Theories and Models

Disagreement about how best to think of the relation between theories and the realities they represent has a longstanding and venerable history. We take up this debate in relation to the free energy principle (FEP) - a contemporary framework in computational neuroscience, theoretical biology and the philosophy of cognitive science. The FEP is very ambitious, extending from the brain sciences to the biology of self-organisation. In this context, some find apparent discrepancies between the map (the FEP) and the territory (target (...) systems) a compelling reason to defend instrumentalism about the FEP. We take this to be misguided. We identify an important fallacy made by those defending instrumentalism about the FEP. We call it the literalist fallacy: this is the fallacy of inferring the truth of instrumentalism based on the claim that the properties of FEP models do not literally map onto real-world, target systems. We conclude that scientific realism about the FEP is a live and tenable option. (shrink)

Jan G. Michel argues that we need a philosophy of scientific discovery. Before turning to the question of what such a philosophy might look like, he addresses two questions: Don’t we have a philosophy of scientific discovery yet? And do we need one at all? To answer the first question, he takes a closer look at history and finds that we have not had a systematic philosophy of scientific discovery worthy of the name for over 150 years. To answer the (...) second question, Michel puts forward three arguments that show the importance of a philosophy of scientific discovery. Briefly, he arrives at the following answers: No, we don’t yet have a philosophy of scientific discovery, and yes, we definitely need one. To remedy this shortcoming, Michel analyzes the concept of discovery, leading him to the insight that scientific discoveries have an underlying structure with certain structural features. Some of these features may be important but not indispensable to scientific discovery processes; these include eureka moments, serendipities, joint discoveries, special science funding, and others. In addition, Michel identifies three indispensable structural features which he examines in detail and which he places in a picture with a certain dynamics according to which the process of making scientific discoveries can be seen as a path, leading us from finding and acceptance to knowledge. (shrink)

Over the last fifteen years, an ambitious explanatory framework has been proposed to unify explanations across biology and cognitive science. Active inference, whose most famous tenet is the free energy principle, has inspired excitement and confusion in equal measure. Here, we lay the ground for proper critical analysis of active inference, in three ways. First, we give simplified versions of its core mathematical models. Second, we outline the historical development of active inference and its relationship to other theoretical approaches. Third, (...) we describe three different kinds of claim -- labelled mathematical, empirical and general -- routinely made by proponents of the framework, and suggest dialectical links between them. Overall, we aim to increase philosophical understanding of active inference so that it may be more readily evaluated. -/- This is a manuscript draft of the Introduction to the Topical Collection "The Free Energy Principle: From Biology to Cognition", forthcoming in Biology & Philosophy. (shrink)

During the twentieth century, the mechanistic worldview came under attack mainly because of the rise of quantum mechanics but some of its basic characteristics survived and are still evident within current science in some form or other. Many scholars have produced interesting studies of such significant mechanistic trends within current physics and biology but very few have bothered to explore the effects of this worldview on current chemistry. This paper makes a contribution to fill this gap. It presents first a (...) brief historical overview of the mechanistic worldview and then examines the present situation within chemistry by referring to current studies in the philosophy of chemistry and determining which trends are still mechanistic in spirit and which are not. (shrink)

On entend généralement par « théorie des modèles » autant la métamathématique (ou sémantique formelle) que la sémantique des modèles des sciences non formelles. Cet article a pour objet la théorie des modèles scientifiques que Mario Bunge a développée dans Method, Models and Matter (1973). J’y analyse l’intégration théorique qu’opère Bunge des sciences formelles et des sciences expérimentales ou observationnelles, laquelle prend appui sur sa philosophie des sciences. Je la compare sommairement à la théorie des modèles de Gilles-Gaston Granger dans (...) le but évident d’en dégager les ressemblances et les dissimilitudes, mais aussi leur commun point d’achoppement : l’une comme l’autre usent en effet d’un concept non analysé dont la fonction épistémologique est pourtant capitale et produit les mêmes effets. Au centre de la théorie des modèles de Bunge se trouve le concept de simulation que je comparerai à celui qui est en usage dans les sciences de l’ordinateur et qui est de nos jours largement appliqué à diverses sciences, tant sociales que naturelles. Je conclurai sur les conséquences méthodologiques et métaphysiques de la théorie bungéenne des modèles. (shrink)

