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Record W143699737 · doi:10.7202/1044681ar

La dimension institutionnelle du développement durable

2018· article· fr· W143699737 on OpenAlexvenueno aff
Ahmed Djoghlaf

Bibliographic record

VenueLes ateliers de l éthique · 2018
Typearticle
Languagefr
FieldSocial Sciences
TopicFrench Urban and Social Studies
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesPolitical sciencePhilosophy

Abstract

fetched live from OpenAlex

La Conférence des Nations Unies sur l’environnement et le développement qui s’est tenue à Rio de Janeiro en juin 1992 a été, sans aucun doute, un événement marquant de la coopération multilatérale contemporaine. Le plus grand rassemblement multilatéral jamais organisé auparavant, cet événement aura marqué d’une empreinte indélébile l’architecture institutionnelle du traitement de la question envionnementale et façonne les institutions issues de la Conférence de Stockholm sur l’environnement humain. La Conférence de Rio aura été, au bout du compte, le point de départ d’une ère institutionelle nouvelle et d’une nouvelle façon d’aborder la coopération multilatérale pour la protection de l’environnement. La dimension institutionnelle de la question du développement durable renvoie nécessairement aux progrès qui restent à accomplir en vue d’une meilleure compréhension de la façon dont le développement durable est perçu au niveau national. Cette question traduit aussi la difficulté qu’il y a à adapter le mandat originel des institutions existantes aux exigences multiformes de l’intégration de la question de l’environnement dans les processus de développement économique et social. Elle exige surtout une action concertée tendue en vue d’une plus grande cohérence de l’action internationale qui serait au service d’une nouvelle démarche muliforme à l’égard de l’environnement, au service d’un développement respectueux des équilibres écologiques de notre planète.

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)0.003
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.018
Threshold uncertainty score0.061

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.003
Science and technology studies0.0020.009
Scholarly communication0.0130.011
Open science0.0010.004
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0180.002

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.

Opus teacher head0.032
GPT teacher head0.268
Teacher spread0.236 · 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 designTheoretical or conceptual
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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