LEADER 05699oam 2200793 c 450 001 9910978227703321 005 20260102090118.0 010 $a9783839465806 010 $a383946580X 024 7 $a10.1515/9783839465806 035 $a(MiAaPQ)EBC7286445 035 $a(CKB)28162959500041 035 $a(Au-PeEL)EBL7286445 035 $a(DE-B1597)644562 035 $a(DE-B1597)9783839465806 035 $a(Perlego)3784301 035 $a(transcript Verlag)9783839465806 035 $a(EXLCZ)9928162959500041 100 $a20260102d2023 uy 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 12$aA Heated Debate$eMeta-Theoretical Studies on Current Climate Research and Public Understanding of Science$fMaria M. Sojka 205 $a1st ed. 210 $aBielefeld$ctranscript Verlag$d2023 215 $a1 online resource (228 pages) 225 0 $aEdition Moderne Postmoderne 311 08$a9783837665802 320 $aIncludes bibliographical references. 327 $aCover -- Contents -- List of Abbreviations -- List of Figures -- 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 -- 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 -- 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 -- 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. 327 $a3.4.2 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 -- 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 -- References -- Acknowledgment. 330 $aEver since climate change has been identified as one of the most significant challenges of humanity, climate change deniers have repeatedly tried to discredit the work of scientists. To show how these processes work, Maria M. Sojka examines three ideals about how science should operate. These ideals concern the understanding of uncertainties, the relationship between models and data, and the role of values in science. Their widespread presence in the public understanding of science makes it easy for political and industrial stakeholders to undermine inconvenient research. To address this issue, Sojka analyses the importance of tacit knowledge in scientific practice and the question of what defines an expert. 410 0$aEdition Moderne Postmoderne. 517 2 $aSojka, A Heated Debate$eMeta-Theoretical Studies on Current Climate Research and Public Understanding of Science 606 $aPhilosophy of Science 606 $aClimate Science 606 $aTacit Knowledge 606 $aComputer Simulations 606 $aExpertise 606 $aScience 606 $aNature 606 $aSociety 606 $aEpistemology 606 $aPhilosophy of Nature 606 $aAnalytical Philosophy 606 $aPhilosophy 615 4$aPhilosophy of Science 615 4$aClimate Science 615 4$aTacit Knowledge 615 4$aComputer Simulations 615 4$aExpertise 615 4$aScience 615 4$aNature 615 4$aSociety 615 4$aEpistemology 615 4$aPhilosophy of Nature 615 4$aAnalytical Philosophy 615 4$aPhilosophy 676 $a363.73874 700 $aSojka$b Maria M$p

Maria M. Sojka, Ruhr-Universität Bochum, Deutschland

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