Models, Perspectives, and Scientific Realism

Home , Bas van Fraassen, Constructive realism

MODELS, PERSPECTIVES, AND SCIENTIFIC REALISM:

ON RONALD GIERE'S PERSPECTIVAL REALISM

A thesis submitted to Kent State University in partial fulfillment of the requirements for the Degree of Master of Arts

Brian R. Huth

May, 2014

Thesis written by Brian R. Huth B.A., Kent State University 2012 M.A., Kent State University 2014

Approved by

Frank X. Ryan, Advisor

Linda Williams, Chair, Department of Philosophy

James L. Blank, Dean, College of Arts and Sciences

TABLE OF CONTENTS

ACKNOWLEDGEMENTS...... iv

INTRODUCTION...... 1

CHAPTER

I. FROM THE RECEIVED VIEW TO THE MODEL-THEORETIC VIEW...... 7

Section 1.1...... 9

Section 1.2...... 16

II. RONALD GIERE'S CONSTRUCTIVISM AND PERSPECTIVAL REALISM...... 25

Section 2.1...... 25

Section 2.2...... 31

Section 2.3...... 34

Section 2.4...... 37

III. PROBLEMS WITH RONALD GIERE'S PERSPECTIVAL REALISM AND SUGGESTED REVISIONS...... 50

Section 3.1...... 51

Section 3.2...... 55

Section 3.3...... 61

Section 3.4...... 66

BIBLIOGRAPHY...... 70

iii

ACKNOWLEDGEMENTS

I would like to thank my thesis advisor Dr. Frank X. Ryan for so diligently taking up this project with me midway through its completion. I would also like to thank my former thesis advisor, Dr. Gene Pendleton, for his generous time and assistance.

Additionally, I extend thanks to my committee of readers, Dr. Pereplyotchik, Dr. Byron, and Dr. Crawford for their time, honesty, and consideration of this thesis. Finally, thank you to my grandmother June Eisenmann for her never ceasing support.

INTRODUCTION

"If any problem in the philosophy of science justifiably can

be claimed the most central or important, it is that of the

nature and structure of scientific theories, including the

diverse roles theories play in the scientific enterprise."

(Frederick Suppe, 1977.)

Frederick Suppe's claim that the most important question for philosophers of science is that of the nature and structure of scientific theories was written in the introductory section of his 1977 work The Structure of Scientific Theories. There can be little doubt that philosophers have given great emphasis and attention to the inquiry into the nature and structure of scientific theories (see Chapter 1); however, as recently as

1989, there has been a domineering theoretical approach about the structure and nature of scientific theories that has won prevalence throughout the philosophical community: the so-called semantic conception of theories in science.1

Frederick Suppe (1989) has traced the origins of the semantic conception of scientific theories back to the work of von Neumann, however, the common view seems

1 See Suppe 1989, p.3. Here, Suppe claims that the semantic conception has become the most widely held analysis of the structure and nature of scientific theories espoused by philosophers of science. Suppe also claims that there has, as of 1989, yet to be any significant challenges made to the semantic conception in the literature. However, in the last decade or so, there have been several attempts to argue against the semantic conception as the correct way of conceptualizing scientific theories. For more on opposition to the semantic conception, see Portides 2005.

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to be, according to Paul Thompson (1988), that the semantic conception of scientific theories was first proposed in the works of Evert Beth and Patrick Suppes in the late

1940s and 1950s as a reaction against the syntactic accounts of scientific theories of the logical positivists. Syntactic accounts of theories identified scientific theories with a body of theorems stated in a singular and particular language chosen for the theory, while semantic accounts identified theories by identifying a class of structures or models which could be described in radically different ways in various languages (van Fraassen, 1980:

44). The semantic conception is then an attempt to characterize the structure of scientific theories as being clusters or families of models, while the syntactic conception of theories presented an axiomatic theory system which formulated scientific theories as a set of theoretical laws written in a particular language (the language of first-order predicate logic).

Since the semantic conception is an approach that utilizes models -- which are (in the sense they are here being used) concrete, mathematical, or computational devices -- it is also referred to as the model-theoretic approach to scientific theories. 2 Within the model-theoretic conception ('MTC' henceforth) the models of a scientific theory are of paramount importance, for it is the models of the theory that provide the means, but not necessarily the mode, of representation. The models of which constitute scientific theories within MTC are usually characterized as being abstract and, often, non-linguistic

2 Mauricio Suárez has pointed out that the name 'semantic conception of scientific theories' is perhaps a misnomer, for it suggests a kind of syntax/semantics distinction in linguistics -- a distinction of which is often not present within certain model-theoretic approaches to the structure and nature of scientific theories (See Suárez, 2005: 35). Bas van Fraassen is one such model-theoretician. In order to avoid being ambiguous about whether or not I am speaking of a model-theoretic approach that incorporates partial linguistic entities ( e.g. Suppes, 1961), I will thus refer to the semantic conception as the model-theoretic conception from now on.

entities whose sole purpose is to function as items of representational value: One uses a model or group of models to represent a domain of phenomena.

In recent years, MTC has gained influence not only within the field of philosophy of science (see Chapter 1), but a thinned-out version of the approach has also found its way into commercial pop-science books such as in Stephen Hawking and Leonard

Mlodinow's book The Grand Design, where the two scientists claim to advocate an approach of which they call "model-dependent realism." Additionally, Bailler-Jones

(2009) recently published a rather interesting and varied series of interviews involving practicing scientists' own accounts of the use of models in science, further escalating the interest of how models fit into the structure and nature of scientific theories.

In this paper, I will be addressing one issue that has recently surfaced as a criticism of MTC, viz. the topic of scientific realism. I am not, however, concerned with whether or not there can ever generally be any adequate kind of scientific realism within

MTC. After all, many proponents of MTC do not even classify themselves as realists: van

Fraassen is classified as an anti-realist, Suppe calls himself a "quasi-realist," etc. Neither is it my intention to argue whether or not MTC can sustain an adequate representation of scientific theories as it claims to do. I am solely here concerned with one variation of

MTC and whether or not there can be a scientific realist account within the framework of that specific variation. The variation of which I am referring to in the preceding sentence is Ronald Giere's so-called constructive realism or perspectival realism.3

3 Giere calls his approach "constructive realism" in 1988 and in 2006 refers to it as "perspectival realism" (which is, as Giere notes, nothing more than a continuation of his constructive realism).

Ronald Giere presents an account of MTC that claims scientific realism due to its capacity to represent, in some respects and to some degree, aspects of a mind- independent world instead of favoring some non-representational virtue of scientific theories such as problem-solving effectiveness (Giere, 1988: 7). I will later argue that

Giere's way of utilizing models as representational is entirely dependent upon the virtue of whether or not the models being used to represent a particular phenomenon are solely explanatorily successful, hence, solely effective problem-solvers. Thus, Giere's claim to scientific realism cannot be supported based upon his own definition of scientific realism.

Further, I will draw upon two arguments first made by Anjan Chakravartty in which

Chakravartty accuses Giere of the following: (1) that Giere's model-theoretic approach is instrumentalist, i.e. Giere values theories -- and evaluates theories by -- how effectively they conform to scientists' intention to explain and predict phenomena as opposed to how accurately they describe a mind-independent reality; and (2) that Giere's perspectivist account of science is a "philosophically controversial" version of perspectivism, meaning that in Giere's account there are only perspectival facts that are conditioned and evaluated solely from constructed frameworks. Taking off from Chakravartty's criticisms, I contend that Giere's methodological approach to science ultimately seeks to "save the phenomena," i.e. Giere's MTC approach fails to represent a mind-independent reality by means of scientific theories, but instead seeks to be an effective problem-solver -- a position which places Giere, by his own definition, firmly in the anti-realist camp.

In order to complete the task of denouncing Giere's realist claim, all of the relevant background information must first be explained. As MTC is a somewhat less

familiar characterization of the structure and nature of scientific theories than is the well- known (mostly for historical reasons) received view of the logical positivists, a brief historical introduction to the topic is warranted in order to familiarize the reader with the technicalities of MTC. Thus, the rest of this chaptered essay is outlined as follows.

Chapter 1 will be divided into two sections. First, MTC will be introduced from within its historical context, that is, as an alternative account to the received view of the structure and nature of scientific theories. This introduction will serve as a kind of preparatory guide, allowing the reader to transition from the well-known doctrines of the logical positivists into the somewhat less known domain of the model-theoreticians. Section 1.1 of Chapter 1 is thus devoted to a general account of the received view, while section 1.2 of Chapter 1 provides both the reasoning for favoring MTC over the received view as well as an historical platform from which the structural aspects of MTC can be explicated.

Chapter 2 covers Giere's methodological approach within MTC, which will include the following: Giere's account of constructivism and his naturalistic methodology; the manner in which models operate within Giere's method; the importance and role of theoretical hypotheses in Giere's method; the heuristics of Giere's perspectivism; and, finally, the manner in which Giere ties his methodology and perspectivism together with his realist claim.

Chapter 3 will be the final one, from which there will initially be a brief summarization of Chakravartty's criticisms of Giere's account of MTC followed by my own expansions upon this criticism, and finishing with a criticism of Giere's

constructivist approach. The first section deals with the notion of scientific realism in comparison to external-world or common-sense realism. Here, Chakravartty's first criticism that Giere is an instrumentalist will surface, and I will look to both defend and expand this criticism. The second section attacks Giere's perspectivism, where

Chakravartty will again be present, as I will make avid use of his accusation that Giere is committed to a "philosophically controversial" version of perspectivism. Finally, the last section adds further reflections and qualifications about Giere's version of MTC and ends with an overall consideration of possible alternatives to Giere's solution.

CHAPTER I

FROM THE RECEIVED VIEW TO THE MODEL-THEORETIC VIEW

MTC began as a response to the then prevalent account of the structure and nature of scientific theories: the Received View ('RV' hereafter). The main features of RV owe their genesis to the hard work of the logical positivists of the Vienna Circle. The members of the Vienna Circle, having been quite taken in by the then recent developments within the field of mathematics and logic, specifically the work done by

Frege, Russell, and Cantor, developed a conception of the structure and nature of scientific theories within the framework of mathematical logic (Suppe, 1977: 12). As a result of this influence, the logical positivist movement looked to reduce all arithmetic to logic and, subsequently, all of science to mathematical logic. RV thus incorporated the values adhered to by the positivists: There are two sources of knowledge, logical reasoning and empirical experience; the former is analytic, while the latter is synthetic.

The values inculcated into scientific theorizing by the positivists resulted in the assertion that a statement is meaningful if an only if one knows the conditions under which that statement is true or false. This assertion became known as the principle of verifiability.

Scientific theories were thus characterized by RV in the language of first-order predicate logic with identity, whereby scientific theories would be axiomatized. Keeping in consideration the principle of verifiability, the positivists divided the language in which a scientific theory was axiomatized into three disjoint vocabularies: a vocabulary

7 8

of logical constants, a vocabulary of observation terms, and a vocabulary of theoretical terms. All terms of the observational vocabulary were interpreted as directly referring to observable objects or observable properties of those objects. Theoretical terms, on the other hand, were given an empirical interpretation through appropriate statements called correspondence rules, which attempted to give an explicit definition of some theoretical term 'F' by linking F to some observational term 'O' in the following manner: x (Fx

Ox) (Suppe, 1977: 16). All theoretical terms were thus given phenomenal definitions by means of being materially equivalent to some corresponding observational term of the observational language.

Since MTC first arose as an alternative to RV, the earliest literature containing variations of MTC consists mostly of different accounts and characterizations of MTC accompanied by arguments about how and why these so-called semantic accounts were superior characterizations of the structure and nature of scientific theories than the accounts given by RV.4 However, as MTC began to gain momentum and mature, and as

RV began to fall from its lofty heights, philosophers of science began to expand and restructure the accounts given by MTC. These new accounts began to focus not on overcoming RV, but on explicating and producing a competent version of MTC of which could be said to be the most satisfactory account of MTC. Additionally, MTC had begun as merely an account of mechanics, however, upon the further maturing of the theory,

4 Most of the accounts given by model-theoreticians in concern to the superiority of MTC over RV focus on MTC's ability to bypass the structural syntax of RV. For more on this topic, see section 1.1 and 1.2 of this chapter.

