The question “what is an interpretation?” is often intertwined with the perhaps even harder question “what is a scientific theory?”. Given this proximity, we try to clarify the first question to acquire some ground for the latter. The quarrel between the syntactic and semantic conceptions of scientific theories occupied a large part of the scenario of the philosophy of science in the 20th century. For many authors, one of the two currents needed to be victorious. We endorse that such debate, (...) at least in the terms commonly expressed, can be misleading. We argue that the traditional notion of “interpretation” within the syntax/semantic debate is not the same as that of the debate concerning the interpretation of quantum mechanics. As much as the term is the same, the term “interpretation” as employed in quantum mechanics has its meaning beyond (pure) logic. Our main focus here lies on the formal aspects of the solutions to the measurement problem. There are many versions of quantum theory, many of them incompatible with each other. In order to encompass a wider variety of approaches to quantum theory, we propose a different one with an emphasis on pure formalism. This perspective has the intent of elucidating the role of each so-called “interpretation” of quantum mechanics, as well as the precise origin of the need to interpret it. (shrink)

ABSTRACT Is there something specific about modelling that distinguishes it from many other theoretical endeavours? We consider Michael Weisberg’s thesis that modelling is a form of indirect representation through a close examination of the historical roots of the Lotka–Volterra model. While Weisberg discusses only Volterra’s work, we also study Lotka’s very different design of the Lotka–Volterra model. We will argue that while there are elements of indirect representation in both Volterra’s and Lotka’s modelling approaches, they are largely due to two (...) other features of contemporary model construction processes that Weisberg does not explicitly consider: the methods-drivenness and outcome-orientedness of modelling. 1Introduction 2Modelling as Indirect Representation 3The Design of the Lotka–Volterra Model by Volterra 3.1Volterra’s method of hypothesis 3.2The construction of the Lotka–Volterra model by Volterra 4The Design of the Lotka–Volterra Model by Lotka 4.1Physical biology according to Lotka 4.2Lotka’s systems approach and the Lotka–Volterra model 5Philosophical Discussion: Strategies and Tools of Modelling 5.1Volterra’s path from the method of isolation to the method of hypothesis 5.2The template-based approach of Lotka 5.3Modelling: methods-driven and outcome-oriented 6Conclusion. (shrink)

This book defends a two-tiered account of epistemic representation--the sort of representation relation that holds between representations such as maps and scientific models and their targets. It defends a interpretational account of epistemic representation and a structural similarity account of overall faithful epistemic representation.

Recent philosophy of science has witnessed a shift in focus, in that significantly more consideration is given to how scientists employ models. Attending to the role of models in scientific practice leads to new questions about the representational roles of models, the purpose of idealizations, why multiple models are used for the same phenomenon, and many more besides. In this paper, I suggest that these themes resonate with central topics in feminist epistemology, in particular prominent versions of feminist empiricism, and (...) that model-based science and feminist epistemology each has crucial resources to offer the other's project. (shrink)

Most philosophical accounts of scientific models assume that models represent some aspect, or some theory, of reality. They also assume that interpretation plays only a supporting role. This paper challenges both assumptions. It proposes that models can be used in science to interpret reality. (a) I distinguish these interpretative models from representational ones. They find new meanings in a target system’s behaviour, rather than fit its parts together. They are built through idealisation, abstraction and recontextualisation. (b) To show how interpretative (...) models work, I offer a case study on the scientific controversy over foetal pain. It highlights how pain scientists use conflicting models to interpret the human foetus and its behaviour, and thereby to support opposing claims about whether the foetus can feel pain. (c) I raise a sceptical worry and a methodological challenge for interpretative models. To address the latter, I use my case study to compare how interpretative and representational models ought to be evaluated. (shrink)

