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Adaptation, Mitigation, and Justice

2010· book-chapter· en· W4251652396 on OpenAlexaboutno aff
Dale Jamieson

Bibliographic record

VenueOxford University Press eBooks · 2010
Typebook-chapter
Languageen
FieldEnvironmental Science
TopicClimate Change and Geoengineering
Canadian institutionsnot available
Fundersnot available
KeywordsPolitical scienceClimate changeEconomic JusticeClimate justiceAdaptation (eye)Global warmingEnvironmental ethicsGeographyEnvironmental resource managementLawEconomicsPsychologyEcology

Abstract

fetched live from OpenAlex

In this chapter I claim that climate change poses important questions of global justice, both about mitigating the change that is now under way and about adapting to its consequences. I argue for a mixed policy of mitigation and adaptation, and defend one particular approach to mitigation. I also claim that those of us who are rich by global standards and benefit from excess emissions have strenuous duties in our roles as citizens, consumers, producers, and so on, to reduce our emissions and to finance adaptation. When I began my research on global climate change in the mid-1980s, it was commonly said that there were three possible responses: prevention, mitigation, and adaptation. Even then we were committed to a substantial climate change, although this was not widely known. This realization began to dawn on many people on June 23, 1988, a sweltering day in Washington, D.C., in the middle of a severe national drought, when climate modeler James Hansen testified before a U.S. Senate committee that it was 99 percent probable that global warming had begun. Hansen’s testimony was front-page news in the New York Times, and was extensively covered in other media as well. Whether or not Hanson was right, his testimony made clear that we were entering a new world, what Schneider (1989) called “the greenhouse century.” Once it became clear that prevention was no longer possible, mitigation quickly moved to center stage. One week after Hansen’s testimony, an international conference in Toronto, convened by the World Meteorological Organization (WMO), called for a 20 percent reduction in greenhouse-gas (GHG) emissions by 2005. In November, the World Congress on Climate and Development, meeting in Hamburg, called for a 30 percent reduction by 2000. Later that same year, acting on a proposal by the United States, the WMO and the United Nations Environment Programme (UNEP) established the Intergovernmental Panel on Climate Change (IPCC) in order to assess the relevant scientific information and to formulate response strategies.

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)0.010
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation 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: Other · Consensus signal: Other
Teacher disagreement score0.011
Threshold uncertainty score0.050

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.010
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0110.047
Scholarly communication0.0100.010
Open science0.0010.011
Research integrity0.0100.011
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 head0.020
GPT teacher head0.182
Teacher spread0.162 · 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 designTheoretical or conceptual
Domainnot available
GenreOther

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

Citations13
Published2010
Admission routes1
Has abstractyes

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