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Record W564884105

The Multilateral Fund for the implementation of the Montreal Protocol : addressing challenges of globalization - an independent evaluation of the World Bank's approach to global programs - case study

2004· article· en· W564884105 on OpenAlexaboutno aff
Lauren Kelly

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicClimate Change Policy and Economics
Canadian institutionsnot available
Fundersnot available
KeywordsMontreal ProtocolSanctionsDeveloping countryKyoto ProtocolProtocol (science)International communityOzone layerBusinessInternational tradePolitical scienceEconomicsEconomic growthLawOzoneMedicineGeographyClimate change
DOInot available

Abstract

fetched live from OpenAlex

Following the discovery of the Antarctic ozone hole in late 1985, governments recognized the need for stronger measures to reduce the production and consumption of a number of ozone depleting substances. The Montreal Protocol on Substances that Deplete the Ozone Layer was adopted in 1987 and became binding international law in 1989. The Protocol is one of the first international environmental agreements to impose trade sanctions to achieve its goals. It is also precedent-setting as it differentiates legal rules between developed and developing countries - recognizing that the latter had contributed little to the global challenge of ozone depletion and hence were entitled to special consideration, despite the fact that all nations are responsible for protecting the ozone layer. The original Protocol provided no mechanism to assist developing countries in meeting control measures. Due to the dissatisfaction expressed by developing countries, the London Amendment in June 1990 revised the Protocol, thus giving birth to the Multilateral Fund and providing a financial mechanism for covering the agreed incremental compliance costs. The Bank entered into a legal agreement with the Fund in July 1991 whereby it agreed to assist its partner implementing agencies in channeling resources to developing countries to support investment operations for the phase-out of ozone depleting substances (ODS).

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)0.059
metaresearch head score (Gemma)0.054
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.372
Threshold uncertainty score0.739

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0590.054
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0050.006
Science and technology studies0.0100.008
Scholarly communication0.0130.006
Open science0.0030.007
Research integrity0.0050.004
Insufficient payload (model declined to judge)0.0100.001

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 head0.367
GPT teacher head0.425
Teacher spread0.058 · 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
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

Citations5
Published2004
Admission routes1
Has abstractyes

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