The incompatibility within the context of modeling cannot be established simpliciter. The fact that modeling is understood as an activity whose representational power can only be partially established, may minimize the supposed existence of incompatible models. Indeed, it is argued from perspectivism that incompatibility can be dissolved, meaning that it becomes trivial or simply false due to the inherently pragmatic and partial nature of the act of representation and modeling. From this perspective, incompatibility can only be a consequence of a (...) misunderstanding of the very nature of modeling and representation In this sense, in order to tackle this strategy at its root from perspectivism, we will first need to outline the maximal perspectivism thesis, attempting to identify the possible escape routes that perspectivism could find in order to explain incompatibility as an illusory incompatibility. Then, we will analyze Valence Bond Model and Molecular Model of covalent bonds, and we will conclude that the dissuasive strategies used to minimize and/or disregard incompatibility prove to be fruitless. (shrink)

During the second half of the nineteenth century, electronegativity has been one of the most relevant chemical concepts to explain the relationships between chemical substances and their possible reactions. Specifically, EN is a property of the substances that allows them to attract external electrons in bonding situations. The problem arises because EN cannot be measured directly. Indeed, the only way to measure it is through different properties that do can be directly measured, for instance enthalpy, ionization energies or electron affinities. (...) What is particularly troubling about this case in quantum chemistry is that the different models used to describe and quantify EN are incompatible but, in a certain sense, equivalent because the same EN scale results in all of them. By analyzing Linus Pauling’s and Robert Mulliken’s models of EN, it will be argued that, if we remain cling to a traditional representative conception of models, we cannot understand the meaning of the information provided by those models. Indeed, if we do not want to adopt an instrumentalist point of view concerning chemical knowledge, we should reconsider by virtue of what a model represents the system, or, in other words, which the factors that determine the representative power of a model are. I will propose a new perspective that incorporates the role of experimental techniques in the very notion of representation; this perspective allows us to understand how supposedly incompatible models of the same target system can be both simultaneously representative. (shrink)

Syntactic approaches in the philosophy of science, which are based on formalizations in predicate logic, are often considered in principle inferior to semantic approaches, which are based on formalizations with the help of structures. To compare the two kinds of approach, I identify some ambiguities in common semantic accounts and explicate the concept of a structure in a way that avoids hidden references to a specific vocabulary. From there, I argue that contrary to common opinion (i) unintended models do not (...) pose a significant problem for syntactic approaches to scientific theories, (ii) syntactic approaches can be at least as language-independent as semantic ones, and (iii) in syntactic approaches, scientific theories can be as well connected to the world as in semantic ones. Based on these results, I argue that syntactic and semantic approaches fare equally well when it comes to (iv) ease of application, (v) accommodating the use of models in the sciences, and (vi) capturing the theory-observation relation. (shrink)

Przedmiotem artykułu jest ukazanie realizmu strukturalnego jako stanowiska realistycznego w dyskusji, prowadzonej wokół realizmu naukowego – jego wybranych zalet i słabości. Realizm strukturalny jest odpowiedzią na wyzwanie, jakie realizmowi naukowemu stawiają historyczne fakty zmiany teorii w nauce. Nawiązuje on do semantycznego ujęcia teorii naukowych i wypracowanego w tym podejściu aparatu pojęciowego. Zgodnie z realizmem strukturalnym to, co zostaje zachowane z dojrzałych teorii naukowych po zmianie teorii, to ich sformułowania matematyczne, będące abstrakcyjnymi modelami teorii. Są one aproksymacyjnie prawdziwe, gdyż reprezentują realne (...) struktury rzeczywistości w sposób wolny od ontologicznej interpretacji, narzuconej przez język teorii. Realizm strukturalny i nawiązujący do niego semirealizm, który rozszerza niezmienniczość dojrzałych teorii na własności detekcyjne obiektów fizycznych, bronią tezy realizmu naukowego w kwestii aproksymacyjnej prawdziwości teorii naukowych, interpretując realistycznie zmiany teorii naukowych. Pozostawiają jednak na boku istotny dla realizmu problem reprezentowania rzeczywistości w teoriach naukowych. Oba wspomniane stanowiska, nawiązując do modelowego ujęcia teorii naukowych, przyjmują, że reprezentacja jest izomorfizmem struktur matematycznego modelu teorii i rzeczywistości. Takie rozumienie reprezentacji jest zbyt wąskie, nie uwzględnia, że struktura zjawisk nie jest jednoznacznie określona. Strukturę tę dla teorii zastępuje matematyczny model danych, który odzwierciedla zjawiska przedstawione jako związki własności określonych przez teorię. Realistyczna interpretacja modelu danych stanowi dla realizmu strukturalnego konieczne uzupełnienie, aby spełniał on naczelną tezę realizmu, głoszącą, że nauka poznaje świat taki, jaki jest niezależnie od teorii. Stanowi to podstawę, aby broniona w realizmie strukturalnym aproksymacyjna prawdziwość teorii naukowych miała ugruntowane uzasadnienie. Wskazanie potrzeby rozszerzenia realizmu strukturalnego i semirealizmu o odpowiednią dla nich koncepcję reprezentacji jest tezą tej pracy. W artykule zostały przedstawione podstawowe elementy współczesnej dyskusji wokół realizmu naukowego oraz stanowiska realizmu strukturalnego i semirealizmu jako uzgodnienie realizmu naukowego z faktem radykalnej zmiany teorii. Następnie zostały ukazane konsekwencje, jakie dla realizmu strukturalnego wynikają z semantycznego (modelowego) ujęcia teorii naukowych i związanego z tym pojęcia reprezentacji jako izomorfizmu struktur. Ostatni fragment został poświęcony wskazaniu, że aby spełnić postulaty realizmu naukowego zarówno realizm strukturalny, jak i semirealizm powinny być uzupełnione o interpretację reprezentacji rzeczywistości w modelu danych w duchu realizmu naukowego. -------------- Zgłoszono: 17/09/2020. Zrecenzowano: 12/10/2020. Zaakceptowano do publikacji: 09/11/2020. (shrink)