MTC began to expand to other fields such as nuclear physics, cosmology, and even biology.5

SECTION 1.1

The original formulation of RV, as it was constructed by the logical positivists, was constantly revised throughout its course. In the following presentation of RV, it is my intention to preserve this general overall approach within RV without paying specific attention to the historical development of RV.6 This means that there will be features of

RV of which have been omitted for the sake of brevity. Unfortunately, when giving a general account of a particular theory that underwent decades of transitions such as RV, omissions are necessary evils. The scope of this section will thus include only the elements of RV that are so often criticized in the literature. Thus, the important elements to a general account of RV that will be scrutinized here are the same ones focused on by

Frederick Suppe (1977 and 1989): the distinction between observational terms and theoretical terms; the distinction between synthetic and analytic statements; the distinction between theoretical axioms and rules of correspondence; and the deductive nature of scientific theories.

Recall the brief characterization of RV outlined in the introductory section of this chapter. As mentioned there, RV axiomatized scientific theories in a language L of mathematical logic, and L was divided into three different vocabularies: a logical vocabulary; an observational vocabulary; and a theoretical vocabulary. The terms

5 See Thompson (1988) and Lloyd (1988) for MTC's application in evolutionary theory. 6 See Suppe (1977) for a full historical account of the development and decline of RV.

contained in the observational vocabulary were terms that could be interpreted as directly, i.e. as non-mediately, referring to some observable object or observable attribute of an object. In addition, all the terms of the theoretical vocabulary were given explicit definitions in terms of the observational vocabulary by way of correspondence rules.

Now, since it is the case that RV construed scientific theories as being axiomatized syntactic systems formalized in language L, and since it is the case that all theoretical terms were given their meaning by the syntactical and logical relationship between observation terms, theoretical terms, and correspondence rules, the resulting scenario for

RV is that the semantics of a scientific theory are given directly by the syntax of the theory (Thompson, 1988: 288 - 289). Indeed, if any element of RV can be called the "key element," it is that it is a syntactic conception of scientific theories (whereas, for comparison, MTC originated as a semantic conception of scientific theories).

Most of the proponents of RV were not interested in developing any kind of descriptive account of science, but were instead concerned with attempting to provide science with logical and epistemological foundations. As Ronald Giere writes, proponents of RV had a primary goal, and it was to “…justify, or legitimate, science, not merely to explain how it works” (Giere, 1988: 23). Thus, RV set about attempting to legitimate science within the framework of first-order predicate logic. However, the focus of RV on linguistic, i.e. syntactic, elements soon led to difficulties within the overall conception of RV.

Let us now then move to our first point of contention concerning RV: the distinction between observational and theoretical terms. The distinction between

observational terms ('Vo' henceforth) and theoretical terms ('Vt' henceforth) depends directly upon the principle of verifiability (Suppe, 1977: 18). Recall that the principle of verifiability asserted that a statement is meaningful if and only if one could know the circumstances under which that statement was true or false. Since, according to RV, the semantics of a theory are given by the logical syntax of L, and since the meaning and interpretation of a statement ultimately answer to the principle of verification, every interpretive account of a theoretical term as being materially equivalent to some observation term is an integral piece of the scientific theory itself.

There are several problems which arise in concern to the Vo/Vt distinction; however, I will here discuss only two of the more prominent difficulties: the problem of interpretation in highly theoretical sciences, e.g. quantum mechanics, and the methodological problem of multiple theory interaction. Let us begin with the former. A quick list of theoretical terms, viz. 'electron' and 'wave function', will serve as examples.

In order to preserve the principle of verifiability, as well as the Vo/Vt distinction, RV must construct a statement which identifies both 'electron' and 'wave function' as being materially equivalent to some observational term; this would both allow us to know the conditions under which 'electron' and 'wave function' are verifiable as well as preserve the empiricist doctrine of RV.

Electrons can be observed in a cloud chamber, meaning that the positivists could, in principle, construct a reduction sentence such as x (Ex Ox), where 'E' stands for 'is

an electron' and 'O' stands for 'is observable in a cloud chamber'.7 This provides us both with a material identification of the theoretical term 'electron' with an observational term

'observable in a cloud chamber' as well as stipulates the conditions under which the statement can be true or false, viz. the formal conditions under which the valuation of the universal biconditional is true. However, when dealing with cases of so-called "highly theoretical terms" such as the wave function in quantum mechanics, reducing the theoretical term 'wave function' to some observation term becomes nearly impossible

(Suppe, 1977: 80, 83).

The wave function, often symbolized as 'Ψ', is a variable quantity describing the quantum state (position and time) of a particle and how that particle behaves. In order to predict the probability of a particle's spatial location at a given time, one multiplies the wave function of that particle with itself, i.e. Ψ2.8 As Suppe (1977) contends, the Vo/Vt distinction can be maintained in such a situation if we look to characterize the wave function and other highly theoretical terms by way of their function instead of the observable circumstances under which statements containing these highly theoretical terms could be known to be true or false.9 However, constructing a formal characterization of the wave function in accordance with the principle of verifiability

7 Obviously, many other factors would actually need to be considered in order to accurately conclude that 'x (Ex Ox)' characterizes electrons, such as the trajectory space of the electron, the conditions of the appearance of the electron, the fact that what is being observed is a subatomic particle, etc. Otherwise, one might as well be observing an α-particle (also observable in a cloud chamber). However, for simplicity's sake, let us say that 'x (Ex Ox)' is all that is required for the moment. 8 This is to say, simply, that the probability of finding the particle described by a specific wave function Ψ at a given point and time is proportional to the value of Ψ2. 9 Suppe is still partial to the Vo/Vt distinction; however, his approach does not involve reduction sentences or the principle of verifiability. For more on Suppe's approach to the Vo/Vt distinction, see Suppe (1977) pp. 80 - 90 and Suppe (1989) chapter one.

seems outright impossible due to the dispositional nature of the wave function, its particularity to any given particle, and the overall problem of equating an entity expressing mathematical probability with an observable entity or property.

A further problem with the Vo/Vt distinction, and the last one of which we will here be concerned with, is the problem that arises from the axiomatization of scientific theories and the conjoint employment of multiple theories. Paul Thompson (1988) claims that in syntactic conceptions of scientific theories, two or more theories cannot be "easily or naturally" employed conjointly because the conjoint employment of theories requires a simultaneous axiomatization of all theories being employed into one single theory.

Thompson argues that the reason for axiomatizing multiple theories as a single theory stems from the role correspondence rules play, viz. as providing a "global meaning structure for an axiomatized formal system" (Thompson, 1988: 289). As separate theories, Thompson argues, certain theories will have different global meanings as provided by the set of correspondence rules, making interaction between theories difficult to employ. However, since science often does employ theories in a causal sequential manner, without axiomatizing the component theories as a single theory, Thompson argues that RV does not provide an accurate account of the way in which scientific theories are explanatorily used in scientific practice. Allow me to present an example from Thompson.

Take the theoretical term 'chromosome' in a theory about chromosomal segregation during meiosis. Now, 'chromosome' will, in RV, be linked (via correspondence rules/reduction sentences) to specific entities having such properties as

the following: staining properties, cell location, behaviors, etc. (Thompson, 1988: 289).

The problem arises when one takes into account the method of observation. The properties listed above, viz. staining properties, behavior, etc., are all properties that need to be observed under the assistance of a microscope. In order to explain why it is that these properties should be linked to anything called 'chromosome', one would have to provide a causal account of the microscope, which thus requires the introduction of outside theories such as optics and subatomic physics (ibid: 289). Now, according to

Thompson, the interaction between chromosomal segregation, optics, and subatomic physics presents problems in RV, for some terms of one theory will indubitably not occur in other theories, making those terms either meaningless in those other theories, or whatever meaning they can be given will be different from the meaning given in the term's origin theory because the term will be given meaning from within a different global meaning structure. In order for chromosomal segregation, optics, and subatomic physics to have the same global meaning structure, they must be axiomatized as a single theory with a single set of correspondence rules, which is, according to Thompson, just not accurate of how science actually operates.10

The distinction between analytic and synthetic statements is a further consequence

(and problem) for RV's principle of verification. The analytic/synthetic distinction is also directly linked to the Vo/Vt problem as well as the problem of the deductive nature of science. Analytic statements had two uses in RV: as correspondence rules (synonymy) and as mathematical/logical theorems (deductive/logical truth). The former kind of

10 If one's goal is to justify a methodological approach such as scientific investigation, then one's account should preserve the actual practice of that method.

analyticity was vehemently assailed by what has become known as the quintessential attack against the analytic/synthetic distinction: Quine's Two Dogmas of Empiricism, where Quine argued that the analytic/synthetic distinction is untenable due to the fact that the various explanations of analyticity as employed by the logical positivists (and others) are circular. I will not here go through the entirety of all six sections of Quine's Two

Dogmas, however, since Quine's attack was so very influential, and since it is simultaneously an attack on the principle of verifiability, the argument should be given some attention.

According to Quine, analytic statements can be one of the following forms: (1) analytic statements are true by their logical form, e.g. 'No unmarried man is married'; and

(2) analytic statements are true by way of meaning, i.e. analytic statements are analytic on the basis of synonymy, e.g. 'No bachelor is married' (Quine, 2003: 274). Notice that

RV attempted to do something very similar to the second kind of analyticity, that is, reduce a theoretical term to an observational term by way of synonymy. However, as

Quine notes in Two Dogmas, one cannot say that (2) is an adequate way of defining analyticity without providing a definition for synonymy, for the definition of 'analyticity' provided by (2) rests on the presupposition of synonymy. Of course, Quine goes on to analyze different kinds of synonymy and whether or not any of those variants can be an adequate account of analyticity. We need not go into an account of that here; suffice it to say that there have been significant challenges to the idea that one can equate two logically non-equivalent predicates and consider the reduction to be analytic (without circularity). Quine's challenge ultimately proved to be disastrous to RV, who relied upon

the reduction of Vt terms to Vo terms as an a priori analytic move requiring no synthetic justification.

Quine's challenge ultimately showed two very important flaws in RV: (1) that every method which presumes analyticity where one term is being reduced to a material equivalence of another (logically non-equivalent term) presumes synonymy; and (2) that the analytic/synthetic distinction being employed by RV in concern to correspondence rules is untenable due to the circularity of the characterization of analytic synonymy

(Suppe, 1977: 75 - 76). The analytic/synthetic distinction is thus not a veridical means of justifying the usage of correspondence rules and, further, the reduction of Vt to Vo is unsupportable as RV has conceived of it.

We have now considered some of the main objections to RV, namely, the problem of the Vo/Vt distinction and the analytic/synthetic distinction. In discussing these two objections, we have also mentioned the problems associated with the deductive nature of RV and the relation between correspondence rules and the theoretical axioms of theories. We will now proceed to an account of MTC and look at how MTC sought to avoid the pitfalls of RV.

SECTION 1.2

In order to explain how it is that MTC is able to bypass the problems associated with the theoretical/observation distinction -- specifically, how MTC avoids the problems associated with reduction sentences (e.g. x (Fx Ox)) -- we need to have a general account of what MTC is. Unfortunately, there exists a wide variety of different versions

of MTC; thus I will once again attempt to give a generalized account of a method that has undergone decades of development. However, even though I will here be presenting a general account of MTC, it is my intention to focus on the versions of MTC that are most relevant to Giere's own position.

