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Record W3001155235 · doi:10.1787/dc34d5e3-en

Study of International Regulatory Co-operation (IRC) arrangements for air quality

2020· paratext· en· W3001155235 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueOECD regulatory policy working papers · 2020
Typeparatext
Languageen
FieldEnvironmental Science
TopicEnvironmental Policies and Emissions
Canadian institutionsnot available
Fundersnot available
KeywordsAir quality indexChinaAir pollutionGovernment (linguistics)East AsiaBusinessQuality (philosophy)Scope (computer science)ConventionEnvironmental planningInternational tradePolitical scienceEnvironmental protectionEnvironmental scienceGeographyMeteorologyComputer scienceLaw

Abstract

fetched live from OpenAlex

China, Japan and Korea have deployed a multiplicity of co-operation efforts at different levels of government to promote air quality and curb transboundary pollution. This paper identifies the existing arrangements for air quality co-operation in North East Asia and provides guidance to advance the co-operation required to face cross-border air pollution building on the experience of two long-standing co-operative agreements in this area: the Canada-United States Air Quality Agreement and UNECE’s Convention on Long-Range Transboundary Air Pollution. This paper finds that the multilateral arrangements existent in North East Asia are yet to produce a comprehensive science-based regional approach to address transboundary air pollution. Key suggestions for countries to capitalise on the stronger momentum for co-operation in this area include: i) building on the existing frameworks for international regulatory co-operation for air quality; ii) advancing a common understanding of transboundary air pollution across scientific regional arrangements; and iii) strengthening the domestic policy frameworks for air quality in each country as a key prerequisite.

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.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.558
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0070.001

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 head0.044
GPT teacher head0.332
Teacher spread0.288 · 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