Experiencias de promoción económica rural en Bolivia

The idea of what a scientific theory is represents the background against which the role of metaphor in the context of scientific inquiry is assessed. Since different views about scientific theories have influenced scholars’ attitude towards this issue, in this section I shall review some of the most influential conceptions in order to make sense of the abundant use of meta- phors in science.

For a long time the syntactic view of scientific theories has represented the paradigm that more strongly hindered a proper appreciation of the role of metaphor in scientific reasoning and theory making. A restrictive assess- ment of the epistemic function of metaphor has resulted from philosophical commitment to certain assumptions, while the stage for its reappraisal has been set by the recognition of the weaknesses of such conception to account for a number of issues related to theory change and the real-world scientific practice (Craver 2002: 57). On the one hand, many criticisms raised by philosophers of science against the syntactic view have served to open new

perspectives on the role of metaphor in science (Hesse 1966; Boyd 1979; Hoffman 1980). On the other hand, the emergence of a cognitive approach to science – focused on the cognitive structures and processes at play in sci- entists’ activities, rather than restricted to the context of justification and guided by a particular concept of rationality, which has led to downgrade certain cognitive aspects as psychological and social factors (cf. Giere 2000) – has further encouraged investigation in this direction. Yet, before the issue of metaphor in science was directly addressed, some have questioned the role of models in scientific theorizing. Though models and metaphors are not the same sort of device, they have often been associated as instantiating similar modes of analogical reasoning.

In the syntactic view theories are construed as sets of sentences closed under logical consequence. Its major tenet states that the truth of a theory is ensured by its ability to entail the evidence. This idea is reflected in the “saving of phenomena” precept. Such view has a long-standing tradition, which could be traced back at least to the ancient astronomy. Logical empiricists, such as Carl Hempel (1942) and Paul Oppenheim (1948), have drawn on this idea and recast it in a formal framing. They construe theories as sets of logico-linguistic expressions linked together by a deductive appa- ratus. Hempel holds both explanations and predictions5 to issue from deduc- tive inferences drawn from the laws and the general hypotheses of a theory, along with some auxiliary premises related to factual circumstances. In accordance with this scheme, an explanation consists of two parts: on one side, a set of statements describing certain phenomena provide the explan-

andum; on the other side, laws and general hypotheses, along with the de-

scription of some related factual conditions, constitute the explanans. Now, if these two parts were connected by a strictly deductive relation, then models, and a fortiori metaphors, should be ascribed no constitutive func- tion within theories. Models and metaphors would turn out to be dispensable once the propositional structure of a theory had properly been rendered; they would admittedly serve an illustrative or, at most, a heuristic function, but they would have no epistemic status. Such claims rest upon a clear-cut dis- tinction between the context of discovery and the context of justification6, a

5 _{The implication of a symmetry between explanation and prediction has encountered many}

objections; see for example Scheffler 1963, Salmon 1966, Hanson 1978, Woodward 2011.

6 _{Although a sharp distinction between the contexts of discovery and the contexts of}

justification was widely agreed among neo-positivist philosophers, it is Karl Popper, in The

logic of scientific discovery (1934), the one who has most emphasized this dichotomy,

stating that the issues of invention and discovery are to be left to empirical psychology, for dealing with them “is irrelevant to the logical analysis of scientific knowledge”. For an

distinction that, on the one hand, does not accommodate the extended proc- ess of theory construction – which often results in a number of different partial theoretical accounts of specific phenomena (Craver 2002) – and, on the other hand, does not help to make sense of the wide use scientists make of models and metaphors in their practice.

One main tenet of logical empiricism, to which one might appeal to deny any cognitive value to metaphor, is the verificationist conception of meaning. It identifies the source of propositions meaning with sensory experience. Accordingly, the only true statements would be either analytic propositions or synthetic verifiable propositions. Synthetic propositions that cannot be empirically verified are deemed of no epistemic value and hence meaningless. Indeed, whereas the terms belonging to the observation lan- guage are held to be directly pegged to experience and therefore the state- ments involving them to be verifiable, theoretical terms, which require interpretation, should be reduced to the observable through a set of corre- spondence rules. As an unintended consequence, while the constitutive symbolism of a theory and the terms belonging to the observation language are taken as literal, theoretical terms cannot: they turn out to be somehow in the same condition as metaphors, as far as their reference can only indirectly (and partially) be referred to the evidence by interpretation (cf. Montuschi 2001).

