When Empirical Success Implies Theoretical Reference: A Structural Correspondence Theorem

Starting from a brief recapitulation of the contemporary debateon scientific realism, this paper argues for the following thesis:Assume a theory T has been empirically successful in a domainof application A, but was superseded later on by a superiortheory T^*, which was likewise successful in A but has an arbitrarilydifferent theoretical superstructure. Then under natural conditionsT contains certain theoretical expressions, which yielded T'sempirical success, such that these T-expressions correspond(in A) to certain theoretical expressions of T^*, and given T^*is true, they refer indirectly to the entities denoted by theseexpressions of T^*. The thesis is first motivated by a studyof the phlogiston–oxygen example. Then the thesis is provedin the form of a logical theorem, and illustrated by furtherexamples. The final sections explain how the correspondencetheorem justifies scientific realism and work out the advantagesof the suggested account.

1. Introduction: Pessimistic Meta-induction vs. Structural Correspondence
2. The Case of the Phlogiston Theory
3. Steps Towards a SystematicCorrespondence Theorem
4. The Correspondence Theorem and ItsOntological Interpretation
5. Further Historical Applications
6. Discussion of the Correspondence Theorem: Objections and Replies
7. Consequences for Scientific Realism and Comparison with OtherPositions

   7.1 Comparison with constructive empiricism

   7.2Major difference from standard scientific realism

   7.3 Fromminimal realism and correspondence to scientific realism

   7.4Comparison with particular realistic positions

     

Crick's notion of genetic information and the 'central dogma' of molecular biology

An assessment is offered of the recent debate on informationin the philosophy of biology, and an analysis is provided ofthe notion of information as applied in scientific practicein molecular genetics. In particular, this paper deals withthe dependence of basic generalizations of molecular biology,above all the ‘central dogma’, on the so-called‘informational talk’ (Maynard Smith [2000a]). Itis argued that talk of information in the ‘central dogma’can be reduced to causal claims. In that respect, the primaryaim of the paper is to consider a solution to the major difficultyof the causal interpretation of genetic information: how todistinguish the privileged causal role assigned to nucleic acids,DNA in particular, in the processes of replication and proteinproduction. A close reading is proposed of Francis H. C. Crick'sOn Protein Synthesis (1958) and related works, to which we owethe first explicit definition of information within the scientificpractice of molecular biology.

1. Introduction

   1.1 The basicquestions of the information debate

   1.2 Thecausal interpretation(CI) of biological informationand Crick's‘central dogma’

2. Crick's definitions of genetic information
3. The main requirementfor (CI)
4. Types of causation in molecular biology

   4.1 Structuralcausation in molecular biology

   4.2 Nucleicacids as correlativecausal factors

5. The ‘central dogma’ withoutthe notion of information
6. Concluding remarks

     

Bayes not Bust! Why Simplicity is no Problem for Bayesians

The advent of formal definitions of the simplicity of a theoryhas important implications for model selection. But what isthe best way to define simplicity? Forster and Sober ([1994])advocate the use of Akaike's Information Criterion (AIC), anon-Bayesian formalisation of the notion of simplicity. Thisforms an important part of their wider attack on Bayesianismin the philosophy of science. We defend a Bayesian alternative:the simplicity of a theory is to be characterised in terms ofWallace's Minimum Message Length (MML). We show that AIC isinadequate for many statistical problems where MML performswell. Whereas MML is always defined, AIC can be undefined. WhereasMML is not known ever to be statistically inconsistent, AICcan be. Even when defined and consistent, AIC performs worsethan MML on small sample sizes. MML is statistically invariantunder 1-to-1 re-parametrisation, thus avoiding a common criticismof Bayesian approaches. We also show that MML provides answersto many of Forster's objections to Bayesianism. Hence an importantpart of the attack on Bayesianism fails.

