Bielefeld, : transcript Verlag, 2023

9783839465806

383946580X

1 online resource (228 pages)

Edition Moderne Postmoderne

363.73874

Philosophy of Science

Climate Science

Tacit Knowledge

Computer Simulations

Expertise

Science

Nature

Society

Epistemology

Philosophy of Nature

Analytical Philosophy

Philosophy

Inglese

Includes bibliographical references.

Cover -- 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.

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 -- 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.

Ever 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.