The thesis is a philosophical analysis of the consumption based capital asset pricing model, investigating in particular its epistemological and methodological foundations. Financial markets are integral parts of advanced and developing economies. They matter because they channel unspent household income into banks’ savings accounts and assets such as bonds and stocks. Financial economists have traditionally taken interest in the pricing mechanism that underlies this capital allocation. The consumption based capital asset pricing model is a prominent effort to describe, explain and (...) predict such prices. It tells a story of investors’ trade-off between consumption now and later and which portfolio of assets to hold. The CCAPM based narrative intuitively makes sense, and the chosen methodology involving theoretical assumption, mathematical models and empirical tests follows the professions’ standards of good scientific practise. But does CCAPM’s research programme provide knowledge for use? My thesis seeks to answer this question in a novel way. Instead of embarking on yet another asset pricing research project, I let Philosophy of Science inform my analysis. Following a “primer” introducing essential CCAPM topics and notations, I discuss, in turn, its theoretical foundation, mathematical model, and empirical test results from a philosophy of science perspective. I find that a few fundamental principles and several auxiliary assumptions combine to develop a simplified, partial and idealized theory of investors, financial markets and assets. The model reflects and represents this theory but also makes narrow claims that are distances away from the real situations they target. Unsurprisingly, ideal model assertions fail standard statistical tests of significance. I conclude that mathematical deductive modelling rooted in orthodox, a priori based fundamental principles create ideal and fictional settings that limit their scope and portability. The development of even more granular models within this orthodox paradigm that searches for “event regularities” will not render the desired knowledge for use. The real situations are possibly too complex to be captured in simplified assumptions, ideal theories and mathematical structures. Novel methodological and ontological approaches to asset pricing are in demand. Hence, claims about tendencies in the real data might replace the current focus on point-forecasts. (shrink)

