Hartmann, Stephan

Reutlinger, Alexander

LSE Research Online

  Alexander Reutlinger and Stephan Hartmann Book review: Margaret Morrison // reconstructing reality  Article (Published version) (Non-refereed)     Original citation: Reutlinger, Alexander and Hartmann, Stephan (2017) Book review: Margaret Morrison // reconstructing reality. British Journal for the Philosophy of Science - Review of Books . ISSN 0007-0882  © 2017 The Author  This version available at: http://eprints.lse.ac.uk/73684/   Available in LSE Research Online: April 2017  LSE has developed LSE Research Online so that users may access research output of the School. Copyright © and Moral Rights for the papers on this site are retained by the individual authors and/or other copyright owners. Users may download and/or print one copy of any article(s) in LSE Research Online to facilitate their private study or for non-commercial research. You may not engage in further distribution of the material or use it for any profit-making activities or any commercial gain. You may freely distribute the URL (http://eprints.lse.ac.uk) of the LSE Research Online website.  Margaret Morrison // Reconstructing Reality bjpsbooks.wordpress.com /2016/08/31/margaret-morrison-reconstructing-reality/Reviewed by Alexander Reutlinger and Stephan HartmannReconstructing Reality: Models, Mathematics, and SimulationsMargaret MorrisonNew York: Oxford University Press, 2015, £44.49 (hardback)ISBN 9780199380275In her new book Reconstructing Reality (henceforth RR), Margaret Morrison’s main target is the kind ofinformation about the world (or, more specifically, about physical and biological systems) one can extract fromthe ‘reconstructive methods and practices of science’ (p. 1). To address this, Morrison focuses on three centralkinds of interrelated strategies for ‘recasting nature’ (p. 2) by using reconstructive methods and practices: (i)abstract mathematical explanations and understanding (Part 1 of the book), (ii) scientific models (Part 2), and (iii)computer simulations (Part 3). Hence, RR is the ambitious attempt to connect and analyse three major topics incurrent philosophy of science.Morrison does not approach these topics by developing a general philosophical theory of (various aspects of)explanation, understanding, models, and simulations in the sciences—where a general philosophical theoryconsists in the explication of concepts in the form of providing necessary and sufficient conditions. Instead, wethink that it is fair to describe Morrison’s project as ‘particularist’ or even ‘therapeutic’—at least in spirit, in thesense of philosophers such as Wittgenstein and Rorty. (Morrison sometimes chooses terms such as ‘naturalist’,‘minimalist’, or ‘deflationist’ to describe her own views.) Her major goal is to show that a general philosophicalaccount of explanations and understanding, models, and simulations cannot be had. Or more cautiously put,Morrison argues that the general accounts currently on the table are all flawed and unsatisfactory in that theseaccounts do not cover all (or even the majority of) paradigmatic examples of explanations and understanding,models, and simulations in the sciences. Either way, RR is a book with provocative meta-philosophical claimsand goals. Throughout the book, Morrison supports this particularist or therapeutic view by guiding the readerthrough a wealth of detailed case studies, each of which is intended to help undermine some aspect of somegeneral account proposed in the literature.Due to the sheer complexity and number of the case studies discussed in RR, it is impossible to summarize thecontent of the book in a review. What we will do instead is to highlight selected examples and claims from thethree main parts of the book in order to present central aspects of Morrison’s particularist and therapeutic project.In Part 1 (‘Mathematics, Explanation, and Understanding’), Morrison turns to the first kind of reconstructivemethod: an analysis of the role that ‘abstract’ mathematical assumptions play in the explanation andunderstanding of physical and biological phenomena. Morrison’s goal is not to argue for any generalphilosophical theories of explanation and of understanding. Following her particularist and therapeutic approachregarding both explanation and understanding in the sciences, Morrison instead adopts a minimalist viewaccording to which ‘neither understanding nor explanation is capable of being successfully codified into aphilosophical theory’ (p. 19). We take this to suggest that Morrison believes that there is no single account ofexplanations (such as the covering law account, the unification account, causal accounts, and so forth) thatdoesn’t face serious counterexamples and that covers all kinds of causal and non-causal (‘structural’)explanations.Morrison’s focus is on ‘abstract’ mathematical assumptions that are key to explaining and understanding certainphenomena and ‘deidealization [of the abstract mathematical assumptions] isn’t possible’ (p. 21). Here, it isimportant to highlight how Morrison draws a line between idealization and abstraction. Morrison uses