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Record W300553201

Durban Dilemma: A Second Green Revolution?

2012· article· en· W300553201 on OpenAlexaboutno aff
Scott Zhuge

Bibliographic record

VenueHarvard international review · 2012
Typearticle
Languageen
FieldEnvironmental Science
TopicSustainable Development and Environmental Policy
Canadian institutionsnot available
Fundersnot available
KeywordsKyoto ProtocolGreenhouse gasClimate changeUnited Nations Framework Convention on Climate ChangeTreatyConference of the partiesGlobal warmingChinaPolitical scienceGeographyEnvironmental protectionConventionLawEcology
DOInot available

Abstract

fetched live from OpenAlex

In 1992, 172 governments participated in the United Nations Conference on Environment and Development, producing the United Nations Framework Convention on Climate Change (UNFCCC). The international environmental treaty, while not itself setting any limits on greenhouse gas emissions, provided a framework for producing future protocols that set mandatory emission limits. From then on, the Conference of Parties (COP) met regularly at various cities, producing important climate treaties like the Kyoto Protocol. In late 2011, the COP met again in Durban, South Africa, to discuss three main issues: future US commitments to emission reduction, the Kyoto Protocol, and the Cancun agreements discussed at the previous meeting. However, expectations for the Durban meeting ran low, as the two countries with the highest emission levels, the United States and China, refused to take leadership in commitments to the UNFCCC protocols. Without the support of those two countries, other major countries like Japan and Canada were unlikely to join in a second round of the protocols. Climate change continues to pose a significant global challenge. In 2007, the IPCC released a comprehensive report on climate change, projecting drastic climate change within this century. The report predicted extreme weather changes, such as ice cap melting, long droughts, and flooding. The UN World Meteorological Association reported that greenhouse gas volumes reached a record high in 2010, with [CO.sub.2] levels increasing to 389 ppm in 2010 from 280 ppm in 1750. One of climate change's biggest global impacts is on agriculture, especially in developing regions like those of sub-Saharan Africa. Climate change threatens food security in several ways. For example, increased temperatures eventually reduce crop yields in the long run. Even if certain crops could grow more effectively in warmer temperatures, the overall net effect of unbalanced temperature increase causes a decrease in desirable crop yields. A report by the International Food Policy Research Institute found that while climate change tended to hurt agricultural output for all countries, developing countries suffered especially sharper decreases in crop yields compared to developed countries. In particular, crops requiring irrigation took the hardest hits, given that both unpredictable precipitation and temperature increases require more effective irrigation systems. The International Water Management Institute found that by 2025, the global percentage of people living in water-stressed basins will increase from thirty-eight percent to sixty-four percent, due to warmer climate. Increased temperatures also promote weed and pest proliferation, adding to the burden of sustaining crop yields. With these changing factors driven by climate change, agricultural adaptations become increasingly imperative. Already, population growth projections point to the need for agricultural reform. The United Nations Population Division projects that by 2050, the human population will range from 7. …

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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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient 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 score0.664
Threshold uncertainty score0.973

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.1340.028

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 head0.013
GPT teacher head0.250
Teacher spread0.237 · 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; both teacher heads agree on what is shown here.

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

Citations0
Published2012
Admission routes1
Has abstractyes

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