Introduction
A Simple Counterexample
A Fregean Counterexample
The Argument 4.1 Defending step 1 4.2 Defending step 2 4.3 Defending step 3 4.4 Defending step 4
Concluding Remarks
Roush, Stanford, and Unconceived Alternatives
Perrin and Brownian Motion
Retention and Possible Alternatives: New Lessons from Some Familiar History
Whither Exhaustion?
Conclusion
1 Introduction
2 Total Synthesis as Applied Science
3 Understanding Organic Chemistry
4 The Heuristics of Synthetic Design
5 An Example: Longifolene
6 Conclusion
1 Scientific Method in Science Textbooks
1.1 Textbook selection 1.2 Topic frequency Part I: Preliminaries
2 Science versus Non-science
2.1 Subjective experience/bias 2.2 Too many unmeasurable variables 2.3 Non-phenomenal objects 2.4 Falsifiability
3 Scientific Method in Everyday Activities?
4 When Did Science Begin?
4.1 Greek science? 4.2 Seventeenth-century origins Part II: Components
5 Formal Logic
5.1 Deduction: ‘if–then reasoning’ 5.2 Induction
6 Hypotheses, Theories, Laws, Models
6.1 Description and explanation 6.2 Models 6.3 ‘Only a theory’ 6.4 Simplicity Part III: Dynamics
7 The Generation of Hypotheses
8 The Testing of Hypotheses
8.1 Proof/verification/confirmation 8.2 Why is confirmation inconclusive? 8.2.1 Inductive generalization 8.2.2 Alternative hypotheses and the hypothetico-deductive method 8.3 Disproof/falsification 8.4 Why is falsification inconclusive? 8.4.1 Saving a hypothesis through ad hoc exceptions 8.4.2 Revising/correcting a hypothesis
9 Experimental Controls and the ‘Broken Lamp’
10 Conclusion
10.1 Different sciences, different concerns 10.2 Simple empiricism 10.3 The demarcation question 10.4 Textbook standardization and the avoidance of controversy
A Probabilistic Formulation of the Problem of Induction
A Problem with Objective Bayesianism 2.1 Intuitive motivation for the Principle of Indifference 2.2 The inconsistency objection 2.3 An effort to contain the problem
Explanationist Relief for Objective Bayesianism 3.1 Explanation and explanatory priority 3.2 Explanatory priority and the assignment of priors 3.3 In defense of Laplace 3.4 The metaphysics of the explanationist defense: causation and laws 3.5 Inference to the best explanation?
Problems and objections 4.1 Unknown explanatory possibilities 4.2 Empirical reasoning about explanatory priority 4.3 The probability of deterministic laws 4.4 Changing chances 4.5 Scruples concerning a priori probability
Mental Representations
Mental Imagery, Perception, and Cognitive Maps
Cognitive Maps in Psychology
Cognitive Maps in Robotics
Cognitive Maps in the Strict Sense?
Logically Structured Representations?
Systematicity and Productivity
Consequences for Philosophy and Psychology
Appendix: Cartographic Semantics
1 Introduction
2 Species as Individuals: The Two Main Arguments
3 Gene-Lineages as Individuals: Rosenberg's Argumentation
4 Assessing the GAI-Thesis 4.1 Metaphysics: What biology tells us about lineages 4.2 Epistemology: How biologists individuate the parts of genomes
5 What Do Gene Names Refer To?
6 Why the GAI-thesis Won't Solve the Gene Problem
Introduction
Sarkar's Information System
The Pre-theoretic Features of Genetic Information 3.1 Intentionality 3.2 Exclusiveness 3.3 Asymmetry 3.4 Causal relevance
Theoretical Usefulness
Conclusion
Introduction
Duhem on the Logic of Crucial Experiments
‘The Most Beautiful Experiment in Biology’
Why Not Simple Elimination?
