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A Heated Debate : Meta-Theoretical Studies on Current Climate Research and Public Understanding of Science /

This note is part of Quality testing.

Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor principal: Sojka, Maria M. (Autor)
Formato: Electrónico eBook
Idioma:Alemán
Publicado: Bielefeld : Transcript [2023]
Colección:Philosophy (Transcript (Firm))
Temas:
Acceso en línea:Texto completo

MARC

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100 1 |a Sojka, Maria M.,  |e author. 
245 1 2 |a A Heated Debate :  |b Meta-Theoretical Studies on Current Climate Research and Public Understanding of Science /  |c Maria M. Sojka. 
264 1 |a Bielefeld :  |b Transcript  |c [2023] 
300 |a 1 online resource (226 pagse) 
336 |a text  |b txt  |2 rdacontent 
337 |a computer  |b c  |2 rdamedia 
338 |a online resource  |b cr  |2 rdacarrier 
490 1 |a Philosophy 
588 |a Description based on online resource; title from digital title page (viewed on September 20, 2023). 
504 |a Includes bibliographical references (pages 203-226) 
505 0 |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 
505 0 |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 
505 0 |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 
505 0 |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 
505 0 |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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