This paper contains a detailed exposition and analysis of The Philosophy of “As If“ proposed by Hans Vaihinger in his book published in 1911. However, the principal chapters of the book (Part I) reproduce Vaihinger’s Habilitationsschrift, which was written during the autumn and winter of 1876. Part I is extended by Part II based on texts written during 1877–1878, when Vaihinger began preparing the book. The project was interrupted, resuming only in the 1900s. My conclusion is based exclusively on the (...) texts written in 1876-1878: Vaihinger was, decades ahead of the time, a philosopher of modeling in the modern sense – a brilliant achievement for the 1870s! And, in the demystification of such principal aspects of cognition as truth, understanding and causality, is he not still ahead of many of us? According to Vaihinger, what we set beyond sensations is our invention (fiction), the correspondence of which with reality cannot (and need not) be verified in the mystical, absolute sense many people expect. (shrink)

Idealization is a necessity. Stripping away levels of complexity makes questions tractable, focuses our attention, and lets us develop comprehensible, testable models. Applying such models, however, requires care and attention to how the idealizations incorporated into their development affect their predictions. In epistemology, we tend to focus on idealizations concerning individual agents' capacities, such as memory, mathematical ability, and so on, when addressing this concern. By contrast, this dissertation focuses on social idealizations, particularly those pertaining to salient social categories like (...) race, sex, and gender. In Chapter II, Privilege and Superiority, we begin with standpoint epistemology, one of the earliest efforts to grapple with the ways that social structures affect our epistemic lives. I argue that, if we interpret standpoint epistemologists' claims as hypotheses about the ways that our social positions affect access to evidence, we can fruitfully employ recent developments in evidence logic to study the consequences. I lay the groundwork for this project, developing a model based on neighborhood semantics for modal logic. Adapting this framework to standpoint epistemology helps to clarify the meaning of terms like "epistemic privilege" and "superior knowledge" and to elucidate the differences between various accounts of standpoint epistemology. I also address a longstanding criticism of these views: Longino's bias paradox, which suggests that there is no objective position from which to judge the goodness of a particular standpoint. Chapter III, Evidence in a Non-Ideal World, turns to the broader social context, looking at how ideology affects the availability of evidence. Throughout the chapter, I take the formation, justification, and maintenance of racist, sexist, and otherwise oppressive beliefs as a central case. I argue that these beliefs are, at least sometimes, formed as a result of evidential distortion, a structural feature of our epistemic contexts that skews readily available evidence in favor of dominant ideologies. Because they are formed this way, such beliefs will appear justified on prominent accounts of justification, both internalist and externalist. As a result, epistemic norms that fail to account for such non-ideal conditions will deliver verdicts that are not only counter-intuitive, but also morally unpalatable. This, I argue, reveals a kind of structural epistemic injustice, especially where oppressive ideology is involved and suggests the need for epistemic norms that are sensitive to agents' social contexts. Much of the discussion in Chapters II and III depends on social categories like race and gender, arguing that they have a distinctive influence on our epistemic lives. In Chapter IV, I Know You Are, But What Am I?, my co-author and I focus on social categories themselves, distinguishing between self-identity, social identity, and social role. We self-identify as gay or straight, men or women, couch-potatoes or gym rats. Sometimes, these identities affect our social roles---the way we are perceived and treated by others---and sometimes they do not. This relationship between our internal identities and our preferred public perceptions begs for explanation. On our account, this relationship is captured by what we refer to as 'social identity'---roughly, internal identities made available to others. We argue that this account of social identity plays an illuminating role in structural explanation of discrimination and individual behavior, dissolves puzzles surrounding the phenomenon of 'passing', and explains certain moral and political obligations toward individuals. (shrink)

Non-epistemic values pervade climate modelling, as is now well documented and widely discussed in the philosophy of climate science. Recently, Parker and Winsberg have drawn attention to what can be termed “epistemic inequality”: this is the risk that climate models might more accurately represent the future climates of the geographical regions prioritised by the values of the modellers. In this paper, we promote value management as a way of overcoming epistemic inequality. We argue that value management can be seriously considered (...) as soon as the value-free ideal and inductive risk arguments commonly used to frame the discussions of value influence in climate science are replaced by alternative social accounts of objectivity. We consider objectivity in Longino's sense as well as strong objectivity in Harding's sense to be relevant options here, because they offer concrete proposals that can guide scientific practice in evaluating and designing so-called multi-model ensembles and, in fine, improve their capacity to quantify and express uncertainty in climate projections. (shrink)

