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Record W3123265815

A Theoretical Framework for Understanding Transnational Public Goods (TPGs) to Upgrade Environmental Quality

2016· article· en· W3123265815 on OpenAlexaboutno aff
Parag Chandra, Saptorshee Kanto Chakraborty

Bibliographic record

VenueSSRN Electronic Journal · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicPublic health and occupational medicine
Canadian institutionsnot available
Fundersnot available
KeywordsGreenhouse gasRatificationEnvironmental protectionNatural resource economicsPublic goodAir quality indexMontreal ProtocolPollutionBusinessEnvironmental qualityPollutantKyoto ProtocolOzone layerEnvironmental scienceEnvironmental planningPoliticsEnvironmental resource managementGeographyPolitical scienceOzoneEconomicsEcologyMeteorologyLaw
DOInot available

Abstract

fetched live from OpenAlex

In recent years, there has been an increase in awareness of trans-boundary pollution that places environmental assets at risk both globally and regionally. Globally, man made pollutants have degraded the stratospheric ozone shield, the oceans, the atmosphere and the biodiversity of the planet. Regionally, these pollutants have harmed aquifers, rivers, lakes, soils and forests. Harmful effects of acid rains, greenhouse gasses, and thin ozone shield are not concentrated within political boundaries of a country, thus jeopardizing the well-being of people in other countries. These trans-boundary pollution problems — termed as Transnational Public Goods (TPGs) — often share two common features: strategic interactions among nations and public good properties. This paper applies the theory of voluntary provisions of TPGs to the behavior of nations to curb chloro-fluoro-carbon emissions that, in large part, preceded the ratification and institution of the Montreal Protocol on substances that deplete the ozone layer.

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)0.007
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation 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 score0.972
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.066
GPT teacher head0.393
Teacher spread0.327 · 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 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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