Severe Testing
An Experimentalist Version of IBE 6.1 Physiological and experimental mechanisms 6.2 Explaining the data 6.3 IBE and the problem of untested auxiliaries 6.4 IBE-turtles all the way down
Van Fraassen's ‘Bad Lot’ Argument
IBE and Bayesianism
Conclusions
Introduction Turning a ‘Scale’ into a ‘Plume’ Lineage Explanations in Biology 3.1 The evolution of eyes 3.2 The evolution of feathers The Two Dimensions of a Lineage Explanation 4.1 The production dimension 4.2 The continuity dimension 4.3 The dual role of the parts Constraining the Explanations Operational and Generative Lineages Explaining Change Without Populations Conclusion
Introduction Correlation Measures 2.1 Standard covariance and correlation measures 2.2 The Wayne–Shogenji measure 2.3 Interpreting correlation measures 2.4 Correlation and evidential independence Focused Correlation Conclusion
Appendix
]]>Introduction: Pessimistic Meta-induction vs. Structural Correspondence The Case of the Phlogiston Theory Steps Towards a Systematic Correspondence Theorem The Correspondence Theorem and Its Ontological Interpretation Further Historical Applications Discussion of the Correspondence Theorem: Objections and Replies Consequences for Scientific Realism and Comparison with Other Positions 7.1 Comparison with constructive empiricism 7.2 Major difference from standard scientific realism 7.3 From minimal realism and correspondence to scientific realism 7.4 Comparison with particular realistic positions
Introduction
Epistemic Structural Realism 2.1 Ramsey-sentences and ESR 2.2 WESR and SESR
The Objection 3.1 Newman's version 3.2 Demopoulos and Friedman's and Ketland's versions
Replies that Abandon the Ramsey-Sentence Approach to ESR 4.1 Redhead's reply 4.2 French and Ladyman's reply
Replies Designed to Rescue the Ramsey-Sentence Approach 5.1 Zahar's reply 5.2 Cruse's reply 5.3 Melia and Saatsi's reply
Replies that Argue that Some Structures/Relations are Privileged 6.1 A Carnapian reply 6.2 Votsis' reply 6.3 The Merrill/Lewis/Psillos reply
Summary
The Problems of Formalism
Norton's Example
Three Species of Classical Mechanics 3.1 Mass point physics 3.2 The physics of perfect constraints 3.3 Continuum mechanics
Conclusion
Introduction
Dynamical Systems and Unpredictability 2.1 Dynamical systems 2.2 Natural invariant measures 2.3 Unpredictability
Chaos 3.1 Defining chaos 3.2 Defining chaos via mixing
Criticism of Answers in the Literature 4.1 Asymptotic unpredictability? 4.2 Unpredictability due to rapid or exponential divergence? 4.3 Macro-predictability and Micro-unpredictability?
A General New Implication of Chaos for Unpredictability 5.1 Approximate probabilistic irrelevance 5.2 Sufficiently past events are approximately probabilistically irrelevant for predictions
Conclusion
Introduction Two Classic Problems, and Two Popular Analyses 2.1 The paradox of anarchy 2.2 The paradox of revolution Restating the Puzzle Evaluating the Prisoners’ Dilemma and S-Curve Models The Variable Belief Threshold Model Example 5.1. A population of moderates with independent deviations Example 5.2 A heterogeneous population with independent deviations Example 5.3 A heterogeneous population with coordinated deviations Conclusion Appendix: Computer Simulations
How to Get to the Structure 1.1 X-ray diffraction and its synthesis 1.2 Model building and Pauling's panache 1.3 The structure of proteins 1.3.1 A failed inference to the best explanation 1.3.2 The misleading 5.1 Å spot in proteins and how to get rid of it 1.3.3 Derived predictions from Pauling's alpha-helix of protein molecules The CCV Theory of Helical X-Ray Diffraction 2.1 The role of the CCV theory in the discovery of the DNA structure Killing the Helix 3.1 Appreciating all evidence—in vain Conclusion Epilogue: Chargaff's Ratios
Theorem A. If H is any hyperarithmetic predicate on integers, then there is an MH spacetime in which any query ? n H ? can be computed.