Despite the various formulations of MTC, there are several elements of which all variants of MTC seem to share to some degree. I will call these elements ''Suppe's elements'' in honor of Frederick Suppe who was the first (that I know of at least) to give a characterization of the elements (see Suppe 1989). Suppe's elements are as follows: (i) theory structure/model structure: either a single model or a group/set/family of models,11

(ii) physical system12: the intended scope of a theory, i.e. the data which a model is representing, (iii) mapping relationships: the manner in which models represent physical systems and physical systems represent phenomena (e.g. isomorphism), and, finally, (iv) theoretical hypotheses: (often) linguistic entities making claims about the nature of the mapping relationship as it pertains to theory structure and some physical or real system.13A scientific theory is thus, according to MTC, a theoretical structure 'T' from which scientists can construct theoretical hypotheses making claims about the models of

T -- specifically, how those models map onto some physical system. A physical system is

11 Recall from the introductory section of this chapter that there are, in general, three types of models: concrete, mathematical, and computational. For a very good and clear classification of various model-types and various notions of what model-types are, see van Fraassen (1980 and 2006) as well as Weisberg (2013), esp. Weisberg (2013) pp. 15 - 23. 12 Physical systems (also known as models of data) are often optional, as they are usually laboratory experiments or simulations meant to model real-world phenomena. Testing theories against physical systems thus results in a model-to-model comparison. See Giere (2006) pp. 68 - 69. 13 Note here that for philosophers such as van Fraassen (1980), there doesn't necessarily need be any mapping relationship between phenomena and the physical system in the strong sense of a relationship. The relationship between phenomena and the physical system could be one of mere empirical adequacy.

merely an idealized account of some target real-world phenomena, such as a laboratory simulation of the formation of a black hole.

The preceding paragraph is something of a skeletal sketching of the most basic elements of MTC. We need to now turn to a more thorough investigation of these elements. It seems proper then to begin with the most important of Suppe's elements -- the "center stage" of MTC (as van Fraassen 1980 is wont to say): the concept of a theory structure, i.e. the family of models. Thus, in order to truly get an understanding of how

MTC operates, we must now turn to a discussion about scientific models and the role and operation of these models within MTC.

Demetris Portides (2008) rightfully claims that the concept of a model in science, due to the various meanings of the term 'model', is a notoriously difficult concept to discern. Indeed, Portides suggests that since models are fundamentally linked to the notion of representation that the best way to understand what a model in science is should be through an analysis of what the referred to model intends to represent

(Portides, 2008: 385 - 386). Models are intended to represent phenomena in various ways depending upon the type of model and the intended mapping relationship between the model and the physical system being modeled. Here, I will briefly sketch various kinds of models and how they might represent phenomena.

Let us first begin with the basics. A model, in general, is often an abstract entity of which is meant to represent a physical system. Philosophers use models in a variety of ways and for various purposes. As mentioned previously, Michael Weisberg (2013) classified three basic categories of models. These three categories are as follows: (i)

concrete models: "physical objects whose physical properties can potentially stand in representational relationships with real-world phenomena;" concrete models are then often physical iconic (even canonical) models, meant to stand, usually, in an isomorphic relationship with their intended representation;14 (ii) mathematical models: "abstract structures whose properties can potentially stand in relations to mathematical representations of phenomena"; such as, for example, the model for universal gravitation, of which can be characterized in mathematical English as 'F = Gmm'/r2'; and, finally, computational models: "sets of procedures that can potentially stand in relations to a computational description of the behavior of a system;" for example, Thomas Schelling's segregation model shows a series of bitmap sequences of which show how racial segregation can occur over time even when there isn't any overt racism present .15 Here, then, we have three different kinds of models, each with its own capacity for representation: concrete models represent in physical, often isomorphic, similarity; mathematical models can represent in a variety of abstract ways, such as through abstraction and idealization; computational models represent via comparison between an ideal, often localized, system and a set of computations.16

In MTC, models provide the semantics17 for a scientific theory; thus, by classifying a set of models, proponents of MTC are able to draw their semantics from a

14 See Suppe (1977) p. 97 for an example contrasting mathematical and iconic models. 15 The preceding quotes of this sentence can be found at Weisberg (2013) p. 7. 16 As we will see in Chapter 2, Giere claims that all models represent by way of similarity. 17 Specifically, in the typical account of MTC, the semantics of a theory are provided by defining a class/set of/cluster of/family of models. Typically, one defines this class via set-theoretic types or state space/topological structures. Ronald Giere, whose own unique version we will be looking at later in this paper, seems to take a very non-typical approach by claiming that the cluster of models is defined by a

domain of which is not bound by necessity to linguistic formalisms as is the syntactic account given by RV. Paul Thompson characterizes this differentiating feature of the semantic view as opposed to the syntactic view as follows:

...an adequate... approach to the structure of scientific

theories consists in the direct specification of the models

(i.e. semantics) and not in the specification of a linguistic

axiomatic-deductive system (i.e. syntax). The significant

differences, therefore, between syntactic and semantic

accounts are the nature of adequate semantics of a scientific

theory and of an adequate (logically and heuristically)

formalization of a scientific theory.

(Thompson 1988: 287).

Where RV views scientific theories to be axiomatized entities characterized by syntactical features, MTC views scientific theories as being groups of extra-linguistic entities (i.e. models) describable by a number of different linguistic formulations. Merely examining the linguistic formulations of a theory is not enough for understanding theories in MTC but must additionally include the specification of a group of extra-linguistic models which are meant to represent certain types of systems, e.g. mathematical, concrete, and computational.

The semantic capacity of MTC, viz. its ability to draw semantics from a pool of extralinguistic abstract models, allows for proponents of MTC to avoid characterizing constructive approach whereby the community of scientists construct exemplary models of whose linguistic characterization can be found within the canon of standard texts. More on Giere's conception later.

theoretical terms vis-a-vis reduction sentences. Thus, when one does wish to attempt to characterize a model by way of a linguistic formalization, since models are themselves extralinguistic, one is free to structure said formalization within any "sufficiently rich" language (Giere, 1988: 48). This "sufficiently rich" language is also the language in which theoretical hypotheses are often formulated, however, not all theoretical hypotheses are conceived of as purely linguistic entities in MTC. Since it is the case that

Giere considers theoretical hypotheses to be purely linguistic entities, we shall pay more attention to the version which formulates theoretical hypothesis purely within the theory formation language ('FL' henceforth). Since it is the case that theories need to be spoken about/written about, and since it is often the case that certain theories are often characterized from within distinct syntactical traditions (e.g. Lagrangian versus

Hamiltonian), the malleability of the FL of a theory allows for any of these sufficiently rich syntactical traditions to characterize models, i.e. refer to the models and mapping relationships, while allowing for the possibility of mutually compatible translations (e.g. from Lagrangian to Hamiltonian18).

When it is the case that theoretical hypotheses are linguistic entities, their only two roles are (1) the assertion of some sort of relationship between models and physical/real systems, and (2) the characterization of some theory structure as formulated in FL. Thus, when asserting a theoretical hypothesis, one asserts an intention to use such- and-such sets of models and the proposed mapping relationship between the models and real system (French, 2008: 272; Giere, 1988: 48; Suppe, 1989: 82). The mapping

18 As in taking the Legendre transformation.

relationship being expressed varies depending upon which model-theoretician you ask.

For example, in van Fraassen's case (esp. van Fraassen 1980), models represent phenomena by way of an isomorphism relationship (one-to-one and onto), whereas

Frederick Suppe (1989) claims that models represent phenomena by way of idealization and abstraction, and Ronald Giere (1988 and 2006) claims that models have a relationship of similarity with phenomena. For example, Giere (1988) usually uses mathematical English as his FL. He will then have a target phenomenon to be explained, and selects groups of models as his theory structure. The theory structure is then what is intended to explain the target phenomenon (this is the second role theoretical hypotheses play). Next, Giere postulates the relationship of similarity of which is to hold between his selected theory structure and the target phenomenon (this is the first role theoretical hypotheses play).

We know that in MTC a theory is identified with a class of models. Now, these models may, indeed, employ various model types such as Weisberg's three model types listed above. For example, cognitive scientists often employ the usage of visuals such as neural synapses scans (concrete models), localized computational assessments of neural responses to various stimuli, e.g. vision (computational models), as well as complex quantitative theories of cognition (mathematical models). Now, of course, there can be overlap between models, i.e. models can be applied together in a conjunctive fashion.19

Thus, models can be built out of other models, making a kind of super model. For example, Newton's universal gravitation law is built up out of the classical mechanics

19 Indeed, according to Thompson (1988), the flexibility of the same model to be used in various theories and in relation to various models is one of the most attractive features of MTC.

models for mass, force, the gravitational constant, and the geometrical relation of distance. These smaller models, mass, force, etc., are atomic models in classical mechanics: they are some of the fundamentals of classical mechanics. When models are combined to make new models, and a collection of these models are characterized as a single entity, we call that entity a theory structure. The relationship of representation between models and phenomena is called a mapping relationship; and the theoretical conjectures espousing the theory structure and the manner (or manners) in which the models of the theory structure map on to physical systems are the theoretical hypotheses.

Thus, whenever a theory is proposed, that theory propounds a family of models (theory structure) as well as theoretical hypotheses claiming some kind of mapping relationship between the family of models and a targeted physical/real system.

In order to be explicit about how MTC differs from RV, allow me to present an example. In RV, we define a set of axioms A such that A is the set of reduction sentences of which define some theoretical term F. Now, we have already seen how such sentences as those contained in A would appear, and have also discussed the problems associated with this approach, viz. reduction sentences as formalized in first-order predicate logic are not an adequate means for a robust account of the semantics of theoretical terms. The alternative account is then the one presented by MTC. In MTC, one proposes a theory T by characterizing a family of models M of which is definitional of T. The relationship between T and M is thus a trivially true one, since T is the theory defined by the set M and M is the set of models of which defines T. Now, the syntactic sentences of which are used to classify the set M as being the models of which define T is

a set of sentences S formulated in FL (whatever sufficient language FL is, e.g.

Mathematical English, set-theoretic types, etc.). Thus, a scientific theory might utilize S as its FL, where S is, say, mathematical English, or French, or Latin, or Peano arithmetic.

As long as the FL is sufficiently rich enough to characterize the models of the theory structure, a scientist is free to choose his/her FL. A theory is thus free to use any sufficiently rich set of sentences in any sufficiently rich language in order to characterize its set of models. However, one must keep in mind that whatever set of sentences is being used to characterize M, that set of sentences falls short of the actual semantics of the theory: it is merely a kind of place-holder or heuristic of which allows us to sufficiently characterize the set of models of which T employs. In MTC, S is not reducible to M (as it would be in RV), since S can be sundry languages all of which are used as a means of communicating about theories.

In summary thus far, we have gone over the historical development of MTC as a competing alternative to RV. From this historical development, we have learned that the most important element of MTC is the notion of a scientific model. However, as noted, scientific models are notoriously difficult to discern, thus making their explication rather difficult. I hope to have presented a general and well-rounded account of what models are and how they relate to phenomena from within a theory structure. With a working knowledge of what exactly MTC is, we must now turn to the real matter at hand: Ronald

Giere's constructive realist account of MTC. In the following chapter, I will present

Giere's specific account of MTC and then, more scrupulously, analyze the foundations for Giere's claim to realism.

CHAPTER II

RONALD GIERE'S CONSTRUCTIVISM AND PERSPECTIVAL REALISM

In order to understand how Giere's version of MTC operates, we need to first break it into its basic constituents. There are six important elements that must be elucidated in order for us to grasp Giere's version of MTC. Those elements are as follows: Giere's account is a constructivist account; Giere's account adopts a naturalistic approach to scientific theories; Giere's account demarcates between theoretical models and exemplary models; Giere's account gives an explicit description of theoretical hypotheses; Giere's account also has a unique method of representation, viz. similarity; and, finally, Giere's manner of explanation in MTC is perspectival, meaning that different theories adopt different perspectives toward the target phenomenon to be explained. We need to also keep in mind that Giere's ultimate goal is to construct a "science of the sciences" (Giere, 1988). This means that Giere is attempting to analyze the structure and nature of scientific theories in a naturalistic and scientific manner. The goal of philosophy of science, Giere contends, should be to construct a theory of science of which would

"...serve to explain the phenomenon of science itself in roughly the way that scientific theories explain other natural phenomenon" (Giere, 1988: 1).