Philosophers of science have often favoured reductive approaches to how-possibly explanation. This article identifies three alternative conceptions making how-possibly explanation an interesting phenomenon in its own right. The first variety approaches “how possibly X?” by showing that X is not epistemically impossible. This can sometimes be achieved by removing misunderstandings concerning the implications of one’s current belief system but involves characteristically a modification of this belief system so that acceptance of X does not result in contradiction. The second variety offers (...) a potential how-explanation of X. It is usually followed by a range of further potential how-explanations of the same phenomenon. In recent literature the factual claims implied by the second variety have been downplayed whereas the heuristic role of mapping the space of conceptual possibilities has been emphasized. I will focus especially on this truth-bracketing sense of potentiality when looking closer at the second variety in the paper. The third variety has attracted less interest. It presents a partial how-explanation of X. Typically it aims to establish the existence of a mechanism by which X could be and was generated. The third conception stands out as the natural alternative for the advocate of ontic how-possibly explanations. This article transfers Salmon’s view that explanation-concepts can be broadly divided into epistemic, modal, and ontic to the context of how-possibly explanations. Moreover, it is argued that each of the three above-mentioned varieties of how-possibly explanation occurs in science. To recognize this may be especially relevant for philosophers. We are often misled by the promises of various why-explanation accounts, and seem to have forgotten nearly everything about the diversity of how-possibly explanations. (shrink)

Today most philosophers of science believe that models play a central role in science and that one of the main functions of scientific models is to represent systems in the world. Despite much talk of models and representation, however, it is not yet clear what representation in this context amounts to nor what conditions a certain model needs to meet in order to be a representation of a certain system. In this thesis, I address these two questions. First, I will (...) distinguish three senses in which something, a vehicle, can be said to be a representation of something else, a target—which I will call respectively denotation, epistemic representation, and faithful epistemic representation—and I will argue that the last two senses are the most important in this context. I will then outline a general account of what makes a vehicle an epistemic representation of a certain target for a certain user—which, according to the account I defend, is the fact that a user adopts what I call an interpretation of the vehicle in terms of the target—and of what makes an epistemic representation of a certain target a faithful epistemic representation of it—which, according to the account I defend, is a specific sort of structural similarity between the vehicle and the target. (shrink)

Inductive reasoning aims at constructing rules and models of general applicability from a restricted set of observations. Induction is a keystone in natural sciences, and it influences diverse application fields such as engineering, medicine and economics. More generally, induction plays a major role in the way humans learn and operate in their everyday life. The level of reliability that a model achieves depends on how informative the observations are relative to the flexibility of the process by which the model is (...) constructed. When the process is articulated so that the model can incorporate descriptive details and subtleties, a large set of informative observations are required to reliably tune the model, whereas models obtained from simple procedures can be tuned with fewer observations. This article introduces the concept of “dominance”, which refers to the situation in which a reduced subset of observations suffices to reconstruct the model. A mathematical framework is presented to quantify the reliability of learning procedures as a function of the size of the subset of dominant observations. Although limited in scope, we believe that our study can contribute to the understanding of some fundamental mechanisms by which knowledge is generated from observations in inductive reasoning. (shrink)

How do models represent reality? There are two conditions that scientific models must satisfy to be representations of real systems, the aboutness condition and the epistemic condition. In this article, I critically assess the two main fictionalist theories of models as representations, the indirect fiction view and the direct fiction view, with respect to these conditions. And I develop a novel proposal, what I call ‘the new fiction view of models’. On this view, models are akin to fictional stories; they (...) represent real-world phenomena if they stand in a denotation relation with reality; and they enable knowledge of reality via the generation of theoretical hypotheses, model–world comparisons and direct attributions. (shrink)

I show that extant attempts to capture and generalize empirical adequacy in terms of partial structures fail. Indeed, the motivations for the generalizations in the partial structures approach are better met by the generalizations via approximation sets developed in “Generalizing Empirical Adequacy I”. Approximation sets also generalize partial structures.

In “The Toolbox of Science” (1995) together with Towfic Shomar we advocated a form of instrumentalism about scientific theories. We separately developed this view further in a number of subsequent works. Steven French, James Ladyman, Otavio Bueno and Newton Da Costa (FLBD) have since written at least eight papers and a book criticising our work. Here we defend ourselves. First we explain what we mean in denying that models derive from theory – and why their failure to do so should (...) be lamented. Second we defend our use of the London model of superconductivity as an example. Third we point out both advantages and weaknesses of FLBD’s techniques in comparison to traditional Anglophone versions of the semantic conception. Fourth we show that FLBD’s version of the semantic conception has not been applied to our case study. We conclude by raising doubts about FLBD’s overall project. (shrink)

