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|a 1399424647
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|a 9783839465806
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|a UAMI
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|a Sojka, Maria M.,
|e author.
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|a A Heated Debate :
|b Meta-Theoretical Studies on Current Climate Research and Public Understanding of Science /
|c Maria M. Sojka.
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|a Bielefeld :
|b Transcript
|c [2023]
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|a 1 online resource (226 pagse)
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|a text
|b txt
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|a online resource
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|a Philosophy
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|a Description based on online resource; title from digital title page (viewed on September 20, 2023).
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|a Includes bibliographical references (pages 203-226)
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|a 1. Introduction -- 2. Some preliminary remarks -- 2.1 Epistemic challenges of highly complex systems -- 2.2 Discovery and justification: the DJ distinction -- 2.3 A few words about objectivity -- 3. Three ideals of science -- 3.1 Value-free science -- 3.1.1 Introduction: values in science -- 3.1.1.1 The rise and fall of the value-free ideal -- 3.1.1.2 Epistemic versus non-epistemic values -- 3.1.2 Inductive risks and social values -- 3.1.2.1 Social values and methodological considerations
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|a 3.1.3 Social values in climate science -- 3.1.3.1 Unconstrained decision making, predictive preferences andcostrestrictions -- 3.1.3.2 Non-traceability -- 3.1.3.3 Coarser uncertainty quantification and other possiblecounterarguments -- 3.1.3.4 Systematic bias and wishful thinking -- 3.1.4 Conclusion -- 3.2 Model, theory and observation -- 3.2.1 Introduction: from handmaiden to a life of their own -- 3.2.1.2 Observation -- 3.2.2 Theory-ladenness, underdetermination and models of data -- 3.2.2.1 Models of data -- 3.2.3 Observations in climate science -- 3.2.3.1 Climate data
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|a 3.2.3.1.1 Observations and uncertainties -- 3.2.3.1.2 Satellite data -- 3.2.3.1.3 Paleoclimate data and proxies -- 3.2.3.1.4 Reanalysis data -- 3.2.3.2 Model-data interdependency -- 3.2.3.3 Verification and validation -- 3.2.4 Conclusion -- 3.3 Predictability -- 3.3.1 Introduction: predictability and uncertainty -- 3.3.2 Robustness -- 3.3.3 Uncertainties in climate science -- 3.3.3.1 Numerical approximation and structural uncertainty -- 3.3.3.2 Parameter uncertainty -- 3.3.3.3 Second-order uncertainty -- 3.3.3.3.1 Ensemble studies -- 3.3.3.3.2 The quantification problem
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|a 3.3.3.4 Robustness revisited -- 3.3.4 Conclusion -- 3.4 Looking back and a tentative look forward -- 3.4.1 Complexity and understanding -- 3.4.2 Discovery and justification -- 3.4.3 Scientific objectivity -- 3.4.4 Conclusion: what now? -- 4. Tacit knowledge, skill and expertise -- 4.1 Tacit knowledge -- 4.1.1 Michael Polanyi: tacit knowledge -- 4.1.2 Gilbert Ryle: knowing how and knowing that -- 4.1.3 Harry Collins: a taxonomy of tacit knowledge -- 4.1.3.1 Relational Tacit Knowledge -- 4.1.3.2 Somatic Tacit Knowledge -- 4.1.3.3 Collective Tacit Knowledge -- 4.2 Tacit knowledge in climate science
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|a 1.2.1 Connection between tacit knowledge and expertise -- 4.2.2 Climate modelling as engineering or craft -- 4.3 Conclusion: expertise through experience -- 2. Concluding remarks -- 5.1 Where to go from here? -- 5.1.1 Philosophy of science -- 5.1.2 Science -- 5.1.3 Public.
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|a This note is part of Quality testing.
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|a JSTOR
|b Books at JSTOR All Purchased
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|a JSTOR
|b Books at JSTOR Demand Driven Acquisitions (DDA)
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|a Climatic changes
|x Research.
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|a Science
|x Public opinion.
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|a Climatic changes
|x Public opinion.
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|a Sciences
|x Opinion publique.
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|a Climat
|x Changements
|x Opinion publique.
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|a Philosophy (Transcript (Firm))
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|u https://jstor.uam.elogim.com/stable/10.2307/jj.6627663
|z Texto completo
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