SECTION 2.1

In this section, I will be dealing with two aspects of Giere's constructive realism:

Giere's constructivist claim as well as his naturalist claim. Giere (1988) repeatedly makes

25 26

the claim that constructivists are intrinsically naturalists; however, Giere's own version of constructivism is not to be confused with the "strong version" of constructivism such as the kind of constructivism that is associated with Bruno Latour and Steven Woolgar.20

Indeed, as Matthew Brown rightly notes, Giere's project seems to aim for a "middle ground" between the strong constructivist positions of sociologists of science and objectivist realism (Brown, 2009: 213). Further, Giere's naturalistic approach to science is not thesis-based but is methodological. This is to say that Giere opts to abandon the doctrine of naturalism as an epistemic thesis and instead adopts an approach that utilizes naturalism specifically as a method.

A naturalist, according to Giere, invokes specific domains of information in order to account for phenomena; these domains each contain information that can be appealed to without relying on any overt appeals to a transcendent realm, essences, or any a priori intuitions in order for their justification. Further, once a naturalistic explanation is found for some phenomenon x, there is no need to pursue a non-naturalist explanation of x.

Naturalism is, of course, a stance that one can take in connection to various domains outside of the philosophy of science, e.g. naturalistic epistemology, naturalistic language theory, etc. Depending on one's domain of interest, the naturalist doctrine operates in slightly different manners and invokes separate domain specific information. For

20 Latour and Woolgar's constructivism is based upon a laboratory setting, where they argue that the daily activity of the laboratory leads to the construction of facts from statements and the deconstruction of facts into statements: "Argument between scientists transforms some statements into figments of one's subjective imagination, and others into facts of nature. The constant fluctuation of statements' facticity allowed us approximately to describe the different stages in the construction of facts, as if a laboratory was a factory where facts were produced on an assembly line" (Latour and Woolgar, 2000: 203). Latour and Woolgar thus argue the position that scientific facts are arbitrarily constructed, whereas (as we shall see later) Giere attempts to push the idea of perspectival facts. For problems with Giere's attempted amelioration, see Chapter 3 of this essay.

example, in the philosophy of science -- specifically, within Giere's account of a naturalistic account of the philosophy of science -- the naturalist invokes information from within the domains of cognitive science, evolutionary theory, and the sociology of science (Giere 2008: 215). Contrast the domain specificity of a naturalistic approach in the philosophy of science with a naturalistic approach in the philosophy of language.

When dealing with language, a naturalistic approach might invoke information from the domains of linguistics and hermeneutics.

To adopt naturalism as a method rather than a doctrine is, according to Giere, to abandon traditional epistemology, i.e. to abandon the idea of Cartesian skepticism, forgo any appeals to a priori justification, and dismiss the idea that rationality is solely a categorical conception (Giere, 1988: 8 - 13). Instead, one should focus on natural causes, empirical experimentation, and, further, consider rationality as being simply "effective goal-directed action" (ibid: 9). Giere claims that naturalism as a method need not be justified in the traditional sense; its utility and problem solving capability are justification enough for its use.21

As mentioned above, a naturalistic philosophy of science, in Giere's account, often utilizes three resources for naturalization: evolutionary theory, cognitive science, and the sociology of science. Now, as pertains to evolutionary theory, Giere wants to argue that science evolves in a manner that is similar to the manner in which natural organisms evolve (Giere, 2008: 216). It is important to note, however, that the selection

21 See Giere (2006) p. 12. Giere's account of naturalism as a method invites obvious charges of circularity. I will not here go into deep detail about this charge, but will simply direct the reader to his reply on pp. 10 - 12 in Explaining Science.

process involved in Giere's evolutionary account of science is a social process. This is to say that people select one theory over another. Theory structures are proposed and last for as long as their utility and problem-solving effectiveness is greater than the utility and problem-solving effectiveness of competing theory structures. As Giere says, "if each of several options is satisfactory [i.e. their utility and problem-solving effectiveness are roughly equal], it makes no difference to the agent which it chooses" (Giere 1988: 158).

Further, since theory structures can adopt new models and/or replace older models, a certain model might be "selected" by scientists to replace an older model within some theory structure. An example of how theories are selected might best be parsed through example.

Let us say that there are three cosmological theories about the movements of the heavenly bodies: a, a geocentric theory in which each body revolves in a circular fashion around the earth; p a geocentric theory in which the observable bodies rotated around the earth in epicycles; and c a heliocentric theory that explained the rotation of the heavenly bodies by including the Earth as one of the rotating bodies. The proposal of a is found to have difficulties in accounting for certain celestial phenomenon, such as the retrograde motion of the planets. a then finds itself in competition with theory p, where the rotation of the planets is described as being epicyclical instead of circular. Now, p is found to describe the retrograde motion of the planets much better than is a, and thus p is

(socially) selected to persevere. However, after a while longer, p now finds itself in competition with theory c. Since c is found to be intuitively simpler, and thus less cumbersome to employ than p, c is eventually selected to persevere over p.

This process of social selection is compatible with Giere's version of naturalism in science, for it is the social setting of the community of scientists of which not only selects which scientific theories will persevere, but also constructs these theories based upon information gathered via instrumental and experimental means.22 According to Giere, scientists construct theories and, over time, select which theories will persevere by observation and judgment. This is the sociological aspect of Giere’s naturalist account of science; however, Giere's version of social construction and selection is not to be equated with the kind of laboratory social construction espoused by Latour and Woolgar. Where

Latour and Woolgar argued for the construction and deconstruction of facts based upon laboratory observation (see note 21 above) ,23 Giere extends the world of discourse to involve what Giere (2006 and 2008) refers to as the "total distributed cognitive system," which will ultimately involve not only laboratory scientists, but the measuring instruments used by those scientists as well as the entire community of scientists and the entirety of peer reviewed journals pertaining to the topic under investigation.

According to Giere (who is here invoking the notion of a distributed cognitive system from the domain of cognitive science) the natural process of cognition is something that is distributed throughout the entire framework of the system (Giere, 2008:

217 - 218) . For example, let us say that there is a set Σ of which includes as one of its members the set S of each and every scientist employed by CERN. Now, Σ also contains as one of its members the set H of which is the set of all active and fruitful non-human

22 See Giere (1988): pp. 4 - 5, 59 - 60, esp. 78 - 79. 23 Giere (1988) does give an account of construction within the laboratory, however, his version is radically different than Latour and Woolgar's version. See Giere (1988) Chapter 5 "Realism in the Laboratory."

devices associated with the Large Hadron Collider (LHC). In Giere's account, set Σ is a local system, whereby local information concerning specifically the outputs of LHC is part of the entire cognitive process. Yes, that includes set H as well. However, Σ is indeed a member of a much larger set Γ of which contains the member P -- the set of all published and peer-reviewed scientific journals pertaining to the research being done at

LHC. It is, in Giere's view, set Γ which is constitutive of the entire cognitive process, and this includes both human and non-human inputs and outputs. Of course, the final judgments are made by humans, but the cognitive process of which leads to those judgments is naturally constituted by the interaction of the members of Γ. In this manner, then, we can now see how Giere accounts for a naturalistic account of the entire process of scientific model construction and selection.

We are now in a position to comment on Giere's version of constructivism. Giere contends that the manner in which scientific models are presented and formatted is entirely constructive. Let us return to our cosmology example of the models a, p, and c.

Now, in Giere's account, a is first constructed by means of observation and social interaction. This means that some group of individual(s) (the group could merely have one member after all) made some observations and constructed a model, or models, of which represent those obervations. The collected set of these models is theory a, and theory a's veracity will then be judged by the system's community of satisficers. Theories are then social constructs of which are first built up out of the representational models of an initial group of scientists. Once the theory has been sufficiently constructed, it is

opened up to judgments from within the whole system (usually by way of publication in a peer-reviewed journal).

We have now covered Giere's approach and method within the philosophy of science (i.e. naturalism) and have explained why it is that he considers himself to be a constructivist. We must now turn to the fundamental pieces of Giere's account of MTC: his notion of what a model is and the difference between exemplary models and theoretical models.

SECTION 2.2

Recall our discussion about models from Chapter 1; and recall the three kinds of models given as an example (concrete, computational, and mathematical). Now, whenever Giere refers to a model, what he intends is reference to any kind of entity which can be properly characterized as one of the three types of models outlined in

Chapter 1. Note here, however, that Giere does not himself make the categorical distinction between mathematical, concrete, and computational models that Weisberg does. In Giere's theory, the term 'model' is a general word for mathematical, concrete, or computational models. Giere (1988), though committed to the notion that models have concrete, computational, or mathematical content, does not care to distinguish between models on the basis of their content: a model is simply a model in Giere's theory, regardless of the content of the model. However, Giere does find it appropriate to distinguish models on the basis of a hierarchical order. According to Giere's theory, models can be better characterized as being either exemplary models or theoretical

models. All exemplary models are theoretical models, but not all theoretical models are exemplary models. Let us examine what Giere has to say about this distinction so that we might parse out a better understanding of what Giere has in mind when he refers to models in general.

Let us first begin with Giere's naturalistic approach. Now, as the type of methodological naturalist that Giere is (as outlined above), Giere does not want to fall back on any sort of non-trivial a priori justification for the validity of his models.24 Giere thus needs to appeal to some naturalistic basis in order to justify the basics, or first principles, of model construction. This feat is accomplished by an appeal to scientific textbooks (Giere, 1988: 63). Giere argues that all scientists begin their training by being inundated with simple models -- e.g. what a force is in Newtonian mechanics, or the difference between vector and scalar quantities -- and from these simple, atomistic models, complex/composite models are built, e.g. the linear oscillator. The question is now, where do these atomic models come from? Giere's response is to argue that the atomic models are constructed and promoted by scientists, allowing us to appeal to them as primary or basic constituents from which more complex models are built out of. The method remains naturalistic due to these atomic models being constructed socially by means of a complex cognitive network that exists as a relationship between communities of scientists as well as individual scientists themselves (see above).

Since all exemplary models are, in Giere's account, theoretical models, it makes sense to begin with the broader class, viz. theoretical models. A theoretical model is,

24 By 'non-trivial justification' I mean justification that is not a mere appeal to syntactic structures.

simply, nothing more than a model of which is applicable to a theory structure. All models, good and bad, are theoretical models so long as they can be used within a scientific theory and are socially selected to do so by the community of scientists. So, in addition to exemplary models such as scientific laws, models such as the Lotka-Volterra model of predation and even the hue circle in color theory are (purely) theoretical models. We now turn to exemplary models.

Certain models, sometimes complex and sometimes atomic, are considered, by

Giere, to be exemplary models. Exemplary models are those models that are so often found in the standard introductory science texts. These highly idealized systems, such as the simple harmonic oscillator, are models of which are generalized to a very high degree in order for them to ideally be applied to a wide variety of possible situations. Thus, the simple harmonic oscillator can be idealized to fit into any system that has elasticity and inertia (e.g. a mass connected to a rigid foundation by means of a spring) and can be subsequently used in conjunctions with Newton's Second Law.

All models are abstract and idealized, for if they were not, then we would need to construct new models for each and every system being represented (this includes temporal parameters) which is just not a feasible endeavor. This does not, however, mean that all models are exemplary models; for an exemplary model is something of which is an exemplar of models, and this is to say that exemplary models are the models that scientists look at when they aim to construct new, context-dependent models such as the

Foucault Pendulum of which has a very specific and patterned oscillation.

SECTION 2.3

Since it is the case that models are abstract entities whose only linguistic characterization is merely definitional, it follows that models themselves are not linguistic entities; however, in Giere's account, theoretical hypotheses are linguistic entities. Theoretical hypotheses are "...statement[s] asserting some sort of relationship between a model and a designated real system (or class of systems)" (Giere, 1988: 80).

