États membres depuis 2014, les États-Unis semblent rester fiables malgré Trump, alors que les principaux alliés européens se sont révélés beaucoup plus décevants et potentiellement peu fiables.

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)0.004
metaresearch head score (Gemma)0.004
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 score0.062
Threshold uncertainty score0.124

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0130.007
Scholarly communication0.0080.003
Open science0.0010.007
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0120.001

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 head0.060
GPT teacher head0.253
Teacher spread0.193 · 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
Published2020
Admission routes1
Has abstractyes

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