Idealization and the aims of science /Angela Potochnik.

Includes bibliographies and index.

Introduction : doing science in a complex world. Science by humans ; Science in a complex world ; The payoff : idealizations and many aims -- Complex causality and simplified representation. Causal patterns in the face of complexity ; Causal patterns ; Causal complexity ; Simplification by idealization ; Reasons to idealize ; Idealizations' representational role ; Rampant and unchecked idealization -- The diversity of scientific projects. Broad patterns : modeling cooperation ; A specific phenomenon : variation in human aggression ; Predictions and idealizations in the physical sciences ; Surveying the diversity -- Science isn't after the truth. The aims of science ; Understanding as science's epistemic aim ; Separate pursuit of science's aims ; Understanding, truth, and knowledge ; The nature of scientific understanding ; The role of truth and scientific knowledge -- Causal pattern explanations. Explanation, communication, and understanding ; An account of scientific explanation ; The scope of causal patterns ; The crucial role of the audience ; Adequate explanations -- Levels and fields of science. Levels in philosophy and science ; Going without levels ; Against hierarchy ; Prizing apart forms of stratification ; The fields of science and how they relate -- Scientific pluralism and its limits. The entrenchment of social values ; How science doesn't inform metaphysics ; Scientific progress.

Idealizations are assumptions made without regard for whether they are true and often with full knowledge they are false. This book develops a strong view of idealization's centrality to science and reconsiders the aims of science in light of that centrality. The starting point is well-accepted ideas about how science is shaped by its human practitioners and by the world's complexity. Together, these ideas inspire a view of science as the search for causal patterns, a search that relies significantly on idealizations. Idealizations contribute to science in a variety of ways, including by playing a positive representational role. Case studies from across science are used to demonstrate idealizations' ubiquity in science, as well as the wide range of purposes they serve. This account of idealization has implications for central philosophical debates about the aims of science. First, it provides reason to think the epistemic aim of science is not truth but human understanding. Understanding is a cognitive achievement that, unlike truth, can be directly furthered by idealizations. This in turn motivates an account of scientific explanation that does justice to how the production of understanding depends on human cognizers, including the cognitive value of causal patterns. It also inspires a view of the relationship among scientific projects not as investigating discrete levels of organization, but as independent and partial explanations dependent on one another for epistemic support. Finally, this account of idealization expands the influence of human values on science's aims and products, while also constraining scientific and metaphysical pluralism.

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