In one sense this is best possible, as there is an upper bound to computational ability in any spacetime, which is thus a universal constant of that spacetime.
Theorem C. Assuming the (modest and standard) requirement that spacetime manifolds be paracompact and Hausdorff, for any spacetime
Introduction 1.1 History and preliminaries Hyperarithmetic Computations in MH Spacetimes 2.1 Generalising SADn regions 2.2 The complexity of questions decidable in Kerr spacetimes An Upper Bound on Computational Complexity for Each Spacetime
Introduction The Doctrine of Creation and Its Warrant Cardinality and Sizes of Infinity Modern Cosmology and Creation Tolerance or Intolerance toward Singularities? Leibniz against Incompetent Watchmaker? Induction from Earlier Theories' Breakdown? Stellar Collapse Implies Theistic Destroyer Stacking the Deck for GTR Quantum Gravity Tends to Resolve Singularities Vicious God-of-the-Gaps Character Fluctuating or Inaccessible Warrant Big Bang Cosmology Not Especially Congenial to Faith
Introduction The Competence Hypothesis The Performance Response Moral Mechanism Interference Blame or Valence?
Introduction Carruthers’ Argument from Design Modularity and Optimality: Problems for the Deductive Argument from Design Degrees of Modularity: Problems for the Inductive Argument from Design Conclusion
Introduction The Biology of Viruses 2.1 Bacteriophage life cycles 2.2 Mechanisms of HGT The Species Problem and Species Concepts 3.1 Phenetic species concepts 3.2 The biological species concept 3.3 Phylogenetic species concepts 3.4 The ecological species concept 3.5 Homeostatic property cluster species Viruses and Species Taxonomy Reticular Phylogenies Conclusion
Introduction
Features of the Theory
Frisch's Inconsistency Claim
Defending Frisch 4.1 Muller 4.2 Belot
Difficulties for Frisch and a Compromise
Conclusion
if your credences are not probabilities, then there is a way in which your rationality is impugned.
Each argument concludes that rationality requires your credences to be probabilities.
I contend that each argument is invalid as formulated. In each case there is a mirror-image theorem and a corresponding argument of exactly equal strength that concludes that rationality requires your credences not to be probabilities. Some further consideration is needed to break this symmetry in favour of probabilism. I discuss the extent to which the original arguments can be buttressed.
Introduction The Dutch Book Argument 2.1 Saving the Dutch Book argument 2.2 ‘The Dutch Book argument merely dramatizes an inconsistency in the attitudes of an agent whose credences violate probability theory’ Representation Theorem-based Arguments The Calibration Argument The Gradational Accuracy Argument Conclusion
Introduction The Construction Project Clocks The Spacetime Presumed Lorentz Covariance Is a Property of a Matter Theory and Spacetime Spatial Distances and Times Elapsed Are Properties of Spacetime Conclusion
Introduction Process and Product Fitness, Mean Fitness, and Phenotypic Change Correlated Interactions Causation Implications
Severity and Use-Constructing: Four Points (and Some Clarificatory Notes) 1.1 Point 1: Getting beyond ‘all or nothing’ standpoints 1.2 Point 2: The rationale for prohibiting double-counting is the requirement that tests be severe 1.3 Point 3: Evaluate severity of a test T by its associated construction rule R 1.4 Point 4: The ease of passing vs. ease of erroneous passing: Statistical vs. ‘Definitional’ probability The False Dilemma: Hitchcock and Sober 2.1 Marsha measures her desk reliably 2.2 A false dilemma Canonical Errors of Inference 3.1 How construction rules may alter the error-probing performance of tests 3.2 Rules for accounting for anomalies 3.3 Hunting for statistically significant differences Concluding Remarks