Physical theories are complex and necessary tools for gaining new knowledge about their areas of application. A distinction is made between abstract and practical theories. The last are constantly being improved in the cognitive activity of professional physicists and studied by future physicists. A variant of the philosophy of physics based on a modified structural-nominative reconstruction of practical theories is proposed. Readers should decide whether this option is useful for their understanding of the philosophy of physics, as well as other (...) philosophies of particular sciences. (shrink)

The structure of communication networks can be more or less “democratic”: networks are less democratic if (a) communication is more limited in terms of characteristic degree and (b) is more tightly channeled to a few specifc nodes. Together those measures give us a two-dimensional landscape of more and less democratic networks. We track opinion volatility across that landscape: the extent to which random changes in a small percentage of binary opinions at network nodes result in wide changes across the network (...) as a whole. If wide and frequent swings of popular opinion are taken as a mark of instability, democratic communication networks prove far more stable than anti-democratic ones. In a fnal section, we consider the democratic or anti-democratic character of networks that respond to volatility by rewiring at random, in a search for community, or in a search for a leader. (shrink)

Polarization is a topic of intense interest among social scientists, but there is significant disagreement regarding the character of the phenomenon and little understanding of underlying mechanics. A first problem, we argue, is that polarization appears in the literature as not one concept but many. In the first part of the article, we distinguish nine phenomena that may be considered polarization, with suggestions of appropriate measures for each. In the second part of the article, we apply this analysis to evaluate (...) the types of polarization generated by the three major families of computational models proposing specific mechanisms of opinion polarization. (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)

Book review of Paul Feyerabend's "Philosophy of Nature". || Reseña del libro "Philosophy of Nature", escrito por Paul Feyerabend.

Many want to know what bitcoin is and how it works. But bitcoin is as complex as it is controversial, and relatively few have the technical background to understand it. In this paper, I offer an accessible on-ramp for understanding bitcoin in the form of a model. My model reveals both what bitcoin is and how it works. More specifically, it reveals that bitcoin is a fictional substance in a massively coauthored story on a network that automates and distributes jobs (...) normally entrusted to centralized publishing institutions. My model therefore falsifies a popular view according to which each bitcoin is a chunk of code. (shrink)

Complex constraints like conditionals ('If A, then B') and probabilistic constraints ('The probability that A is p') pose problems for Bayesian theories of learning. Since these propositions do not express constraints on outcomes, agents cannot simply conditionalize on the new information. Furthermore, a natural extension of conditionalization, relative information minimization, leads to many counterintuitive predictions, evidenced by the sundowners problem and the Judy Benjamin problem. Building on the notion of a `paradigm shift' and empirical research in psychology and economics, I (...) argue that the model of hypothesis testing can explain how people learn complex, theory-laden propositions like conditionals and probability constraints. Theories are formalized as probability distributions over a set of possible outcomes and theory change is triggered by a constraint which is incompatible with the initial theory. This leads agents to consult a higher order probability function, or a 'prior over priors,' to choose the most likely alternative theory which satisfies the constraint. The hypothesis testing model is applied to three examples: learning a simple probabilistic constraint involving coin bias, the sundowners problem for conditional learning, and the Judy Benjamin problem for learning conditional probability constraints. (shrink)

En su reciente obra Tony Lawson nos invita a recorrer una vez más un análisis detallado de los problemas de la economía como ciencia, y en particular del modelar matemático. Intenta responder a preguntas como ¿qué hacen los economistas académicos modernos?, ¿qué es actualmente la economía mainstream?, ¿qué esla economía neoclásica y qué la heterodoxa?, ¿cómo se relacionan las preocupaciones de los economistas modernos con aquellas que tradicionalmente consideraba la disciplina? y ¿cómo llegó la economía a su estado actual?