theabstract/idealized distinction in a rather idiosyncratic way: ‘abstraction is a process whereby we describephenomena in ways that cannot possibly be realized in the physical world’ and ‘the mathematics associated withthe description is necessary for modeling the system’ (p. 20). By contrast, idealization ‘typically involves a1/3process of approximation whereby the system can become less idealized by adding correction factors’ (p. 20).Morrison presents two main examples illustrating explanation and understanding based on abstractmathematical assumptions. Both examples concern limit theorems. The first example is the renormalizationgroup explanation of phase transitions and universality involving the abstract mathematical assumption that ‘asystem contains an infinite number of particles’ (p. 27), the so-called thermodynamic limit. Her second example isfrom biology and concerned with abstract mathematical assumptions involved in the application of the Hardy–Weinberg law, such as the assumption that a population of organisms is infinitely big.Morrison defends such a reliance on mathematical assumptions against critics (including Callender and Earman,among others) who are portrayed as dismissing any idealization or abstraction as bad science if it cannot be de-idealized (p. 28). Morrison’s main line of argument against the critics is that their ‘line of reasoning quickly rulesout explanations of the sort we deem acceptable in other contexts’ (p. 28). One example that Morrison uses inorder to support this claim are cases of inter-theory relations. It is uncontroversial that characterizing therelations between theories (in physics) often involves limit theorems. However, the critics of limit theorems in thecontext of renormalization group explanations do not seem to be critical of limit theorems in the context of inter-theoretical relations, or so Morrison argues (p. 29). Furthermore, Morrison provides a stimulating and detaileddiscussion of how abstract mathematical assumptions are linked with statistical analyses in R. A. Fisher’s modelin population ecology (pp. 40–8).Morrison also tackles another big issue regarding so-called mathematical explanations. A large part of the recentliterature on this subject has revolved around making a sensible distinction between ‘purely’ or ‘distinctively’mathematical explanations of physical phenomena and merely mathematized explanations thereof (p. 50).Morrison proposes to side-step this issue in a particularist and therapeutic fashion: ‘the worry isn’t whether theexplanation is truly mathematical but rather whether there is any genuine physical information over and abovethe calculation or prediction of numerical values for specific parameters and effects’ (p. 55). To address thisextremely interesting question, Morrison returns to one of her main examples of an abstract mathematicalassumption figuring in the explanation and understanding of a physical phenomenon—renormalization groupexplanations of universality involving the thermodynamic limit. Morrison defends the claim that the abstractmathematical assumptions (such as the thermodynamic limit) within renormalization group explanations providegenuine physical information, because—without limit assumption—it is not possible to ‘show how the couplingconstants at different length scales could be computed; how critical exponents could be estimated; and, finally,that the universality followed, in a sense, from the fact that the process [of applying renormalization grouptransformations] can be iterated’ (p. 78).In Part 2 (‘Where Models Meet the World: Problems and Perspectives’), Morrison lays out several extended casestudies of models including Maxwell’s ether model and the Fisher–Wright model in population genetics. Morrisonuses these case studies to support her particularist and therapeutic stance. First, she argues against fictionalismabout models as being ‘at once too broad and too narrow’ (p. 90) targeting views by Cartwright, Frigg, Godfrey-Smith, and others. Morrison articulates her general line of critique as follows: ‘The general characterization ofmodels as fictions seems unable to do justice to the way models are used in unearthing aspects of the world wewant to understand’ (p. 97). Drawing on a complex historical case study of Maxwell’s ether model (pp. 98–112),Morrison attempts to show how a toy model (containing certain fictional elements) can be used to do preciselywhat fictionalists fail to capture—namely, to ‘unearth aspects of the world’ (including mechanical aspects, pp.110–11) we wish to explain and understand.The second target of Morrison’s particularist and therapeutic approach is the debate on scientific representationin the context of models. Morrison focuses on accounts of scientific representation by Cohen and Callender,Frigg, Giere, Suarez, and van Fraassen. Although Morrison is explicitly sympathetic to various features of theseaccounts, she argues that general philosophical accounts of representation—referring to truth, approximatetruth, isomorphism, and so on—are wrong-headed. Morrison advocates a ‘deflationary attitude’ (p. 125) towardsscientific representation. No