1. Introduction
2. TheCurve Fitting Problem

   2.1 Curves and families of curves

   2.2 Noise

   2.3 Themethod of Maximum Likelihood

   2.4 ML and over-fitting

3. Akaike's Information Criterion(AIC)
4. The Predictive Accuracy Framework
5. The Minimum MessageLength (MML) Principle

   5.1 The Strict MML estimator

   5.2 Anexample: Thebinomial distribution

   5.3 Properties ofthe SMML estimator

   5.3.1  Bayesianism

   5.3.2  Languageinvariance

   5.3.3Generality

   5.3.4  Consistencyand efficiency

   5.4 Similarity to false oracles

   5.5 Approximationsto SMML

6. Criticisms of AIC

   6.1 Problems with ML

   6.1.1  Smallsample biasin a Gaussian distribution

   6.1.2  Thevon Misescircular and von Mises—Fisherspherical distributions

   6.1.3  The Neyman–Scottproblem

   6.1.4  Neyman–Scott,predictive accuracyandminimum expected KL distance

   6.2 Otherproblems with AIC

   6.2.1  Univariate polynomial regression

   6.2.2  Autoregressiveeconometric time series

   6.2.3  Multivariatesecond-orderpolynomial modelselection

   6.2.4  Gapor no gap:a clustering-like problem forAIC

   6.3 Conclusionsfrom the comparison of MML and AIC

7. Meeting Forster's objectionsto Bayesianism

   7.1 The sub-family problem

   7.2 Theproblem of approximation,or, which framework forstatistics?

8. Conclusion

1. Details of the derivation of the Strict MMLestimator
2. MML, AIC and the Gap vs. No Gap Problem

   B.1 Expectedsize of the largest gap

   B.2 Performanceof AIC on thegap vs. no gap problem

   B.3 Performanceof MML in thegap vs. no gap problem

     

Realization, completers, and ceteris paribus laws in psychology

I defend Jerry Fodor's ([1991]) account of the semantics ofceteris paribus laws against an objection raised by Peter Mott([1992]). In doing so, I clarify certain issues regarding thenature of realization. I argue that not all things that realizea state or property are realizers of that state or property:the relation x realizes y tolerates the inclusion of gratuitouselements in x— elements that play no particular role inthe realization of y— whereas the relation x is a realizerof y does not. I then criticize a rejoinder that, in effect,builds such gratuitous elements into the antecedents of thelaws of a science of the realized properties.

1. Fodor's Proposal
2. Mott's Objection
3. Conjunctive States, Realization, and MinimalRealization
4. Mixed Antecedents

     

The Crux of Crucial Experiments: Duhem's Problems and Inference to the Best Explanation

Going back at least to Duhem, there is a tradition of thinkingthat crucial experiments are impossible in science. I analyseDuhem's arguments and show that they are based on the excessivelystrong assumption that only deductive reasoning is permissiblein experimental science. This opens the possibility that someprinciple of inductive inference could provide a sufficientreason for preferring one among a group of hypotheses on thebasis of an appropriately controlled experiment. To be sure,there are analogues to Duhem's problems that pertain to inductiveinference. Using a famous experiment from the history of molecularbiology as an example, I show that an experimentalist versionof inference to the best explanation (IBE) does a better jobin handling these problems than other accounts of scientificinference. Furthermore, I introduce a concept of experimentalmechanism and show that it can guide inferences from data withinan IBE-based framework for induction.

1. Introduction
2. Duhem onthe Logic of Crucial Experiments
3. ‘The Most BeautifulExperiment in Biology’
4. Why Not Simple Elimination?
5. SevereTesting
6. An Experimentalist Version of IBE

   6.1 Physiologicaland experimentalmechanisms

   6.2 Explaining the data

   6.3IBE and the problemof untested auxiliaries

   6.4 IBE-turtlesall the way down

7. Van Fraassen's ‘Bad Lot’ Argument
8. IBE and Bayesianism
9. Conclusions

     

Focused Correlation and Confirmation

This essay presents results about a deviation from independencemeasure called focused correlation. This measure explicatesthe formal relationship between probabilistic dependence ofan evidence set and the incremental confirmation of a hypothesis,resolves a basic question underlying Peter Klein and Ted Warfield's‘truth-conduciveness’ problem for Bayesian coherentism,and provides a qualified rebuttal to Erik Olsson's claim thatthere is no informative link between correlation and confirmation.The generality of the result is compared to recent programsin Bayesian epistemology that attempt to link correlation andconfirmation by utilizing a conditional evidential independencecondition. Several properties of focused correlation are alsohighlighted.