Theoretical hypotheses are then statements, which can be true or false, that assert that some model m stands in relation R to some real world system x. Now, the question is the following: what kind of relationship do theoretical hypotheses claim exists between a given model m and a real world system x? Giere tells us that the relationship cannot be one of truth valuation for the following reasons: no model is literally true of its intended real system,25 expressions of truth between models and real systems would constrain what models could be used in various situations,26 and, as concerns the notion of approximate truth, there can be no such thing as approximate truth! In Giere's system, there is only a bivalent truth system, either the valuation of R is false or the valuation of R is true: there is no in-between. In Giere's own words, "Approximately true implies "not exactly true," which means false..." (Giere, 1988: 106).

25 Indeed, as noted above, Giere claims that scientists are aware of this point and that they are not concerned with constructing literally true models. 26 For instance, scientists will often use Newtonian mechanics when dealing with kinematics that do not approach near light speed, while the mechanics of Einstein must be employed for any speeds reaching near light speed (See Hawking and Mlodinow 2010). Giere's claim is that if the relationship between models and real systems is one of truth values, then either one or the other scenarios presents itself: either what is really true changes from low-velocity kinematics to high-velocity kinematics, or scientists are using at least one blatantly false theory.

So, if R is not claiming a representational relationship between m and x as truth- functional, then what is R claiming? In Giere's system, R is asserting a similarity relationship between m and x. Now, a theoretical hypothesis can be true or false dependent upon whether or not the claimed similarity relation R obtains between m and x; however, the valuation of R is not objective: Giere admits that any system x can be considered similar to any model m (Giere, 1988: 93). Prima facie, Giere's admission that any system may be similar to any model by some account makes his similarity relationship seem vacuous. 27 Thus, in an attempt to ameliorate this problem, Giere imposes specific qualifications upon his notion of similarity in an effort to restrict nonsense applications of the similarity relationship. These qualifications are the respects in which m can be similar to x and the degree in which m is similar to x. The respects in which a model can be similar to some physical system are what allow Giere to avoid the accusation that similarity is a vacuous relationship.

Giere defines 'respects' as follows: "The respects in which similarity may be claimed can only be those represented in the model. One cannot claim... that a mechanical system is similar to a classical model with respect to color simply because there is nothing which represents color in any classical model" (Giere, 1988: 93). The respect in which a model can represent phenomena is the manner in which a model can represent phenomena. Thus the respects in which a model can be similar to a real system are determined by the content that the model expressively claims to represent. This is to

27 Giere's admission seems particularly influenced by Nelson Goodman. For example, what is the similarity between a model of light propagation and the planet Mars? Answer: Mars is an entity and the model of light propagation is an entity. The similarity between the two is completely arbitrary and vacuous.

say that the respects in which a model can be similar to a real system are inherently contained within the model: if the model claims to represent phenomena x1, x2, x3, then it cannot be claimed to have similarity with phenomena x4, x5, x6, and so on.

Now, the degrees to which a model can be similar to a real system are not inherently expressed in the model's characterization. The degree of similarity is the measurement of how similar m is to x based upon how well m "fits" with x (Giere, 1988 and 2006), as determined by scientific experiments, observations, and judgments. 28

Theoretical hypotheses assert just how much degree of similarity there is between the model m and real system x. For example, a theoretical hypothesis may claim that there is a "high" or "low" degree of similarity between m and x.

I have explained Giere's attempt to maneuver around the problem of ambiguity in his notion of similarity, however, I would like to now point out that, though Giere has proposed a notion of theoretical hypotheses that seems, perhaps, intuitively friendly toward our common conception of scientific theories, he has not done anything to avoid ambiguity in reference to similarity. The problem still remains: how do scientists adjudicate between models? The notion of similarity here espoused by Giere seems overly vague as a means of deciding between competing theories. Giere gives us little to assuage our fears. He merely claims that as long as one model "fits" better in a certain context than another, then the former theory is favored over the latter (Giere, 2006: 64 -

28 Giere's notion of fitness is not very well defined in any of his works, and, indeed, he has been charged (by Chakravartty in particular) with being overly vague about what exactly "fitness of models" is. See Chapter 3 below.

65). Giere's notion of a similarity relationship leads to his scientific perspectivism, to which we will now turn.

SECTION 2.4

Giere's stance on realism has shifted slightly from his 1988 work Explaining

Science to his 2006 work Scientific Perspectivism; the former being an account of what

Giere calls "constructive realism" and the latter being, as Giere tells us in a footnote to

Scientific Perspectivism, a further extension of constructive realism: a perspectival realism. The goal of Giere's perspectival realism is to mediate between what Giere calls a

"strong objectivism" or "hard realism" and the constructivist accounts commonly found within sociological accounts of science. 'Hard realism', or 'objective realism' in the sense that Giere has in mind, refers to any stance of which claims that there are objective scientific truths, that there is a single unified scientific account of reality, or that scientific laws are descriptions of reality simpliciter, etc.29 Giere's overall goal is to present a perspectival realist account of science by characterizing science in terms of different perspectives, of which are intersubjectively objective.

I want to begin my account of Giere's realism by appealing to Matthew Brown's

(2009) work, where he outlines six of the major claims of Giere's 2006 perspectivism.

Brown's six points will serve as a kind of springboard into Giere's perspectival realism from which I will elucidate the overall structure. Brown's six points are as follows:

29 See the first chapter to Giere 2006.

1. Human and scientific observation and scientific theories

are all perspectival.

2. Perspectives are an asymmetric interaction between

human (biological, cognitive, social) factors and the world.

That is, humans and science have perspectives on the world

while the world has no perspective on us.

3. Perspectives are partial and of limited accuracy.

4. Perspectives are neither objectively correct nor uniquely

veridical: they are "intersubjectively objective."

5. Scientific truth-claims are relative to a perspective and

are about the fittingness of perspectives.

6. Representation is a quadratic, not dyadic relation.

(Brown, 2009: p. 214)

(1) and (2) are Giere's attempts to avoid both scientific objectivism and pure constructivism and of which, when taken in conjunction with (3), lead to (4) which removes any possibility that there might be an objective perspective that is "better than" any other perspective. (5) further limits the strength of any objectivism while (6) is an account of how (1) - (5) all fit together.

Here, I want to further elaborate upon each individual point above, beginning with point (1). Since Giere gives an account of his perspectivism as analogous to color perspectivism, I will here present Giere's account of perspectivism as a series of analogies with color perspectivism.

1. Human and scientific observation and scientific theories are all perspectival.

First, we have to explain how human and scientific observation is perspectival in

Giere's account. Giere (2006) asks his readers to consider the empirical fact that color identification is ubiquitous among human beings, the exceptions being those unfortunate individuals born blind or color-blind. Now, as color identification is ubiquitous among humans, it follows that, according to Giere, humans ubiquitously have a colored representation of the world. However, when Giere claims that humans experience the world as being colored, what he means is that our biological makeup results in our ability to distinguish between colored things. We do not experience the world as a series of various colors, but "...perceive aspects of the world itself, which aspects being determined by our particular sensory capacities" (Giere, 2006: 36). Color is, then, not an intrinsic property of the world in the sense that any creature with ocular capacities will experience color as we ourselves do, but is a phenomenon of which is a result of the process of a set of physical properties interacting in a particular way: Sets of physical properties are ordered by our ocular and cognitive apparatai, constructing colors as we perceive them. Our biological makeup thus determines the perspectival range in which we can comprehend the color of the received electromagnetic reflectance profile. Thus, my Cleveland Indians ball cap is not objectively blue and red, but is blue and red within my perspective.

The paragraph above brings obvious intonations of the seventeenth-century primary/secondary distinction of color. Giere cares very little for the distinction between

primary and secondary qualities in respect to color (perhaps even in general), 30 however,

Giere does say the following: "It is generally scientifically correct that... the physical constitution of the light together with the physical operations of the human visual system determine the color experience of a normal viewer." (Giere, 2006: 37). However, if one considers primary qualities to be objectively true of the object, then there cannot be such a thing as primary qualities, for all statements derive their truth valuation from within a unique perspective. In order to illustrate Giere's position, let me present an example in my own words that Giere (2006) gives comparing trichromats and dichromats.

Let us say that I am a trichromat (having color vision based on three primary colors, e.g. red, green, blue), while one of my roommates, let's call him Bob, is a dichromat (someone who has color vision based on two primary colors, e.g. blue and red). Now, let us say that there is a green rug with a red pattern on it. I, being a trichromat, see the rug as being green with a red pattern; however, Bob sees the rug as being an overall faded blue.31 Now, I am a trichromat, and Bob is a dichromat. This means that Bob's disposition toward color perception is biologically different from mine, and, thus, according to Giere, that one cannot adjudicate in terms of correctness/incorrectness between my perception of the rug and Bob's perception of the rug. Indeed, Giere claims, the rug itself is not objectively green with a red pattern, but is only green with a red pattern from the perspective of the trichromat. From the perspective

30 Giere cites the phenomenon of metamerism as an example that colors are not necessarily objective. Humans have relatively poor color discrimination, and a monochromatic light with wavelength around 580nm will produce the same color experience as will an "appropriate mixture" of two monochromatic wavelengths of 540nm and 640nm respectively. Additionally, the class of metamers for single-wavelength color includes various, and often radically different, electromagnetic reflectance profiles. See Giere (2006: 21 - 22) and his influence: Churchland (2005). 31 This example is taken from Giere (2006) p. 33.

of the dichromat, the rug is intersubjectively a faded blue. Thus, it makes no sense to talk about the truth of one type of perspective over another. There is no objective framework from which to say that certain primary qualities are objectively so-and-so without observation, and observation always imports some kind of perspective (Giere, 2006: 48).

Color vision is then, at best, intersubjectively objective.

We have discussed perspectivism in concern to human observation, now we must transition to scientific perspectivism. Recall our earlier discussion about models and constructive realism in Chapter 1 and section 2.1, specifically in concern to theory structure. Now, a theory structure is the family or cluster of models that compose a specific scientific research program. Giere's perspectivism, as far as I can tell, takes its

"view" from the perspective of a given theory structure. This is to say that when one has the intention of utilizing the theory structure of Newtonian mechanics to explain some phenomenon x, then one has a Newtonian perspective of x. However, say that for some reason one wanted to view phenomenon x (where x is some kind of light phenomenon) as being a wave entity instead of a ballistic-particle entity; one might then wish to take a different perspective of x that does not involve a ballistic-particle interpretation of x (as would Newtonian mechanics). Giere here makes a helpful analogy to maps, where he states that the intentional use of a given scientific perspective (as determined by the relevant theory structure) is akin to selecting a map (Giere, 2006: 77 - 80). Certain maps show more topography, and are more helpful when considering backpacking trips or vacation destinations to the mountains. However, certain maps focus more on roadways and highways, allowing one to better plan one's travel. Depending on one's intentions,

one selects a given map that better represents the target phenomenon (or task). According to Giere, science is very much the same in that it adopts a certain perspective that has a

"better fit" to explain the target phenomenon. However, a scientific perspective can draw upon various research programs at one time (the perspective can utilize and combine the models of different theory structures in order to create a new perspective for whatever intention the perspective is needed for). One could, then, use Darwinian evolutionary models within a cosmological theory structure, thus altering the traditional cosmological theory structure and slightly changing the perspective of the inquiry.

2. Perspectives are an asymmetric interaction between human (biological, cognitive, social) factors and the world.

This point is actually quite simply illustrated: humans have a perspective of the world, but the world has no perspective on humans (Giere, 2006: 32). The asymmetry is then from humans to world without the relationship being reciprocal. The world neither attempts to compute us humans in any kind of cognitive sense, nor does it have any intention of attempting to represent humans in any sense. The world, in Giere's view, just doesn't care about us at all. We, on the other hand, very much care about the world. We have intentions that help us form specific representations about the world and, in addition, these intentions are computed in various fashions. The computations referred to in the preceding sentence are what provide our perspectives, and they are mostly influenced by our biological dispositions, the distributed cognitive systems we participate in (like the one referred to in the previous section), and the social interactions of which we partake.

