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Record W2567327536 · doi:10.4000/vertigo.17858

La Cour européenne des droits de l’homme et le traitement de la connaissance scientifique sur la nocivité des ondes électromagnétiques, produits chimiques et autres activités polluantes

2016· article· fr· W2567327536 on OpenAlexvenueno aff
Elisabeth Lambert Abdelgawad

Bibliographic record

VenueVertigO · 2016
Typearticle
Languagefr
FieldEnvironmental Science
TopicInternational Environmental Law and Policies
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesPolitical sciencePhilosophy

Abstract

fetched live from OpenAlex

Cet article propose une lecture critique de l’appréhension de la connaissance scientifique ou de son absence par la CourEDH dans le contentieux sanitaire et environnemental. Il révèle que la position de la Cour se décline en deux catégories principales : 1) l’hypothèse la plus simple d’expertises unanimes réalisées en interne ou l’existence de seuils réglementaires ; 2) l’hypothèse compliquée pour la Cour de controverse scientifique ou d’absence de connaissance scientifique sur les effets sur la santé des activités dangereuses, cas de figure dans lesquels la Cour ne cherche pas à approfondir la connaissance manquante, mais, bien au contraire, se retranche, solution certes de facilité, derrière la marge d’appréciation. Cette étude appelle à s’interroger sur le maintien du raisonnement par causalité et surtout sur le refus d’une Cour des droits de l’homme de rendre la justice en s’équipant des données scientifiques nécessaires afin de trancher les litiges portés par des victimes en quête de justice.

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)0.010
metaresearch head score (Gemma)0.029
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.995
Threshold uncertainty score0.066

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.029
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0050.009
Scholarly communication0.0080.005
Open science0.0010.005
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0200.001

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 head0.016
GPT teacher head0.264
Teacher spread0.249 · 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.

Study designQualitative
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

Citations1
Published2016
Admission routes1
Has abstractyes

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