A Theoretical Framework for Understanding Transnational Public Goods (TPGs) to Upgrade Environmental Quality
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.015 |
| Scholarly communication | 0.005 | 0.007 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.005 | 0.003 |
| Insufficient payload (model declined to judge) | 0.015 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".