3. Perspectives are partial and of limited accuracy.

Giere contends that perspectives are always partial (Giere, 2006: 48), that is, that any given perspective at any given time is only a partial representation of all that is going on around the perceiver. Giere contends that there is no scientific perspective that can possibly encompass and explain everything in its scope. Indeed, Giere goes as far as to call for an abandonment of the search for absolute truths.32 Instead, what science can do is give a partial and perspectival representation of a limited range of phenomena at any given time, depending upon the intention of the agent or agents responsible. What this means is as follows below.

I want to again appeal to the notion of a theory structure as being that from which a perspective is derived. When a theory structure is applied with the intention of explaining a given phenomenon or set of phenomena, the perspective is automatically constrained by the exemplary models. This constraint allows scientists to select a theory appropriate for the representational task at hand. Now, there are sundry exemplary models which characterize theory structures, however, there is no fact or absolute truth behind them: they are, at best, very good approximations (Giere 1988 and 2006). If one wants to represent the kinematics of a certain class of relatively low-speed ballistic- particle phenomena as traveling through otherwise empty space, then one can easily implement the perspective of Newtonian mechanics, which includes all of the classical laws of mechanics. However, if one is attempting to represent a class of ballistic-particle phenomena traveling near or at light speed, then Newtonian mechanics no longer

32 See Giere 2006 pp. 15 and 16.

becomes the "best fit" or "best map" for the job, but, instead, a theory structure characterized by its ability to express ballistic-particle phenomena at near light speed becomes the best fit.

In every instance of representation in science, the intended phenomenon or phenomena to be represented is a finite set, either a singleton {x1} or a finite set or class of entities {x1, x2,..., xn}. Of course, each member of each set can also be seen as itself being a set, so that when one intends to represent {x1}, where 'x1' is the future trajectory of space travel of the Andromeda Galaxy, then 'x1' is here itself a set {y1, y2,..., yn} of all the stars and planetary objects, etc. of the Andromeda Galaxy. However, scientific representation does not, according to Giere (1988), represent any given phenomenon xi in its totality. What is meant by this is that when science aims to represent some xi, it is not the case that science is actually representing the sum total of the class of phenomena that make up xi, but often what is represented is an idealization or generalization of xi

(Giere 1988: 90 - 91). This is the kind of partial representation that is important to Giere's theory: the phenomenon being represented is never the phenomenon in its totality.

Further, the phenomenon being represented is being represented from a particular perspective, while other perspectives will represent the phenomenon differently.

This account of partial representation means that we can only have a limited amount of accuracy in scientific predictions, for as we represent a phenomenon in an ideal or generalized way and from within a particular perspective, we limit how much information is actually put into any theoretical predictions, thus making much of science

a matter of approximation.33 Since models represent by approximation, abstraction, or generalization, and since models are the means in which phenomena becomes represented within a certain perspective (the perspective of the model), it follows that models only partially represent phenomena, and in a limited way.

4. Perspectives are neither objectively correct nor uniquely veridical. and

5. Scientific truth-claims are relative to a perspective and are about the fittingness of perspectives.

Points (4) and (5) are intimately connected, thus I will here deal with them together. Recall the above example about Giere's stance on the perspectival domains of the trichromat versus the dichromat. Recall that, as I worded the example, I was a trichromat and saw the rug as being both green and red. Even though in the example my perspective of color was delimited to a certain range (due to my biological disposition), that range holds intersubjectively among all of my fellow trichromats. This is to say that if you are a trichromat, then you can see, for the most part, the same spectrum of colors that I can see. Now, let us presume that one of my roommates (not Bob) who is a trichromat walks into my room and asks what color my Cleveland Indians ball cap is.34 I respond that it is blue and red. My roommate, if he is telling the truth that is, will most likely agree with me that the ball cap is indeed blue and red. Presuming that the lighting in my room is adequate and that both my roommate and I are standing in a position that

33 See Giere (1988) pp. 80 - 82, and 102 -103. Notice that although Giere does not approve of the notion of approximate truth (see section 2.3), he is more than fine utilizing the notion of approximation in concern to similarity. More on this in Chapter 3. 34 I am here continuing to take on Giere's stance on the philosophy of color, though must note that Giere's stance is not my own.

allows us to view the ball cap with equal lighting, there should be little controversy between my roommate and I about the color of my ball cap. This kind of objective agreement between two agents of whom are dispositionally similar in that (i) their ability to perceive some phenomenon x is fundamentally the same and (ii) there are no contingent factors of which might alter the mechanism for perceiving x (such as lighting source) is what Giere means by intersubjective objectivity. If I were to get every single individual within the graduate department that I belong to, and place my Cleveland

Indians ball cap on a desktop under a singular white incandescent bulb and ask each person to write down the color of the ball cap on a piece of paper, wouldn't it be rather surprising if one of the individuals wrote something like ''pink and green"? It indubitably would, and this kind of objective agreement from within a shared perspective is the kind of intersubjectivity that is important to Giere's notion of perspectivism.

Perspectives are indeed not uniquely veridical nor objectively correct. Thus, the method of selecting a certain perspective or theory structure depends not upon unique truth claims formulated by hypotheses, but upon how well a theory structure "fits" the phenomena it is intended to represent.35 Thus, Giere's notion of similarity comes into play.

Scientists select a theory structure, or perspective, that is closest in similarity to the phenomenon it is intended to represent. Recall the previous example above about maps; we select a certain map with the intention for it to represent a target phenomenon.

35 As mentioned earlier, Giere gives no real criterion for fitness. Indeed, Giere writes "Representing aspects of real systems... does not require the existence of a general measure of similarity... I doubt that there exists any uniquely justifiable measure of this type" (Giere 2006: 64).

The same is true for theory structures (or at least this is Giere's claim). Recall our earlier example about representing light as a ballistic-particle phenomenon or a dynamic wave phenomenon. The debate about whether light is a particle or wave has gone on since at least the time of Newton and Huygens, however, one might ask which better characterizes light. Typically, in contemporary science, one represents light relative to the system being employed, e.g. electromagnetic spectrum, photoelectric effect, etc. Now, when dealing with light in terms of the electromagnetic spectrum, light commonly acts as if it is a wave, and thus we utilize the models of light as a dynamic wave phenomenon.

Whereas, as Einstein did with the photoelectric effect, when electrons are emitted from solids, liquids or gases when they absorb energy from light, the resulting photoelectrons are projected as ballistic-particle phenomena. Thus, depending on what degree of similarity is desired, one selects a representational perspective of a given phenomenon that is best "fitted" for the type of representation needed.

6. Representation is a quadratic, not dyadic relation.

Point (6) has been hinted at this entire section: the manner in which scientific representation occurs is quadratic, not (as is traditional) dyadic. What this means is that there is a four-place relationship between agent, model, phenomenon/phenomena, and intention: "S uses X to represent W for purposes P" (Giere, 2006: 60). This brings back constructivist elements of Giere's theory, for it is the agent, i.e. the scientist or group of scientists, doing the representing who constructs the actual representation. The scientist/agent S constructs a model X within a certain perspective/theory structure h for the intention P of representing a particular phenomenon W. Thus we might say that "S

uses X as a model of h to represent W for purpose P." It is still a quadratic relation, but now also emphasizes that X is a theoretical model from within some perspective h.

Representation thus begins with scientists and their intentions to represent some phenomenon/phenomena (Giere, 2006: 60 - 63). The perspective from which the phenomenon/phenomena will be represented is thus determined by the intention, or purpose, of representation. If one intends to represent blackbody radiation, one typically resolves to use the photoelectric effect in which photoelectrons are ballistic-particle phenomena. Mutatis mutandis for the electromagnetic spectrum being represented as waves. Now, as Giere emphasizes, whichever or whatever way scientists choose to represent a given phenomenon x does not make one perspective concerning x more uniquely correct than another. Indeed, much like the example of trichromats and dichromats, the perspective from which we represent x is merely a different perspective: neither is more correct than the other. Since theory structures, and thus perspectives, are constructions created by scientists, and since any and all truth claims made about the theoretical models of a theory structure are true or false only from within the perspective of the relevant theory structure, there is no situation where one perspective can be uniquely more true than another. Instead, the focus shifts to mapping the similarity of a particular perspective onto a physical system. If one perspective p1 is more similar to represent x than is another perspective p2, then p1 is the more appropriate choice. Again, the criterion for choosing fitness and judging similarity is vague in Giere's account, yet his method of model selection (see section 2.3) favors instrumentalist values. Thus we have what Giere claims to be his stance on realism: Scientists have a target phenomenon/

phenomena to be represented; the perspective in which the target phenomenon/phenomena is represented depends upon the fit of a constructed theory structure; a theoretical model is designed and hypotheses about that model are then formulated; a collection of test data is collected as model data to which the predictions of the relevant model can be compared against relative to the perspective being used (the theoretical model will itself be constrained by the theory structure being utilized); and finally, scientific claims are made based upon the resulting information from the model data and its comparison to the predictions of the model, from which one can say that from within the perspective of such-and-such theory structure, this-and-that is true. What Giere hopes makes him a realist (a moderate/non-objectivist realist) is that Giere is committed to the idea that there is an independent and external world (Giere, 2006: 88), and that science aims to represent that world to certain degrees and respects (Giere, 1988: 7) from within a perspectival context.

The next chapter will focus on issues concerning what exactly scientific realism is, including an analysis of external-world realism versus scientific realism. In the next chapter, I will be arguing that Giere is not, indeed, a scientific realist; though he may be a common sense realist about the external world, his account of the structure and nature of scientific theories leans him far more onto the side of the relativist than the realist.

CHAPTER III

PROBLEM WITH RONALD GIERE'S PERSPECTIVAL

REALISM AND SUGGESTED REVISIONS

The last chapter outlined Ronald Giere's version of MTC as well as presented

Giere's version of realism within his conception of MTC. In this chapter, I will attempt to scrutinize Giere's realist stance in the following ways. To begin, the sundry variants of versions of scientific realism calls for a brief conceptual analysis of what scientific realism is, with particular attention being paid to Giere's version of scientific realism.36

The argument which I will push in concern to Giere's version of scientific realism is as follows: that Giere's own requirements for scientific realism are indeed conducive toward a naive external world realist position; however his actual approach -- that is, his version of MTC -- fails to satisfy his own requirements for scientific realism.

Several issues of Giere's MTC conception will be analyzed in relation to the above argument, specifically the following: the manner in which theoretical models are constructed and used as well as their continuity of usage within Giere's conception of

MTC; the manner in which models are used as partial representations of real/physical systems as well as the relationship of similarity Giere posits to adhere between models and the physical world; and, of course, Giere's perspectivism. What I hope to convince

36 Indeed, Anjan Chakravartty (2007) jokes that it is not the case that there are as many versions of scientific realism as there are scientific realists, but that there are probably as many versions of scientific realism as there are both scientific realists and anti-realists alike! Chakravartty's jest comically puts forth the difficulty in characterizing exactly what it is to be a scientific realist.

50 51

the reader of is that although Giere advocates a (moderate) realist position, his version of

MTC is actually far more conducive toward a relativistic position given the fact that (1)

Giere's own criteria for scientific realism are not satisfied by his own account, (2) the relationship between the perspective of a theory structure and a real system is far too vague under Giere's current usage of the similarity relationship, and (3) that Giere's encapsulated perspectivism creates a system of relative perspectival dependency of concern to factual claims made about real systems.

SECTION 3.1

Let us then begin our inquiry by briefly examining the notion of scientific realism.

In order to examine what scientific realism is, we must first demarcate scientific realism from what Michael Devitt (2008) refers to as common-sense realism. This conceptual distinction between scientific realism and common sense realism is a rather important point that I think is often overlooked by many philosophers of science. Michael Devitt

(2008) rightly makes the point that before one can accept scientific realism, one must first accept external world realism or, as he calls it, "common-sense realism" (Devitt, 2008:

226). I agree heartily with Devitt's claim, however, I would like to put more emphasis on the distinction than does Devitt. The reason for the emphasis on this distinction will become clear as we examine Giere's own criteria for scientific realism against his actual methodology.