The critics of rational choice theory (RCT) frequently build on the contrast between so-called thick and thin applications of RCT to argue that thin RCT lacks the potential to explain the choices of real-world agents. In this paper, I draw on often-cited RCT applications in several decision sciences to demonstrate that despite this prominent critique there are at least two different senses in which thin RCT can explain real-world agents’ choices. I then defend this thesis against the most influential objections (...) put forward by the critics of RCT. In doing so, I explicate the implications of my thesis for the ongoing philosophical debate concerning the explanatory potential of RCT and the comparative merits of widely endorsed accounts of explanation. (shrink)

In a recent article, Barrett & Halvorson define a notion of equivalence for first-order theories, which they call “Morita equivalence.” To argue that Morita equivalence is a reasonable measure of “theoretical equivalence,” they make use of the claim that Morita extensions “say no more” than the theories they are extending. The goal of this article is to challenge this central claim by raising objections to their argument for it and by showing why there is good reason to think that the (...) claim itself is false. In light of these criticisms, this article develops a natural way for the advocate of Morita equivalence to respond. I prove that this response makes her criterion a special case of bi-interpretability, an already well-established barometer of theoretical equivalence. I conclude by providing reasons why the advocate of Morita equivalence should opt for a notion of theoretical equivalence that is defined in terms of interpretability rather than Morita extensions. (shrink)

In recent years, several authors advocated neuroscience imperialism, an instance of scientific imperialism whereby neuroscience methods and findings are systematically applied to model and explain phenomena investigated by other disciplines. Calls for neuroscience imperialism target a wide range of disciplines, including psychology, economics, and philosophy. To date, however, neuroscience imperialism has not received detailed attention by philosophers, and the debate concerning its identification and normative assessment is relatively underdeveloped. In this paper, I aim to remedy this situation by making some (...) conceptual distinctions about neuroscience imperialism and by providing a normative assessment of prominent calls in its favour. I shall articulate and defend two interrelated claims that, I argue, undermine prominent calls for neuroscience imperialism. First, the proponents of neuroscience imperialism significantly overstate the evidential and explanatory relevance of neuroscience methods and findings for the disciplines they target. And second, prominent calls for neuroscience imperialism point to an untenable reductionist position, which rests on unsupported empirical and normative presuppositions. To substantiate these two claims, I shall draw on two sets of influential calls for neuroscience imperialism, which respectively target the economic modelling of choice and entrenched philosophical conceptions of free agency. (shrink)

Well-known epistemologies of science have implications for how best to understand knowledge transfer (KT). Yet, to date, no serious attempt has been made explicate these particular implications. This paper infers views about KT from two popular epistemologies; what we characterize as incommensurabilitist views (after Devitt 2001; Bird 2002, 2008; Sankey and Hoyningen-Huene 2013) and voluntarist views (after van Fraassen 1984; Dupré 2001; Chakravartty 2015). We argue views of the former sort define the methodological, ontological, and social conditions under which research (...) operates within ‘different worlds’ (to use Kuhn’s expression), and entail that genuine KTs under those conditions should be difficult or even impossible. By contrast, more liberal voluntarist views recognize epistemological processes that allow for transfers across different sciences even under such conditions. After outlining these antithetical positions, we identify two kinds of KTs of two kinds present in well-known episodes in the history of ecology—specifically, successful model transfers from chemical kinetics and thermodynamics into areas of ecological research—which reveal significant limitations of incommensurabilitist views. We conclude by discussing how the selected examples support a pluralistic voluntarism regarding KT. (shrink)

In domains like stock brokerage, clinical psychiatry, and long‐term political forecasting, experts generally fail to outperform novices. Empirical researchers agree on why this is: experts must receive direct or environmental learning feedback during training to develop reliable expertise, and these domains are deficient in this type of feedback. A growing number of philosophers resource this consensus view to argue that, given the absence of direct or environmental philosophical feedback, we should not give the philosophical intuitions or theories of expert philosophers (...) greater credence than those of novice philosophers. This article has three objectives. The first is to explore several overlooked issues concerning the strategy of generalizing from empirical studies of non‐philosophical expertise to the epistemic status of philosophical expertise. The second is to explain why empirical research into a causal relationship between direct learning feedback and enhanced expert performance does not provide good grounds for abandoning a default optimism about the epistemic superiority of expert philosophical theories. The third is to sketch a positive characterization of learning feedback that addresses developmental concerns made salient by the empirical literature on expert performance for specifically theory‐driven or “armchair” domains like philosophy. (shrink)