The recent discussion on scientific representation has focused on models and their relationship to the real world. It has been assumed that models give us knowledge because they represent their supposed real target systems. However, here agreement among philosophers of science has tended to end as they have presented widely different views on how representation should be understood. I will argue that the traditional representational approach is too limiting as regards the epistemic value of modelling given the focus on the (...) relationship between a single model and its supposed target system, and the neglect of the actual representational means with which scientists construct models. I therefore suggest an alternative account of models as epistemic tools. This amounts to regarding them as concrete artefacts that are built by specific representational means and are constrained by their design in such a way that they facilitate the study of certain scientific questions, and learning from them by means of construction and manipulation. (shrink)

Current discussion of scientific realism and antirealism often cites Pierre Duhem’s argument for the underdetermination of theory choice by evidence. Participants draw on an account of his underdetermination thesis that is familiar, but incomplete. The purpose of this article is to complete the familiar account. I argue that a closer look at Duhem’s The aim and structure of physical theory suggests that the rationale for his underdetermination thesis comes from his philosophy of scientific language. I explore how an understanding of (...) physical laws as symbolic is meant to support the thesis. In the course of my argument, I point out that Duhemian underdetermination is not meta-practical but grounded in the practice of science, specifically in the scientist’s use of instruments and measurement techniques. Measurement has a significant limitation, according to Duhem: it always involves approximation and a degree of experimental error. Consequently, it cannot overcome the gap between the ordinary, concrete language of observation and the mathematical language of science. Moreover, Duhem argues that the use of instruments in experiment invokes whole groups of theories. I contend that, ultimately, this reliance on auxiliary assumptions—which makes possible the use of instruments—is the foundation of his thesis and that recognizing this completes the familiar account of his underdetermination argument.Author Keywords: Duhem; Suppes; Underdetermination; Measurement; Physical theory. (shrink)

This dissertation consists of three parts. Part I is a defense of an artificial language methodology in philosophy and a historical and systematic defense of the logical empiricists' application of an artificial language methodology to scientific theories. These defenses provide a justification for the presumptions of a host of criteria of empirical significance, which I analyze, compare, and develop in part II. On the basis of this analysis, in part III I use a variety of criteria to evaluate the scientific (...) status of intelligent design, and further discuss confirmation, reduction, and concept formation. (shrink)

We continue in this article the abstract algebraic treatment of quantum sentential logics Wil. The Notions borrowed from the field of Model Theory and Abstract Algebraic Logic - AAL (i.e., consequence relation, variety, logical matrix, deductive filter, reduced product, ultraproduct, ultrapower, Frege relation, Leibniz congruence, Suszko congruence, Leibniz operator) are applied to quantum logics. We also proved several equivalences between state property systems (Jauch-Piron-Aerts line of investigations) and AAL treatment of quantum logics (corollary 18 and 19). We show that there (...) exist the uniquely defined correspondence between state property system and consequence relation defined on quantum logics. We also signalize that a metalogical property - Lindenbaum property does not hold for the set of quantum logics. (shrink)

What are scientific models? Philosophers of science have been trying to answer this question during the last three decades by putting forward a number of different proposals. Some say that models are best understood as abstract Platonic objects or fictional entities akin to Sherlock Holmes, while others focus on their mathematical nature and see them as set theoretical structures. Although each account has its own strengths in offering various insights on the nature of models, several objections have been raised against (...) these views which still remain unanswered, making the debate on the ontology of models seem unresolvable. The primary aim of this paper is to show that a large part of these difficulties stems from an inappropriate reading of the main question on the ontology of models as a purely metaphysical question. Building on Carnap, it is argued that the question of the ontology of scientific models is either an internal theoretical question within an already accepted linguistic framework or an external practical question regarding the choice of the most appropriate form of language in order to describe and explain the practice of scientific modelling. The main implication of this view is that the question of the ontology of models becomes a means of probing other related questions regarding the overall practice of scientific modelling, such as questions on the capacity of models to provide knowledge and the relation of models with background theories. (shrink)