1. Introduction
2. Correlation Measures

   2.1 Standard covarianceand correlation measures

   2.2 The Wayne–Shogenjimeasure

   2.3 Interpreting correlation measures

   2.4 Correlationandevidential independence

3. Focused Correlation
4. Conclusion

Appendix     

DNA, Inference, and Information

This paper assesses Sarkar's ([2003]) deflationary account ofgenetic information. On Sarkar's account, genes carry informationabout proteins because protein synthesis exemplifies what Sarkarcalls a ‘formal information system’. Furthermore,genes are informationally privileged over non-genetic factorsof development because only genes enter into arbitrary relationsto their products (in virtue of the alleged arbitrariness ofthe genetic code). I argue that the deflationary theory doesnot capture four essential features of the ordinary conceptof genetic information: intentionality, exclusiveness, asymmetry,and causal relevance. It is therefore further removed from whatis customarily meant by genetic information than Sarkar admits.Moreover, I argue that it is questionable whether the accountsucceeds in demonstrating that information is theoreticallyuseful in molecular genetics.

1. Introduction
2. Sarkar's InformationSystem
3. The Pre-theoretic Features of Genetic Information

   3.1Intentionality

   3.2 Exclusiveness

   3.3 Asymmetry

   3.4 Causalrelevance

4. Theoretical Usefulness
5. Conclusion

     

What Are the New Implications of Chaos for Unpredictability?

From the beginning of chaos research until today, the unpredictabilityof chaos has been a central theme. It is widely believed andclaimed by philosophers, mathematicians and physicists alikethat chaos has a new implication for unpredictability, meaningthat chaotic systems are unpredictable in a way that other deterministicsystems are not. Hence, one might expect that the question ‘Whatare the new implications of chaos for unpredictability?’has already been answered in a satisfactory way. However, thisis not the case. I will critically evaluate the existing answersand argue that they do not fit the bill. Then I will approachthis question by showing that chaos can be defined via mixing,which has never before been explicitly argued for. Based onthis insight, I will propose that the sought-after new implicationof chaos for unpredictability is the following: for predictingany event, all sufficiently past events are approximately probabilisticallyirrelevant.

1. Introduction
2. Dynamical Systems and Unpredictability

   2.1 Dynamical systems

   2.2 Natural invariant measures

   2.3Unpredictability

3. Chaos

   3.1 Defining chaos

   3.2 Definingchaos via mixing

4. Criticism of Answers in the Literature

   4.1 Asymptotic unpredictability?

   4.2 Unpredictability dueto rapid or exponential divergence?

   4.3 Macro-predictabilityand Micro-unpredictability?

5. A General New Implication ofChaos for Unpredictability

   5.1Approximate probabilistic irrelevance

   5.2 Sufficiently pastevents are approximately probabilisticallyirrelevant for predictions

6. Conclusion

     

Maddy and Mathematics: Naturalism or Not

Penelope Maddy advances a purportedly naturalistic account ofmathematical methodology which might be taken to answer thequestion `What justifies axioms of set theory?' I argue thather account fails both to adequately answer this question andto be naturalistic. Further, the way in which it fails to answerthe question deprives it of an analog to one of the chief attractionsof naturalism. Naturalism is attractive to naturalists andnonnaturalists alike because it explains the reliability ofscientific practice. Maddy's account, on the other hand, appearsto be unable to similarly explain the reliability of mathematicalpractice without violating one of its central tenets.

1 Introduction

2 Mathematical Naturalism

3 Desiderata and the attractionof naturalism

4 Assessment: Naturalism and names

4.1 Taking‘naturalism’seriously

4.2 Second philosophy (orwhat's in a name)

5 A way out?

6 Or out of the way?

     

Whence Philosophy of Biology?

A consensus exists among contemporary philosophers of biologyabout the history of their field. According to the receivedview, mainstream philosophy of science in the 1930s, 40s, and50s focused on physics and general epistemology, neglectinganalyses of the ‘special sciences’, including biology.The subdiscipline of philosophy of biology emerged (and couldonly have emerged) after the decline of logical positivism inthe 1960s and 70s. In this article, I present bibliometric datafrom four major philosophy of science journals (Erkenntnis,Philosophy of Science, Synthese, and the British Journal forthe Philosophy of Science), covering 1930–59, which challengethis view.