Related to the empiricist view is the assumption of meaning invariance of observation language terms. This assumption has been called into ques- tion by Mary Hesse, who counters the idea with the so called Thesis M, stating that all language is primarily metaphorical and hence subject to change over time. “Metaphor is a fundamental form of language and prior (historically and logically) to the literal” (Hesse 1993: 54). Based on a fam- ily-resemblance conception of categorisation, Hesse regards language as a

overview of the debate and a critical analysis of the topic, see Hoyningen-Huene (1987). The indispensable role of analogy in the context of justification and after justification of a theory being given is defended by Itkonen (2005: 176-197) (metaphor is seen as a subtype of analogy, with additional constraints; ibid. 41). Summarizing his remarks, he states that “analogy is important at least in the following three ways. First, even assuming that there is a distinction between ‘discovery’ and ‘justification’, analogy surely plays a role in discov- ery. Second, analogy must also play a role in justification, because there is, as a matter of fact, no (clear) distinction between discovery and justification; rather, only that is discov- ered which can be justified. Third, even after a theory has been discovered and justified, analogy continues to play a role: every theory achieves a generalization, either within one domain or across (what has previously been regarded as) several domains; and it is analogy which, being synonymous with generalization, keeps all this body of knowledge together” (2005: 194).

network in which any term is related to the others, so thatthe meaning of any expression, far from being given once and for all, is affected by the transformations the network undergoes, locally or on a more extended scale, to fit our experience and our practical and theoretical goals7.

The verificationist view of meaning has also a bearing on the distinction between theoretical and observation language, which has also been criti- cised from a different angle. In the wake of Quine and Sellars’ analysis, Hesse notes that because the same terms (e.g. wave, current, collision, spin, transcription, etc.) can be used in different contexts to refer either to observ- able or to non-observable entities, the theoretical-observational distinction cannot be construed as an ultimate epistemic or logic dichotomy; it must rather be regarded as pragmatic in its nature (cf. Hesse 1966). This finally affects the distinction, maintained by the logical empiricists, between a par- tial and a complete interpretation of terms, which is also a crucial point for the debate concerning the role of models in scientific theories, and involves metaphor as well.

In response to these considerations, Hesse famously suggested to regard explanation as a metaphorical redescription of the domain of the explanan-

dum (cf. Hesse 1966). Her main point is that models and metaphors provide

the possibility to extend theories through analogical inferences. For this to be possible, the condition is that theories are open. This would not be the case if theories were strictly deductive systems, closed by their constitutive principles. If so, any interaction with other theoretical fields8 would be a merely extrinsic juxtaposition, which does not describe the real dynamics of scientific evolution. It is through the investigation of the function of models that light has been shed on certain aspects of theories that the formal fram- ing has overlooked or even obscured.

Norman Campbell (1920), who brought the issue of models to promi- nence in the philosophical debate, identified several components of a theory: the calculus, the dictionary connecting the formal system to the experimen-

7 _{For an overview of Hesse’s theory of language, see chap. V, Favrin and Storari, in this}

volume.

8 _{Typically, scientific breakthroughs are not obtained in isolation from ideas coming from}

other fields of research. Models and metaphors are often based on representations and for- malisms borrowed from other fields. As regards methodology, certain theoretical frame- works have sometimes deeply influenced the way problems have been settled in different fields, as well as the expectations as to how the adequate solutions should look like. For in- stance, all along the western history, Euclid’s axiomatic method has been regarded as a model of scientific thinking in different domains, and Darwin’s evolutionism has become the paradigm for a variety of disciplines. It goes without saying that this has not been in- variably tied with scientific success.

tal language, the experimental laws, which can be deduced from the hypothesis plus the dictionary and are susceptible of empirical tests, and the

analogy, provided by models and serving to link the theory to the physical

system it aims to describe. In this perspective, models serve two functions: first, they provide an interpretation of theories; second, offer either a simpli- fied representation of the target system or a formalism or a set of equations to be applied to it. In so doing, models enable the inquirer to link a theory to the appearances it is designed to explain. Taking into consideration the Kinetic Molecular Theory of gases, Campbell shows that Dutch physicist Van der Waals (1873), pursuing the analogy between the model and the target system as to the properties of motion and elastic collision, could introduce new assumptions and thereby extend the original theory to account for its discrepancies vis-à-vis the experimental behaviour of gases. This case, as well as others, show that models enable theories to grow. It should not be underestimated that theories, far from being static structures, are rather composite arrangements, constantly modified and extended to better explain certain regularities or events.

Scientists make use of models (scale models, diagrams, maps, systems of equations, mental representations and the like) because they are more familiar, or more manageable,9 than the investigated phenomena. Their function in the constitution of theories depends on that they give impulse and direction to scientific inquiry and guide researchers in their choice of formalisms. Moreover, since the interpretation they provide makes intuitive sense of theories, they cannot be set aside and are instead to be treated as constitutive parts of them. To illustrate this point, Thomas Kuhn and others highlight the role that the planetary model of the atom plays even once the theory has been given a mathematical formulation. When Bohr resorted to this model, depicting electrons and nucleus as tiny charged corpuscles inter- acting under the laws of mechanics and electromagnetic theory, he replaced the metaphor-based representation, but the relation between the new model and the investigated physical system remains dependent upon a “metaphor- like process” insofar as the resemblance between them is only approximate.

