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Record W2622502955 · doi:10.7202/1034837ar

À propos du nucléaire : modèle de développement et santé

2016· article· fr· W2622502955 on OpenAlexvenueno aff
Alberto L’Abate, Frédéric Lesemann

Bibliographic record

VenueInternational Review of Community Development · 2016
Typearticle
Languagefr
FieldSocial Sciences
TopicRisk Perception and Management
Canadian institutionsnot available
Fundersnot available
KeywordsPolitical scienceHumanitiesArt

Abstract

fetched live from OpenAlex

Les mouvements anti-nucléaires luttent pour l’instauration d’un « nouveau modèle de développement ». En effet, la nécessité de recourir à l’énergie nucléaire est l’aboutissement d’un modèle de développement basé sur l’industrialisation lourde, l’urbanisation intensive, la minorisation de l’agriculture, le gaspillage sauvage des ressources naturelles qui a été celui qui a assuré l’essor des pays industriels centraux. Les effets de ce modèle de développement sont extrêmement néfastes et inquiétants à de nombreux points de vue. L’expansion du nucléaire est corrélative de la volonté des pays centraux de poursuivre leur développement selon le modèle initial qui a assuré leur domination, au détriment des pays périphériques ou « en voie de développement », mais aussi des conditions de vie sanitaires et écologiques des populations de tous les pays. L’auteur illustre sa thèse par de nombreux exemples italiens, mais aussi d’autres pays et prône la promotion de l’utilisation de sources d’énergies renouvelables et non polluantes, en lien avec un processus de décentralisation économique et politique qui accorderait un poids accru aux populations et aux communautés locales, leur permettrait de reprendre collectivement le contrôle de leurs conditions de vie et favoriserait l’avènement d’une société « conviviale ».

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)0.005
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 score0.039
Threshold uncertainty score0.079

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0050.004
Open science0.0020.003
Research integrity0.0040.003
Insufficient payload (model declined to judge)0.0240.003

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 head0.083
GPT teacher head0.411
Teacher spread0.328 · 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
Published2016
Admission routes1
Has abstractyes

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