What I am here referring to as external world realism is nothing more than the metaphysical doctrine of accepting the existence of a sensible37 world that is not dependent upon the mind. However, scientific realism, at least as how I am using it,38 requires the addition of at least three more steps: (1) scientific realism also implies that in addition to the mind-independent existence of a sensible world, the scientific realist is also committed to the existence of a non-sensible world of phenomena, e.g. the subatomic world; (2) scientific realism must also be committed to the idea that, to quote Anjan

Chakravartty (2007), "scientific theories correctly describe the nature of a mind- independent world... a [nature] that does not depend on minds, human or otherwise"

(Chakravartty, 2007: 4. Italics are my own)39; (3) scientific realism cannot be (entirely) committed to relativism.

Thus, in order for one to be a scientific realist, one must be committed to the idea that there is indeed a mind-independent world and that this world is describable by scientific theories. The real question is then "how does science describe this mind- independent world?" Many philosophers claiming to be scientific realists have developed extensive answers to this question, and the crux of their answer always, not surprisingly, hinges upon the relationship of which they posit to hold between scientific theories and the external world.

37 By 'sensible' I here mean anything that can be humanly sensed without instrumental aid. 38 I am here using a notion of scientific realism that is mostly influenced by Michael Devitt and Anjan Chakravartty. From Devitt (2008) I draw (1), from Chakravartty (2007) I draw (2). 39 To qualify Chakravartty's statement, when he says "correctly describes a mind-independent world" he is couching the statement within the practice of approximate truth. One could instead replace Chakravartty's statement with the following: "scientific realists aspire to theories that describe the mind-independent world to at least a high degree of approximation."

Given the above account of scientific realism, one can easily see how it is possible for one to be a realist without being a scientific realist. The scientific realist is committed to the idea that science aspires to represent a mind-independent reality. One could instead accept common-sense realism and deny the representational role of science in concern to a mind-independent world, favoring instead a different method of explanation. Further, there are theoretical, directly unobservable, entities postulated by science to which the radical empiricist might deny on the basis of the seemingly occult nature of these entities. This is to say that one might accept the representational role of scientific models purporting to describe observable entities (e.g. rocks and chairs) yet reject those models purporting to represent objects on the basis of non-observable entities

(e.g. the Higgs boson, electrons, germs, etc.).40 However, this is not to say that the scientific realist need be a reductionist in concern to the structure of reality; it does mean that the scientific realist must be committed to the representational role of models projecting the existence of unobservable entities: unobservable phenomena are at least a part of the mind-independent world.

Giere gives his own version of what scientific realism is. In his 1988 book

Explaining Science, Giere tells us that scientific realism is the view that "...when a scientific theory is accepted, most elements of the theory are taken as (in some respects and to some degree) [representing] aspects of the world" and that an anti-realist view of science is when "...theories are accepted for some nonrepresentational virtue... or for very limited representational virtues such as "problem solving effectiveness"" (Giere, 1988: 7).

40 A radical empiricist such as Nelson Goodman or Bas van Fraassen is most often compelled toward an instrumentalist conception of science.

What Giere has in mind as being a kind of nonrepresentational virtue, or a very limited kind of representational virtue, is the kind of empiricist line espoused by van Fraassen in

The Scientific Image, where van Fraassen perpetuates the notion of empirical adequacy, a doctrine of which makes no commitments to the truth or a belief in the reality of scientific theories but instead values scientific theories for their ability to "save the phenomenon," i.e. to simply explain the phenomenon consistently and in an operationally acceptable manner.41 We shall see in this chapter a strong similarity between Giere and van Fraassen, which again brings into question the veracity of Giere's scientific realist stance.

Giere's definition of scientific realism is somewhat vague: after all, what is the demarcating line between adequate means of representation? The claim that scientific realism is a stance in which scientific theories are seen as representational of aspects of the world needs to be further qualified than Giere's usage of "to some respects and to some degree."42 Since Giere is advocating some kind of demarcating line between adequate means of representation and inadequate means of representation, and since operational and instrumental values are not efficient enough to be representational in

Giere's account, it follows that Giere needs to qualify the degree of representation in science.

In principle, scientific realists should, indeed, be committed to the idea that scientific theories do represent the external world in some respect and to some degree, however, the problem is to qualify what exactly respects are and, even more so, what the

41 For more on Giere's stance toward van Fraassen, see Giere 2005. 42 The problem of respects and degree of representation will become more apparent in section 3.2.

degree of representation is. (The degree of representation, in Giere's account, is the degree of similarity between a model and real system.). Further, given that Giere's modus operandi in using similarity as his relation of representation, and given the vagueness of the relation of similarity, one must ask whether or not Giere's MTC theory actually does value the representational role of theories or whether he actually values their problem solving capability. This question shall be the topic of the next section.

SECTION 3.2

Anjan Chakravartty (2001 and 2010) has two rather cogent and compelling criticism of Giere's MTC approach. 43 Chakravartty (2001) claims that Giere's omission of an informative, non-arbitrary, and meaningful relationship between models and language must be supplemented with a relationship that is less ambiguous than Giere's cryptic usage of similarity. Indeed, Chakravartty contests that it does not matter how many models one stacks in-between a theory structure and a real system, ultimately some meaningful form of linguistic valuation must come into play (Chakravartty, 2001: 335).

One cannot merely say that the valuation of hypothesis h is true in that h claims model m represents phenomenon x in such-and-such respects and to such-and-such a degree of similarity as is stated by the hypothesis.44 The vagueness of degrees of similarity allows for ambiguity when evaluating whether or not the hypothesis is indeed true. A hypothesis

43 The first of Chakravartty's criticisms will be relevant here in section 3.2. The second criticism has been saved for Section 3.3, where I discuss Giere's perspectivism and its tendency toward relativism. 44 Recall that the respects in which a model can represent phenomena is determined by the model itself. This is to say that a model about predator-prey relations cannot model electromagnetic waves, for the predator-prey model says nothing about electromagnetic waves. The degree of similarity is then how much or little similarity the model has in its relevant respect of representing the target phenomenon.

might say that m has a high degree of similarity to x, but Giere never tells us what that means!

Giere (1988) is actually rather ambiguous about the importance of theoretical hypotheses. He claims that theoretical hypotheses are "statement[s] asserting some sort of relationship between a model and a designated real system" but that the relation itself of which holds between model and real system is not linguistic and thus cannot have a truth- value (Giere, 1988: 80). According to Giere, the role that truth-valuation plays in regard to theoretical hypotheses is a role of characterization. Imagine a scientist who has formulated the following hypothesis: "Model m represents phenomenon x in certain respects and to a high degree of similarity." Now, briefly setting aside the problem of vagueness in concern to similarity, let us imagine that the valuation of the scientist's hypothesis is true. What does that mean to Giere? The valuation of the scientist's hypothesis is affirming or denying an existence claim about the relationship between the model and the phenomenon, that is, the scientist's hypothesis is stating nothing more than that there is (or is not) some kind of similarity between m and x: "To claim a hypothesis is true is to claim no more or less than that an indicated type and degree of similarity exists between a model and a real system. We can therefore forget about truth and focus on the details of the similarity" (ibid, 81). The role of the truth valuation of a theoretical hypothesis is then nothing more than allowing one to characterize, i.e. allow one to talk about, the fact that there exists a relationship between model and real system, and that relationship is one of such-and-such respect to such-and-such degree of similarity. The

hypothesis is asserting the scope of the representation as well as the degree of similarity.

The real problem is, then, how to make sense of Giere's notion of similarity.

The greatest threat to Giere's notion of similarity is indeed its opaque and vague nature. Giere's (2006) attempt to ameliorate this problem comes by way of his introduction of agent intention. Recall that, for Giere, scientific representation is a quadratic relation: S uses M to represent X for purposes Y. Now, 'M' is some model or conjunction of models of which is meant to represent a real system. The intention of the agent/scientist -- signified by the 'Y' in the above quadric -- is meant to hone the degree of similarity to hold between M and X. Giere wants to leave the representational relationship between M and X (the phenomena being targeted) as being directly dependent upon the degree of similarity between M and X. Theoretical hypotheses, in

Giere's system, are the tools which scientists use to characterize what degree of similarity they are intending to use M to represent X.

Giere's emphasis on agent intention seems to import some importance to theoretical hypotheses above characterization, since the representational force of the similarity relation is now joined with the agent's desire to represent. The role of similarity is now qualified as the role of similarity according to the intention of the agent doing the representing. The degree of similarity between a model and real system might

(presumably) actually be higher than the intention of the agent. However, the truth of the hypothesis is only evaluated relative to the agent's intention to represent the target phenomena to such-and-such degree as specified by the agent.

The problem with introducing agent intention as a means of qualifying similarity is, as Chakravartty argues, that without some kind of objective manner of adjudication between degrees of similarity, Giere's system falls into either relativism or instrumentalism, the former case being an account in which degrees of similarity vary and are evaluated relative to the intention of individual scientists, the latter case being that all we are here doing is affirming that the model is adequately successful based on the intentional performance criteria set by the agent -- in a sense saving the phenomena, which is exactly what Giere does not consider to be a realist stance from his own definition as given above (Chakravartty, 2001: 335). The degree of similarity is either relative to the intention of the agent (and would thus not be completely independent of theoretical hypotheses) or the degree of similarity is being valued for the representational role desired by the agent, meaning that what becomes important when testing the hypothesis is that the resulting data is explanatorily successful within the intentional scope of the agent.

The problem with Giere's claim is that the measurement of similarity between a model in relevant respect to a class of targeted phenomena as a degree of "highs" and

"lows" cannot be resolved by the inclusion of agent intention as Giere has argued. Indeed, the inclusion of agent intention as a way of attempting to hone degrees of similarity might actually make the case worse off in concern to scientific realism. The agent is the one who constructs the hypothesis claiming that M is similar to X to such-and-such a degree. Imagine a scientist who is trying to represent a game of pool. That scientist must construct a hypothesis which specifies his/her intention to represent the game of pool to

such-and-such a degree of similarity: that such-and-such models represent the physics of the game of pool to such-and-such a degree of intended similarity. However, what models would best map a game of pool, Newtonian or Einstein's relativity? Both

Newtonian mechanic's and Einstein's mechanics can account for ballistic-particle phenomena, so the respects of either group of models is consistent with the target phenomena. How does one measure which group of models has the highest degree of similarity in Giere's system? The answer is that there cannot be a way to tell which theory structure is best suited to represent a game of pool in Giere's system, because agent intention doesn't actually resolve the problem of which group of models is really most similar to the target real system. The degree of similarity is actually relative to the agent's intention. In order to be a scientific realist, Giere needs to either give us a satisfactory

(non-linguistic framework) account of the manner in which one adjudicates degrees of similarity between models and the real world, or Giere needs to invoke some kind of linguistic framework that explicitly spells out the valuation rules that compel one to select model M1 over model M2 when attempting to represent some phenomena X.

Chakravartty's dubiety about the plausible tenability of Giere's notion of similarity is a reasonable challenge lobbied against Giere. The rigor and diligence of the logical positivists in their attempt to construct correspondence rules linking observational terms to theoretical terms ultimately fell apart partially due to the very rigor and diligence that the positivist program demanded. Giere, who is well aware of the shortcomings of the positivist program, perhaps tries to remove his system too far from some kind of meaningful syntactical valuation. Giere is more than justified in rejecting the positivists'

syntactic-semantic structure; however, the alternative MTC program which Giere has proposed is far too loose, and as a consequence slips into new pitfalls of his own digging.

An interesting note to make before I close this section comes from Stathis Psillos

(2003) who, for his own reasons, translates Giere's idea of similarity into approximate truth. Psillos does not actually give an argument for this, and prima facie I am inclined to disagree with Psillos on the basis of Giere's rejection of approximate truth as well as

Giere's insistence that theoretical hypotheses play a more restricted role in his system.