general philosophical account of scientific representation is needed to state whysome particular model is useful for representing a target: ‘for example, Maxwell’s ether model was a usefulrepresentation, not because it was true or approximately true but because it could be used to generatehypotheses about how electromagnetic waves were propagated through space’. This ‘deflationary’ case study-2/3based approach is, according to Morrison, not an anything goes view since particular models are subject tospecific modeling constraint such as: ‘But that model [that is, Maxwell’s ether model] needed to represent theether as a mechanical system if it was to yield useful results’ (p. 128). Morrison’s more general lesson regardingscientific representation is this: ‘we don’t need a metaphysics of representation to understand how specificexamples of representational models can convey information about their target’ (p. 129). Furthermore, Morrisonprovides a detailed and critical discussion of the (alleged) role of inconsistencies in science (see Chapter 5).Once more, the upshot of Morrison’s discussion regarding (alleged) inconsistencies in science is particularistand therapeutic: ‘What is significant for philosophical purposes is that this is not a situation that is resolvableusing strategies like partial structures, paraconsistent logic, or perspectivism. No amount of philosophicalwizardry can solve what is essentially a scientific problem of theoretical consistency and coherence’ (p. 192).In Part 3 (‘Computer Simulation: The New Reality’), Morrison investigates philosophical issues arising in thecontext of computer simulations. One such issue concerns a central question in the recent epistemology ofcomputer simulation: the question whether computer simulations (or, computer simulation studies) provide thesame kind of knowledge as laboratory experiments do. A plausible reason for believing that computersimulations do not yield the same kind of knowledge as laboratory experiments is expressed by the ‘materialitycondition’, that is, ‘the idea that experimental inquiry typically involves not only a concrete physical system buttypically one that is made of the “same stuff” as the target’ (p. 211). Morrison does not accept the materialitycondition and puts more emphasis on ‘formal similarity’ between the model underlying the simulation and itstarget (p. 211). Simulations sometimes have the epistemic function of a traditional lab experiment (especially, butnot only, in situations in which we cannot perform traditional lab experiments): ‘for instance, measuring thevalues of critical exponents in second-order phase transitions is typically done via simulations. Given thatsimulation is capable of generating enough data to take account of an extremely large number of scenarios andconditions, it would seem that it can provide a much more reliable way to determine or measure the values ofparameters than experiment, even when the latter might be possible’ (p. 238). And in the same vein, Morrisonwrites: ‘the computational power provided by CS [computer simulations] allows us to uncover features ofphysical systems that may be implicit in the equations but would otherwise remain unknown’ (p. 250).However, she also points out that it too simple-minded (and ultimately not interesting) to exclusively focus on thequestion of whether computer simulations are just like ordinary lab experiments, and to then search for a generalphilosophical account of experiments applying to both traditional lab experiments and computer simulationstudies. The lesson of her particularist and therapeutic approach to the epistemology of computer simulations issummarized in two quotes. First: ‘my intention was not to argue that simulation is just like experiment but ratherto emphasize that the conditions under which we have faith in the experimental data are sometimes alsoreplicated by CS [computer simulations]’ (p. 249). Second: ‘the claim that simulation is, in essence, epistemicallyinferior to experiment is simply not true’ (p. 316). Morrison supports and supplements this view by (a) a detailedanalysis of the validation and verification of computer simulations, especially engaging with Winsberg’s work (pp.253–84), and by (b) analysing the role of computer simulations in the discovery of the Higgs boson.In sum, Morrison’s new book is a rich and provocative contribution to several core debates in current philosophyof science such as explanations and understanding, idealizations, models, and computer simulations. Even ifone is not convinced by all of the points that Morrison makes in (what we call) a ‘particularist’ and ‘therapeutic’style, one thing is for sure: if one wants to defend a ‘general philosophical account’ of some of the discussedtopics, then one has to respond to the criticisms forcefully presented in RR.Alexander Reutlinger and Stephan HartmannMunich Center for Mathematical Philosophy, LMU MunichMunich, GermanyAlexander.Reutlinger@lmu.deS.Hartmann@lmu.de 3/3

Book review: Margaret Morrison // reconstructing reality

Abstract

Similar works

Full text

Available Versions

LSE Research Online