I. INTRODUCTION

1. Myths of LaPlacean Omniscience

Realism for Limited Beings in a Rich Messy World

Social Natures

Heuristics as Adaptations for the Real World

Nature as Backwoods Mechanic and Used-Parts Dealer

Error and Change

Organization and Aims of This Book

2. Normative Idealizations versus the Metabolism of Error

Inadequacies of Our Normative Idealizations

Satisficing, Heuristics, and Possible Behavior for Real Agents

The Productive Use of Error-Prone Procedures

3. Toward a Philosophy for Limited Beings

The Stance and Outlook of a Scientifically Informed Philosophy of Science

Ceteris Paribus, Complexity, and Philosophical Method

Our Present and Future Naturalistic Philosophical Methods

II. PROBLEM-SOLVING STRATEGIES FOR COMPLEX SYSTEMS

4. Robustness, Reliability, and Overdetermination

Common Features of Concepts of Robustness

Robustness and the Structure of Theories

Robustness, Testability, and the Nature of Theoretical Terms

Robustness, Redundancy, and Discovery

Robustness, Objectification, and Realism

Robustness and Levels of Organization

Heuristics and Robustness

Robustness, Independence, and Pseudo-Robustness: A Case Study

5. Heuristics and the Study of Human Behavior

Heuristics

Reductionist Research Strategies and Their Biases

An Example of Reductionist Biases: Models of Group Selection

Heuristics Can Hide Their Tracks

Two Strategies for Correcting Reductionist Biases

The Importance of Heuristics in the Study of Human Behavior

6. False Models as Means to Truer Theories

Even the Best Models Have "Biases"

The Concept of a "Neutral Model"

How Models Can Misrepresent

Twelve Things To Do with False Models

Background of the Debate over Linkage Mapping in Genetics

Castle's Attack on the "Linear Linkage" Model

Muller's Data and the Haldane Mapping Function

Muller's "Two-Dimensional" Arguments against Castle

Multiply-Counterfactual Uses of False Models

False Models Can Provide New Predictive Tests Highlighting Features of a Preferred Model

False Models and Adaptive Design Arguments

Summary and Conclusions

7. Robustness and Entrenchment: How the Contingent Becomes Necessary

Generative Entrenchment and the Architecture of Adaptive Design

Generative Systems Come To Dominate in Evolutionary Processes

Resistance to Foundational Revisions

Bootstrapping Feedbacks: Differential Dependencies and Stable Generators

Implications of Generative Entrenchment

Generative Entrenchment and Robustness

Conclusion

8. Lewontin's Evidence (That There Isn't Any)

Is Evidence Impotent, or Just Inconstant?

False Models as Means to Truer Theories

Narrative Accounts and Theory as Montage

III. REDUCTIONISM(S) IN PRACTICE

9. Complexity and Organization

Reductionism and the Analysis of Complex Systems

Complexity

Evolution, Complexity, and Organization

Complexity and the Localization of Function

10. The Ontology of Complex Systems: Levels of Organization, Perspectives, and Causal Thickets

Robustness and Reality

Levels of Organization

Perspectives: A Preliminary Characterization

Causal Thickets

11. Reductive Explanation: A Functional Account

Two Kinds of Rational Reconstruction

Successional versus Inter-Level Reduction

Levels of Organization and the Co-Evolution and Development of Interlevel Theories

Two Views of Explanation: Major Factors and Mechanisms versus Laws and Deductive Completeness

Levels of Organization and Explanatory Costs and Benefits

An Example: The Assumption of "the Purity of the Gametes" in the Heterozygote

Identificatory Hypotheses as Tools in the Search for Explanations

Appendix: Modifications Appropriate to a Cost-Benefit Version of Salmon's Account of Explanation

12. Emergence as Non-Aggregativity and the Biases of Reductionism(s)

Reduction and Emergence

Aggregativity

Perspectival, Contextual, and Representational Complexities; or, "It Ain't Quite So Simple as That!"

Adaptation to Fine- and Coarse-Grained Environments: Derivational Paradoxes for a Formal Account of Aggregativity

Aggregativity and Dimensionality

Aggregativity as a Heuristic for Evaluating Decompositions, and Our Concepts of Natural Kinds

Reductionisms and Biases Revisited

IV. ENGINEERING AN EVOLUTIONARY VIEW OF SCIENCE

13. Epilogue: On the Softening of the "Hard" Sciences

From Straw-Man Reductionist to Lover of Complexity

Messiness in State-of-the-Art Theoretical Physics

Hidden Elegance and Revelations in Run-of-the-Mill Applied Science

"Pure" versus Applied Science, and What Difference Should It Make?

Hortatory Closure

Appendix A. Important Properties of Heuristics

Appendix B. Common Reductionistic Heuristics

Appendix C. Glossary of Key Concepts and Assumptions

Appendix D. A Panoply of LaPlacean and Leibnizian Demons

Notes

Bibliography

Credits

Index

William Wimsatt is Professor of Philosophy and of Evolutionary Biology at the University of Chicago.