1 Introduction

2 Methods

3 Results

4 Conclusions

     

Newman's Objection

This paper is a review of work on Newman's objection to epistemicstructural realism (ESR). In Section 2, a brief statement ofESR is provided. In Section 3, Newman's objection and its recentvariants are outlined. In Section 4, two responses that arguethat the objection can be evaded by abandoning the Ramsey-sentenceapproach to ESR are considered. In Section 5, three responsesthat have been put forward specifically to rescue the Ramsey-sentenceapproach to ESR from the modern versions of the objection arediscussed. Finally, in Section 6, three responses are consideredthat are neutral with respect to one's approach to ESR and allargue (in different ways) that the objection can be evaded byintroducing the notion that some relations/structures are privilegedover others. It is concluded that none of these suggestionsis an adequate response to Newman's objection, which thereforeremains a serious problem for ESRists.

1. Introduction
2. EpistemicStructural Realism

   2.1 Ramsey-sentences and ESR

   2.2WESR andSESR

3. The Objection

   3.1 Newman's version

   3.2 Demopoulosand Friedman'sand Ketland's versions

4. Replies that Abandonthe Ramsey-Sentence Approach to ESR

   4.1Redhead's reply

   4.2French and Ladyman's reply

5. Replies Designed to Rescue theRamsey-Sentence Approach

   5.1Zahar's reply

   5.2 Cruse's reply

   5.3 Melia and Saatsi's reply

6. Replies that Argue thatSome Structures/Relations are Privileged

   6.1 A Carnapian reply

   6.2 Votsis' reply

   6.3 The Merrill/Lewis/Psillosreply

7. Summary

     

Consciousness and Action: Does Cognitive Science Support (Mild) Epiphenomenalism?

Questions about the function(s) of consciousness have long beencentral to discussions of consciousness in philosophy and psychology.Intuitively, consciousness has an important role to play inthe control of many everyday behaviors. However, this view hasrecently come under attack. In particular, it is becoming increasinglycommon for scientists and philosophers to argue that a significantbody of data emerging from cognitive science shows that consciousstates are not involved in the control of behavior. Accordingto these theorists, nonconscious states control most everydaybehaviors. Andy Clark ([2001]) does an admirable job of summarizingand defending the most important data thought to support thisview. In this paper, I argue that the evidence available doesnot in fact threaten the view that conscious states play animportant and intimate role in the control of much everydaybehavior. I thereby defend a philosophically intuitive viewabout the functions of conscious states in action.

1 Introduction

2 Clarifying EBC

2.1 Control and guidance

2.2 Fine-tunedactivity

3 The empirical case against EBC

4 Conclusion

     

纳里莫夫:苏联科学计量学的创始人——纪念纳里莫夫诞辰100周年

由于受到极"左"思潮的影响,纳里莫夫在青年时代历经磨难,遭受迫害。他矢志科学,即使在流放远乡的痛苦岁月里,仍然专注于科学研究。恢复自由以后,他在很短的时间里,就在科学研究方面取得一系列的成果,成为莫斯科大学教授、技术科学博士、控制论专家、俄罗斯自然科学院院士。其研究领域主要是化学控制论、化学数量分析学、试验数学理论。在科学学领域,他是世界上第一个提出"科学计量学"概念的学者。     

Empty Waves in Bohmian Quantum Mechanics

There is a recurring line of argument in the literature to theeffect that Bohm's theory fails to solve the measurement problem.I show that this argument fails in all its variants. Hence Bohm'stheory, whatever its drawbacks, at least succeeds in solvingthe measurement problem. I briefly discuss a similar argumentthat has been raised against the GRW theory.

1 Introduction

2 Three Theories

3 The Basic Argument

4 Branches and Worlds

5 Theory and Interpretation

6 Size Matters

7 Conclusion

     

Sklar's Maneuver

Sklar ([1974]) claimed that relationalism about ontology—thedoctrine that space and time do not exist—is compatiblewith Newtonian mechanics. To defend this claim he sketched arelationalist interpretation of Newtonian mechanics. In hisinterpretation, absolute acceleration is a fundamental, intrinsicproperty of material bodies; that a body undergoes absoluteacceleration does not entail that space and time exist. ButSklar left his proposal as just a sketch; his defense of relationalismsucceeds only if the sketch can be filled in. I argue that thiscannot be done. There can be no (relationalist) dynamical lawsof motion based on Sklar's proposal that capture the contentof Newton's theory. So relationalists must look elsewhere fora relationalist interpretation of Newtonian mechanics.

