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Record W7148493162 · doi:10.7202/1124104ar

Ban Ki-moon et l’action climatique

2025· article· fr· W7148493162 on OpenAlexvenueno aff
Luis Rivera-Velez

Bibliographic record

VenueÉtudes internationales · 2025
Typearticle
Languagefr
FieldSocial Sciences
TopicInternational Development and Aid
Canadian institutionsnot available
Fundersnot available
KeywordsContext (archaeology)European unionTreatyDiplomacy

Abstract

fetched live from OpenAlex

À son arrivée à la tête de l’ONU en 2007, Ban Ki-moon hérite d’une politique climatique multilatérale fragilisée par le manque de leadership des États, la fragmentation des agences onusiennes et la faible implication des acteurs non étatiques. Contre toute attente, le Secrétaire général fait du climat une priorité de son mandat, se positionnant comme un acteur clé des négociations climatiques. À partir d’archives relatives aux actions du Secrétaire général, cet article montre comment Ban Ki-moon a su tirer parti de la crise de gouvernance pour s’imposer, d’abord comme autorité reconnue, puis comme administrateur et diplomate influent dans la gouvernance mondiale du climat. Son action culmine avec la signature de l’Accord de Paris en 2015 et se prolonge sous le mandat de son successeur, António Guterres, consacrant ainsi l’institutionnalisation du rôle climatique du Secrétaire général des Nations Unies.

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)0.002
metaresearch head score (Gemma)0.003
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: none
Teacher disagreement score0.062
Threshold uncertainty score0.123

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0110.010
Scholarly communication0.0070.005
Open science0.0010.005
Research integrity0.0030.006
Insufficient payload (model declined to judge)0.0140.001

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 head0.052
GPT teacher head0.375
Teacher spread0.323 · 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
Published2025
Admission routes1
Has abstractyes

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