Thesemanticviewofscientifictheoriesassumesthedependenceofmodelsontheories.Someauthorschal- lenge that assumption by means of the study of certain models conceived as phenomenological. On the basis of the analysis of atomic and molecular models in quantum chemistry, in this article we will argue for an independence of models from theories, which cannot be interpreted as merely historical and context relative. Those models shows a conceptual independence that is constitutive of the modeling process; such independence cannot be conceived as a result of a contingent deficiency of the theory used, (...) deficiency that would be overcome by the future progress of science. (shrink)

In this paper we explore the hypothesis that constrained uses of imagination are crucial to economic modeling. We propose a theoretical framework to develop this thesis through a number of specific hypotheses that we test and refine through six new, representative case studies. Our ultimate goal is to develop a philosophical account that is practice oriented and informed by empirical evidence. To do this, we deploy an abductive reasoning strategy. We start from a robust set of hypotheses and leave space (...) for the generation of further hypotheses and theoretical claims based on the qualitative analysis of new empirical data. (shrink)

This paper intends to bring Austinian themes into methodological discussion about models. Using Austinian conceptual vocabulary, I argue that models perform actions in and outside of the academic field. This multiplicity of fields induces a variety of felicity conditions and types of performed actions. If for example, an inference from a model is judged according to some epistemological criteria in the scientific field, the representation of the world which the model carries will not be judged by the same criteria outside (...) the scientific field. A model can be considered as a standard in a strict scientific framework, while not being used as part of public policies, or vice versa. However, we focus on the dynamics between different fields. (shrink)

Our concern is in explaining how and why models give us useful knowledge. We argue that if we are to understand how models function in the actual scientific practice the representational approach to models proves either misleading or too minimal. We propose turning from the representational approach to the artefactual, which implies also a new unit of analysis: the activity of modelling. Modelling, we suggest, could be approached as a specific practice in which concrete artefacts, i.e., models, are constructed with (...) the help of specific representational means and used in various ways, for example, for the purposes of scientific reasoning, theory construction and design of experiments and other artefacts. Furthermore, in this activity of modelling the model construction is intertwined with the construction of new phenomena, theoretical principles and new scientific concepts. We will illustrate these claims by studying the construction of the ideal heat engine by Sadi Carnot. (shrink)

In recent years, the use of historical cases in philosophy of science has become a proper topic of reflection. In this article I will contribute to this research by means of a discussion of one very famous example of case-based philosophy of science, namely the debate on the London & London model of superconductivity between Cartwright, Suárez and Shomar on the one hand, and French, Ladyman, Bueno and Da Costa on the other. This debate has been going on for years, (...) without any satisfactory resolution. I will argue here that this is because both sides impose on the historical case a particular philosophical conception of scientific representation that does not do justice to the historical facts. Both sides assume, more specifically, that the case concerns the discovery of a representational connection between a given experimental insight – the Meissner effect – and the diamagnetic meaning of London and London’s new equations of superconductivity. I will show, however, that at the time of the Londons’ publication, neither the experimental insight nor the meaning of the new equations was established: both were open for discussion and they were stabilized only later. On the basis of this historical discussion, I will then propose an alternative approach to the case study: the case should not be seen as a site of confrontation between pre-existing philosophical accounts, but rather as a way to historically elaborate and develop philosophical concepts. I will then show how approaching the historical episode in this way suggests an alternative approach to the philosophical study of representation, according to which it involves the establishment, over time, of a stable connection between constellations of different elements that, through discussion and engagement with alternative views and approaches, come to constitute phenomenon and meaning. (shrink)

In this work I attempt a reformulation of Lewis’ Best System Account, explicitating the underlying formal conception of scientific theories and trying to define the concepts of simplicity, strength and balance. This essay is divided in three sections. In the first one I introduce the Best System Account of natural laws and formulate the need for its improvement. In the second section I outline a formal framework where the notions of deductive system and scientific theory can be defined precisely. In (...) the last section the notions of simplicity, strength and balance are analyzed. To conclude I argue that the framework proposed does indeed provide the precision required. In addition, it also offers interesting insights on the plurality of concepts of simplicity, strength and balance, and on the general enterprise of formalizing scientific theories. (shrink)