However, if Giere were to introduce a form of approximate truth as a means of adjudicating similarity, then he may perhaps be able to dig himself out of the pit he put himself in. Anjan Chakravartty's treatment of approximate truth in his book A

Metaphysics For Scientific Realism presents a form of approximate truth where he develops a notion of approximate truth as being realized "...by means of different representational relationships, involving true descriptions of concrete structures in some cases, and little more than successful reference in others" (Chakravartty, 2007: 234).45

Though the point is at best speculative for the moment, Giere could perhaps implement the notion of similarity within different ranges of descriptions from successful reference to true descriptions of phenomena. This would allow Giere to utilize his similarity relation as a kind of guiding principle from which he might go on to add more rigorous and realistic criteria. If Giere could indeed restructure his notion of similarity to involve true descriptions as well as successful reference, then the problem of selecting between

45 To qualify, when Chakravartty is here speaking of "successful reference," what he is speaking about is predictive success, abstract reference (it is true that there are entities that behave as do quarks), etc. Chakravartty's claim is that there are "...different sorts of truth... within different sorts of scientific representation" (2007: 231), which does not limit scientific representation to one notion such as similarity.

competing models could perhaps be assuaged (though perhaps not entirely fixed). One might say that one group of models successfully refers to more phenomena and/or truly describes certain concrete phenomena within the targeted domain than do competing models.

Although Giere's account of similarity is ultimately inadequate as a scientific realist description of the relationship of representation between models and the real world

-- and is also prone to a strong relativist interpretation as Chakravartty has suggested -- it is a problem that Giere could at least potentially overcome (by introducing some kind of linguistic valuation directly linking to the concrete world). However, we have one aspect of Giere's MTC approach that still need touched on: his perspectivism. In the next section, I will attempt to show that Giere's perspectivism is, as Chakravartty would call it, a "philosophically controversial" kind of perspectivism of which lends itself toward relativism.

SECTION 3.3

Chakravartty's second criticism of Giere's MTC approach comes from

Chakravartty's (2010) work "Perspectivism, Inconsistent Models, and Contrastive

Explanation." In this paper, Chakravartty distinguishes between what he calls

"philosophically controversial perspectivism" and "philosophically non-controversial perspectivism." The former is characterized by Chakravartty as being restricted to the claim that perspectival facts are "all that can be known" (Chakravartty, 2010: 406). This is to say that philosophically controversial perspectivism claims either that there are no

non-perspectival facts in the world, or that non-perspectival facts are simply beyond our grasp in any way, shape, or form. 46 Either case of controversial perspectivism ('CP' henceforth), Chakravartty argues, debases into a form of anti-realism or relativism. The former case constructs the world as conditioned and determined in-itself by perspectival facts, while the latter restricts knowledge claims to the conditions of encapsulated perspectives while denying our ability to escape the encapsulated perspectives and achieve objective knowledge about the actual world. Both cases of CP deny the idea that there can be any objective truth about the world.

There is, however, according to Chakravartty, a non-controversial version of perspectivism ('NP' henceforth) which utilizes the idea of isomorphically extensional perspectival truths to obtain non-perspectival, i.e. objective, truth values. We will expand upon the third version later in this section; however, presently I want to motivate the claim that Giere's perspectivism is a kind of CP.

Giere contends that "...truth claims are always relative to a perspective" (Giere,

2006: 81). Further, in regard to multiple perspectives, Giere adds the following: "The knowledge that we get comes from one perspective or another, not from no perspective at all" (ibid: 92). Recall that in Giere's version of MTC theory structures provide distinct and separate perspectives of which are incapable of being adjudicated against one another. Further, all claims made by theoretical hypotheses have their truth valuations considered solely in respect to agent intention and to the perspective from which the theoretical hypotheses are invoking. For example, let's say that we have two different

46 'Facts' here as Chakravartty is using the word, denotes any true proposition (Chakravartty, 2010: 407).

theory structures T1 and T2. Now, each of these theory structures consists of a set of models; we can shorthand the set of models for T1 as M1 and the set of models for T2 as

M2. As Giere (1988) tells us, a theoretical hypothesis asserts redundantly true valuations as specified by the models. This is to say that for some model mi that belongs to either M1 or M2, mi will have innate restrictions on what could possibly be true or false within the model. Further, any set of claims which do not map onto relations between or among models and real systems are neither true nor false in respect to their mapping relation; they are nonsense from within the given context.

Given the above information, it is not hard to see how Giere has set up a version of CP. Remember that CP claimed that there were either no non-perspectival facts or that science does not have access to non-perspectival facts. Now, the important point to remember is that we are here examining Giere's scientific realism, not his external world realism in general. Recall from the first chapter that Giere explicitly denies that science is a search for objective truth, that indeed the scientific enterprise cannot and should not even entertain the idea that there is an objective truth to be found but that all scientific knowledge is derived from within a scientific, model-theoretic, perspective. Since it is the case that Giere contends that there cannot be any form of objective truth in science, and since it is the case that knowledge is instead delimited to encapsulated model-theoretic perspectives -- again, recall the fact that perspectives have their own unique truth valuations and that they cannot be adjudicated with one another -- it follows that Giere's

MTC theory is philosophically controversial; for, regardless of whether or not Giere does

believe that there is a world of objective facts independent of scientific scrutiny, scientific knowledge, in Giere's theory, is bound to encapsulated perspectives.

What Giere has then is a system that is delimited to perspectival knowledge in the sense that any and all claims of knowledge coming from scientific contexts can only come from one perspective or another. There are, then, no non-perspectival kinds of truth in Giere's system. After all, recall that Giere wants to do away with the idea that truth claims are relevant in scientific contexts and instead replace it with his notion of similarity (which, as we saw in Section 3.2, ended up being a rather untenable approach as formulated). Further, Giere's contention that scientists intend to represent a target phenomenon by means of a selected perspectivism, coupled with the idea that truth claims are only warranted relative to whatever perspective they are being formulated within, and that science represent the target phenomena from within the partial scope of the relevant perspective means that there is no scientific knowledge that is not perspectival.

The partiality of scope of a theory structure, i.e. the intentional target of which a theory structure is being used to represent, sets limits on what can and cannot be known, and Giere's claims that truth valuations are always and necessarily linked with a given perspective further sets limits on what can possibly be known in science. There is no scientific knowledge beyond a scientific perspective for Giere, thus making Giere an adherent of the kind of CP as outlined above.

Giere's stance easily slips toward relativism, as perspectives are incomparable, truth relative, scope-dependent, and unassertive of any possible non-perspectival

knowledge. However, even though Giere's perspectivism does orient his position toward relativism, there is still the possibility of saving Giere's MTC from being a full-blown relativist approach, and that possibility actually comes in the form of what Chakravartty calls a "non-philosophically controversial version" of perspectivism.

Chakravartty (2010) attempts to motivate a kind of perspectivism that allows for cross-perspectival fact evaluation by means of the modal dispositions of scientific properties. Chakravartty claims that in the case where non-perspectival facts underlie perspectival facts, perspectivism is uncontroversial, i.e. it does not lend itself toward relativism (Chakravartty, 2010: 406). Chakravartty gives the example of he and another observer who are oriented to observe a man named Peter from within separate spatial perspectives. This is what Chakravartty has to say:

...there are non-perspectival facts of the matter about the

dimensions of Peter in our inertial reference frame that, in

conjunction with facts about optics and my visual sensory

apparatus, underwrite the differences in the appearance of

his size. There is a height that he is, and then many ways he

may appear to be from different perspectives.

(Chakravartty, 2010: 406).

Chakravartty's claim is that, in addition to the perspectival knowledge that Peter seems short to one observer, there is also the non-perspectival knowledge of how tall

Peter actually is. Now, by removing encapsulation from perspectives and considering a kind of isomorphism, one can adjudicate, according to Chakravartty, between

perspectives. Chakravartty states that "[a] non-perspectival fact about a target system is thus a proposition that is true, independently of any particular perspective one may take with respect to it; it is true across perspectives" (Chakravartty, 2010: 407). There is then a division of the perspectival world, which has any propositions about Peter as dependent upon the relevant perspective, and a non-perspectival world that can be given to us by the combined facts found within the sciences. According to Chakravartty, the agents and instruments of science have limited/partial scopes due to their innate dispositions, however, even though these agents and instruments have only a partial scope from which they can intend to represent some phenomenon, like Peter's height, this fact does not preclude the fact that there is, indeed, a definite way in which the target phenomenon actually is. Further, as Chakravartty goes on to say, science reveals these dispositional facts about the target phenomenon (Chakravartty, 2010: 409). These dispositional facts have, according to Chakravartty, the same truth value across perspectives. This is to say that if some thing x is fragile then it has certain dispositional factors of which make it fragile from whatever perspective that is being used. It is this kind of cross-perspective agreement that Chakravartty wants to see from Giere in order for him to label Giere as a

(moderate) realist.

SECTION 3.4

In Sections 3.1 and 3.2, we saw relativistic tendencies within Giere's notion of the similarity relationship he posits to hold between models and the real world as well as his version of perspectivism which has left him floating in waters too close to the Charybdis

of relativism. However, I have briefly suggested some variations -- inspired by Anjan

Chakravartty -- to both Giere's notion of similarity as well as his notion of perspectivism of which might be able to save Giere from relativism and bring him into the household of the scientific realists where he wants to be. Let me then summarize what we have gone through so far.

Giere's notion of similarity was an attempt to alleviate the importance of truth valuation in concern to the relationship between model representation and real systems.

However, we found that Giere's notion of similarity is far too vague and, as a response to the vagueness of his similarity relation, Giere imported the notion of agent intention as a means of clarifying degrees of similarity. The problem, of course, with Giere's revision is that it leads toward relativism. Since truth is evaluated solely within the context of the intention of the scientist and the perspective the scientist is choosing to work from, what ends up being true in scientific discourse is relative to the perspective of the agent's intention.

The suggested revision of which I proposed was to adopt a notion of approximate truth instead of utilizing similarity as well as adopt a version of NP, i.e. philosophically non-controversial perspectivism . Instead of adopting agent intention, and thus making truth values relative in the manner mentioned above, one might instead adopt a notion of approximate truth that is accepted across perspectives. A non-perspectival truth is then a proposition that is true regardless of which relevant perspective is adopted. For instance, one might take several perspectives regarding a particular phenomenon. The collected data in concern to that phenomenon would serve as a kind of observable fact (at least

until more data or contradictory data turns up). The several perspectives representing the phenomenon could then perhaps be judged by some kind of representational role such as extensional isomorphism.

As an example, if each of the above mentioned perspectives adequately and equally represents the target phenomenon by means of extensional isomorphism, then one might say that those perspectives are all equally approximately true about the phenomenon in terms of extensional reference. If one of the theories fails to be extensionally isomorphic with the phenomenon or has a smaller range of extension than do the other models, then we might say that such a model is less approximately true in terms of extensional isomorphism. Further, extensional isomorphism need not be the only means of representation in science. Indeed, scientific theories might represent in a variety of ways with different successes. For instance, Newtonian mechanics might be approximately true in terms of predictive representation of low speed ballistic-particle phenomena, while it would be less approximately true in representing near light-speed ballistic-particle phenomena.

What does this all mean for Giere's version of MTC? Is it doomed to relativism, or can it be revised and brought back to the table of the scientific realists? Whether or not the suggestions I have given are adequate measures to save Giere from relativism, the fact remains that Giere has two very important issues he needs to address before he can legitimately claim scientific realism: (1) the vagueness of the similarity relation; and (2) the relativism of his perspectivism. Abandoning, or at least revising, the role that similarity plays in relation to models and real systems is of utmost importance, for it is

from the problem of Giere's similarity relation that the charge of relativism begins to take form.

Indeed, Giere might be able to claim that he is an external world realist, and I would not look to contest Giere on that point, however, Giere is claiming that he is a scientific realist, meaning that he must make some kind of commitment to science being a non-relativistic means of accurately representing the world. Unfortunately, due to Giere's insistence on a vague notion of similarity as well as his CP stance on perspectivism,

Giere ends up falling firmly into the relativist camp.

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