In the large grey area between science and technology, specialisms emerge with associated specialists. But some specialisms remain ‘peripheral sciences’, never attaining the status of disciplines ensconced in universities, and their specialists do not become recognised professionals. A major social component of such side-lined sciences – one important grouping of techno-scientific workers – is the research-technology community. An important question concerning research-technology is to explain how the grouping survives without specialised disciplinary and professional affiliations. The case discussed illustrates the dynamics (...) of one such community. (shrink)

The concept of linguistic infinity has had a central role to play in foundational debates within theoretical linguistics since its more formal inception in the mid-twentieth century. The conceptualist tradition, marshalled in by Chomsky and others, holds that infinity is a core explanandum and a link to the formal sciences. Realism/Platonism takes this further to argue that linguistics is in fact a formal science with an abstract ontology. In this paper, I argue that a central misconstrual of formal apparatus of (...) recursive operations such as the set-theoretic operation merge has led to a mathematisation of the object of inquiry, producing a strong analogy with discrete mathematics and especially arithmetic. The main product of this error has been the assumption that natural, like some formal, languages are discretely infinite. I will offer an alternative means of capturing the insights and observations related to this posit in terms of scientific modelling. My chief aim will be to draw from the larger philosophy of science literature in order to offer a position of grammars as models compatible with various foundational interpretations of linguistics while being informed by contemporary ideas on scientific modelling for the natural and social sciences. (shrink)

Moderate pluralism is a popular position in contemporary philosophy of biology. Despite its popularity, various authors have argued that it tends to slide off off into a radical form of pluralism that is both normatively and descriptively ueptable. This paper looks at at the case of biological species classification, and evaluates a popular way of avoiding radical pluralism by relying on the shared aims and norms of a discipline. The main contention is that while these aims and norms may play (...) an important role in the legitimacy of species classifications, they fail to fend off radical pluralism. It follows from this that the legitimacy of species classifications is also determined by local decisions about the aims of research and how to operationalize and balance these. This is important, I argue, because it means that any acceptable view on the legitimacy of classification should be able to account for these local decisions. (shrink)

Most scientific theories are globally inconsistent. Chunk and Permeate is a method of rational reconstruction that can be used to separate, and identify, locally consistent chunks of reasoning or explanation. This then allows us to justify reasoning in a globally inconsistent theory. We extend chunk and permeate by adding a visually transparent way of guiding the individuation of chunks and deciding on what information permeates from one chunk to the next. The visual representation is in the form of bundle diagrams. (...) We then extend the bundle diagrams to include not only reasoning in the presence of inconsistent information or reasoning in the logical sense of deriving a conclusion from premises, but more generally reasoning in the sense of trying to understand a phenomenon in science. This extends the use of the bundle diagrams in terms of the base space and the fibres. We then apply this to a case in physics, that of understanding binding energies in the nucleus of an atom using together inconsistent models: the liquid drop model and the shell model. We draw some philosophical conclusions concerning scientific reasoning, paraconsistent reasoning, the role of logic in science and the unity of science. (shrink)

We review the most prominent modeling approaches in social epistemology aimed at understand- ing the functioning of epistemic communities and provide a philosophy of science perspective on the use and interpretation of such simple toy models, thereby suggesting how they could be integrated with conceptual and empirical work. We highlight the need for better integration of such models with relevant findings from disciplines such as social psychology and organization studies.

I propose a framework that explicates and distinguishes the epistemic roles of data and models within empirical inquiry through consideration of their use in scientific practice. After arguing that Suppes’ characterization of data models falls short in this respect, I discuss a case of data processing within exploratory research in plant phenotyping and use it to highlight the difference between practices aimed to make data usable as evidence and practices aimed to use data to represent a specific phenomenon. I then (...) argue that whether a set of objects functions as data or models does not depend on intrinsic differences in their physical properties, level of abstraction or the degree of human intervention involved in generating them, but rather on their distinctive roles towards identifying and characterizing the targets of investigation. The paper thus proposes a characterization of data models that builds on Suppes’ attention to data practices, without however needing to posit a fixed hierarchy of data and models or a highly exclusionary definition of data models as statistical constructs. (shrink)