Furthermore, even when that process of exploring potential similarities had gone as far as it could (it has never been completed) the model remained essential to

9 _{In this context, it is worth remembering that Newton reversed this rule and applied the}

concept of inertia as unending rectilinear motion of heavenly bodies, such as the planets, to motion of terrestrial bodies, thus extending to the sublunary region some principles that were thought to be peculiar of the superlunary region. This way, he came to explain certain familiar phenomena by analogy with less familiar circumstances.

the theory. Without its aid, one cannot even today write down the Schrödinger equation for a complex atom or molecule, for it is to the model, not directly to nature, that the various terms in that equation refer.10

Unpacking all possibly fruitful implications of a model or a metaphor is a task that can engage scientists for years or generations (Hoffman 1980: 415). In many cases this sustains the extension of theories by way of making them predictive (Hesse 1966), a function that cannot be reduced to the for- mal isomorphism11 between a model and the logical structure of the theory in which it is introduced. A formal reduction does not necessarily capture the traits whereby a model applies to something in the world. By focusing on formal isomorphism, the relevant properties of a model would be selected as compared to the formal structure of the theory, rather than to the material constitution of the things it points to. Hesse refers to the kind of similarity that explains the predictive import of models and metaphors as “material analogy”. On her view, material analogy should be analysed into three factors: the positive, the negative and the neutral analogy. The positive analogy identifies the respects under which the model and what it represents are recognized as being alike. The negative analogy identifies those respects for which they are held to differ from one another. The neutral analogy con- cerns those features which status, whether positive or negative, is still unknown. It is through the neutral analogy that models set the inquirer on the track of new, explanatorily relevant aspects of a domain. The reduction of similarity to isomorphism, far from justifying the substitution of models by a fully formalized system, misses a crucial point: Because such a formal approach focuses on the positive analogy, at most it allows a synchronic reconstructions of theories, whereas a proper epistemological reassessment of models contributes to explain the dynamics of their evolution.

The shortcomings of a formalist picture of theories are even more evi- dent if we set ourselves in pursuit of a general view of the overall scientific enterprise. The strictures of the logical framing leave it ill-suited to account for a variety of scientific fields other than physics, such as life and social

10 _{Kuhn (1979: 538). Few lines below, Kuhn adds: “Though not prepared here and now to}

argue the point, I would hazard the guess that the same interactive, similarity-creating proc- ess which Black has isolated in the functioning of metaphor is vital also to the function of models in science. Models are not, however, merely pedagogic or heuristic. They have been too much neglected in recent philosophy of science”.

11

“The relevant similarity or ‘analogy’ between a model […] and the modeled type of a phenomenon consists in a nomic isomorphism, i.e. a syntactic isomorphism between two

corresponding sets of laws.” (Hempel 1965, Aspects of scientific explanation, New York,

sciences. In fact, not all the important aspects of theories in those fields can be captured by first-order predicate calculus. Moreover, genuinely excep- tionless laws of nature are hard to come by even in physics (Cartwright 1983, Giere 1999). So, without diminishing the merits of having recon- structed the logical patterns of scientific reasoning, we should take into con- sideration other attempts at clarifying what theories are. Approaches that appeal to the notion of representation and include nonformal patterns of explanation aim at coming closer to science as it is made “in the wild” (Craver 2002: 58) in order to elaborate an empirically adequate account of theory construction and change.

Different proposals have been made which go in this direction. Some of them, generally labelled semantic views (cf. Hesse 2000; Craver 2002; French 2008), are due to Suppes (1967), Van Fraassen (1980), Giere (1988), Suppe (1989). They contrast the syntactic view by stating that scientific theories are collections of models, rather than sets of sentences.

Let us consider Ronald Giere’s cognitive approach. His conception, which he calls “Constructive Realism”, ascribes to models a major role in the constitution of scientific theories. Similarity is viewed as “the basic relationship between models and the world” (Giere 2010: 269). Science is characterized as a complex of fundamentally pragmatic practices aimed at providing the best possible representations of nature. To this purpose, sci- entists use a variety of means, such as natural and formal languages, equa- tions, graphs, pictures, physical objects, computer programs, etc. Under- standing how these means intervene in the constitution of theories, which is their function, requires a shift of focus from the syntactical structure of theo- ries to their semantic counterpart, and more fundamentally from language to the activity of representing the world. “If we wish to understand these prac- tices, we should not begin with the language itself, but with the scientific practices in which the language is used.” (Giere 2004: 743).12 Defining this activity in terms of a binary relation holding between statements (i.e. lin- guistic entities) and aspects of the world leads to neglect some important factors involved in it. Instead, argues Giere, we need to characterize repre- sentation as a four-terms relation, including the agents (S), the aspects of the world being represented (W), the medium (M) used to represent them, and the purposes (P) the agents aim at. Such relation could be formulated like this: the agents S use M, meaning to represent W for purposes P (cf. Giere 2004: 744; Giere 2010: 274). This way of approaching the problem goes

12 _{In the same vein, Richard Boyd (1979) has insisted on the appropriateness of relativizing}

along with the conviction that focusing “on the activity of representing fits more comfortably with a model-based understanding of scientific theories” (Giere 2004: 743-744). Giere also describes the process by which models are introduced. The laws and principles of theories are not applied to real systems in the world directly, but via models of them. Based on general principles, serving as templates (e.g. Newton’s laws of motion), plus spe- cific conditions (e.g. Newton’s gravitational law), scientists construct mod- els (e.g. models that represent interactions between bodies in three dimen-