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Record W4409511920 · doi:10.33002/jelp050101

Litigating Industrial Air Pollution in The Netherlands: The Impact of The European Court of Human Rights

2025· article· en· W4409511920 on OpenAlexvenueno aff
Jaike Josephine Louise Wolfkamp, Mia Swart

Bibliographic record

VenueJournal of Environmental Law & Policy · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicEnvironmental law and policy
Canadian institutionsnot available
Fundersnot available
KeywordsAir pollutionHuman rightsPollutionPolitical scienceEnvironmental planningLawEnvironmental protectionEnvironmental scienceEcology

Abstract

fetched live from OpenAlex

This article will focus on how the development of the European Human Rights Convention (ECHR) by the European Court of Human Rights (ECtHR) prompted Dutch environmental movements and citizens to rely on the ECHR to reduce industrial air pollution. It will further examine the decisive role of human rights in legal proceedings concerning industrial air pollution between environmental movements and affected individuals and the State and/or business entities. The impact of the developing case law by the ECtHR on Dutch cases such as the Air Quality cases, the Urgenda case and the Shell cases will be considered. This article will consider the effects of changing public opinion and scientific developments to understand the changing role of the ECHR in the Netherlands.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.758
Threshold uncertainty score0.986

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.017
GPT teacher head0.316
Teacher spread0.298 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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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