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Record W2980404233 · doi:10.5334/aogh.2646

The Human Right to Breathe Clean Air

2019· editorial· en· W2980404233 on OpenAlexaff
David R. Boyd

Bibliographic record

VenueAnnals of Global Health · 2019
Typeeditorial
Languageen
FieldEnvironmental Science
TopicAir Quality and Health Impacts
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsHuman healthHuman rightsClean Air ActRight to healthStatement (logic)Public healthAir pollutionPolitical scienceBusinessEnvironmental protectionEnvironmental healthLawMedicineGeography

Abstract

fetched live from OpenAlex

Five national academies of science and medicine-from Brazil, Germany, South Africa, and the United States-issued a powerful statement about air pollution's immense impacts on public health. The statement concluded that the evidence linking air pollution and adverse health effects is unequivocal, the costs are enormous and yet the problem is preventable. However it is insufficient to treat clean air as a policy objective. It must be regarded as a fundamental human right, related to the rights of life, health, and a safe, clean, healthy and sustainable environment. The human rights perspective changes everything, because governments have clear, legally enforceable obligations to respect, protect, and fulfill human rights.

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)0.007
metaresearch head score (Gemma)0.019
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: Not applicable
GenreCandidate signal: Editorial · Consensus signal: Editorial
Teacher disagreement score0.026
Threshold uncertainty score0.044

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.019
Meta-epidemiology (narrow)0.0030.001
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0020.001
Science and technology studies0.0050.009
Scholarly communication0.0110.007
Open science0.0030.003
Research integrity0.0260.043
Insufficient payload (model declined to judge)0.0060.005

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 head0.045
GPT teacher head0.420
Teacher spread0.376 · 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
GenreEditorial

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

Citations28
Published2019
Admission routes1
Has abstractyes

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