1 Introduction

2 The Relationalist Initial Value Problem

3 Sklar's Maneuver

4 Sklar's Initial Value Problem is not Well-posed

5 ConcludingRemarks

     

贝尔纳科学社会学思想再认识

认为贝尔纳科学社会学最突出的理论贡献有二:(1)力主科学的可计划性,并系统阐述了计划科学的理论基础和实施对策等;(2)对科学的社会功能问题进行了深入研究。指出在上述两个方面,贝尔纳的科学社会学也存在明显缺陷,而且对马克思主义哲学有某些误读,其中,对经济需要与科学发展关系上的机械理解即是典型的一例。     

The Somatic Marker Hypotheses, and What the Iowa Gambling Task Does and Does not Show

Damasio's somatic marker hypothesis (SMH) is a prominent neuroscientifichypothesis about the mechanisms implementing decision-making.This paper argues that, since its inception, the SMH has notbeen clearly formulated. It is possible to identify at leasttwo different hypotheses, which make different predictions:SMH-G, which claims that somatic states generally implementpreferences and are needed to make a decision; and SMH-S, whichspecifically claims that somatic states assist decision-makingby anticipating the long-term outcomes of available options.This paper also argues that neither hypothesis is adequatelysupported empirically; the task originally proposed to testSMH is not a good test for SMH-S, and its results do not supportSMH-G either. In addition, it is not clear how SMH-G could beempirically invalidated, given its general formulation. Suggestionsare made that could help provide evidence for SMH-S, and makeSMH-G more specific.

1 Introduction

2 Two Hypotheses: SomaticMarkers as Embodied Preferences, andas a Source of Farsightedness

3 Lack of Evidence for Somatic Farsightedness

4 Does MakingDecisions Require Somatic Markers, and can itbe Shown in theLaboratory?

5 Conclusion

     

The life and work of William Harvey

This year marks the four hundredth anniversary of the birth of William Harvey, discoverer of the circulation of the blood. His enunciation of this in his elegant De Motu Cordis et Sanguinis in Animalibus (1628) is of interest because it appeals not merely to anatomical and clinical observation but to quantitative methods. Although this is the work for which Harvey is best remembered he also did important work on the formation of the embryo and expounded the theory of epigenesis.     

Who is a Modeler?

Many standard philosophical accounts of scientific practicefail to distinguish between modeling and other types of theoryconstruction. This failure is unfortunate because there areimportant contrasts among the goals, procedures, and representationsemployed by modelers and other kinds of theorists. We can seesome of these differences intuitively when we reflect on themethods of theorists such as Vito Volterra and Linus Paulingon the one hand, and Charles Darwin and Dimitri Mendeleev onthe other. Much of Volterra's and Pauling's work involved modeling;much of Darwin's and Mendeleev's did not. In order to capturethis distinction, I consider two examples of theory constructionin detail: Volterra's treatment of post-WWI fishery dynamicsand Mendeleev's construction of the periodic system. I arguethat modeling can be distinguished from other forms of theorizingby the procedures modelers use to represent and to study real-worldphenomena: indirect representation and analysis. This differentiationbetween modelers and non-modelers is one component of the largerproject of understanding the practice of modeling, its distinctivefeatures, and the strategies of abstraction and idealizationit employs.

1 Introduction

2 The essential contrast

2.1 Modeling

2.2 Abstract directrepresentation

3 Scientific models

4 Distinguishing modeling from ADR

4.1 The first and secondstages of modeling

4.2 Third stage of modeling

4.3 ADR

5 Who is not a modeler?

6 Conclusion: who is a modeler?

     

Le Poidevin on the Reduction of Chemistry

In this article we critically evaluate Robin Le Poidevin's recentattempt to set out an argument for the ontological reductionof chemistry independently of intertheoretic reduction. We argue,firstly, that the argument he envisages applies only to a smallpart of chemistry, and that there is no obvious way to extendit. We argue, secondly, that the argument cannot establish thereduction of chemistry, properly so called.

1 Introduction

2The scope of the reductionist claim

3 The combinatorial argument

4 The strength of the ‘reduction’

5 Concludingremarks