For centuries the case of Galileo Galilei has been the cornerstone of every major argument against the church and its supposedly unscientific dogmatism. The church seems to have condemned Galileo for his heresies, just because it couldn’t and wouldn’t handle the truth. Galileo was a hero of science wrongfully accused and now – at last – everyone knows that. But is that true? This paper tries to examine the case from the point of modern physics and the conclusions drawn are (...) startling. It seems that contemporary church was too haste into condemning itself. The evidence provided by Galileo to support the heliocentric system do not even pass simple scrutiny, while modern physics has ruled for a long time now against both heliocentric and geocentric models as depictions of the “truth”. As Einstein eloquently said, the debate about which system is chosen is void of any meaning from a physics’ point of view. At the end, the selection of the center is more a matter of choice rather than a matter of ‘truth’ of any kind. And this choice is driven by specific philosophical axioms penetrating astronomy for hundreds of years now. From Galileo to Hubble, the Copernican principle has been slowly transformed to a dogma followed by all mainstream astronomers. It is time to challenge our dogmatic adherence to the anti-humanism idea that we are insignificant in the cosmos and start making true honest science again, as Copernicus once postulated. (shrink)

In this thesis I am going to explain the role of metaphor in articulation of new scientific theories, explicitly speaking, indeed, I have not a word about metaphorical thinking in theory invention, implicitly speaking. In fact, I talk about conceptual metaphor instead of linguistic metaphor. As another classification, this investigation belongs to “justification context”, rather than “discovery context”. Employing Boyd’ ideas on metaphor in science can lend a hand for acquiring this point. In Boyd’ set of beliefs; we need another (...) reference theory which has not the problems of kiripki-pautnam’s reference fixing theory, thus, Boyd proposes the “epistemic-access theory of reference”. With accepting “interacting view” of Block on metaphor, he demonstrates that in this theory of reference we are not encountering the problems such as referent shifting, lack of precise of metaphor which exist in kripki-pautnam’s reference fixing. On the other hand, by admitting “relativity”, Kuhn criticizes the Boyd’s attitude on metaphor in science. To conclude, I defend kripki-pautnam’s reference fixing theory; since, it seems to be implausible to accept Boyd’s criticism. (shrink)

Econophysics is a new and exciting cross-disciplinary research field that applies models and modelling techniques from statistical physics to economic systems. It is not, however, without its critics: prominent figures in more mainstream economic theory have criticized some elements of the methodology of econophysics. One of the main lines of criticism concerns the nature of the modelling assumptions and idealizations involved, and a particular target are ‘kinetic exchange’ approaches used to model the emergence of inequality within the distribution of individual (...) monetary income. This article will consider such models in detail, and assess the warrant of the criticisms drawing upon the philosophical literature on modelling and idealization. Our aim is to provide the first steps towards informed mediation of this important and interesting interdisciplinary debate, and our hope is to offer guidance with regard to both the practice of modelling inequality, and the inequality of modelling practice. _1_ Introduction _1.1_ Econophysics and its discontents _1.2_ Against burglar economics _2_ Modelling Inequality _2.1_ Mainstream economic models for income distribution _2.2_ Econophysics models for income distribution _3_ Idealizations in Kinetic Exchange Models _3.1_ Binary interactions _3.2_ Conservation principles _3.3_ Exchange dynamics _ 4 _ Fat Tails and Savings _ 5 _ Evaluation. (shrink)

Mathematicians, physicists, and philosophers of physics often look to the symmetries of an object for insight into the structure and constitution of the object. My aim in this paper is to explain why this practice is successful. In order to do so, I present a collection of results that are closely related to (and in a sense, generalizations of) Beth’s and Svenonius’ theorems.

Modern scientific cosmology pushes the boundaries of knowledge and the knowable. This is prompting questions on the nature of scientific knowledge, and the emergence of the new field “Philosophy of Cosmology.” One central issue is what defines a “good” model. I discuss how “good” models are conventionally chosen, and how those methods operate in data-sparse situations: enabling the implicit introduction of value judgments, which can determine inference and lead to inferential polarization, e.g., on the question of ultimate explanation. Additional dimensions (...) for comparing models are needed. A three-legged comparison is proposed: evidence, elegance and beneficence. This explicitly considers the categories of criteria that are always at least implicitly used. A tentative path to an implementation of the proposed model comparison framework is presented. This extends the Bayesian statistical framework. Model comparison methodology is fertile ground for dialogue between the sciences and the humanities. The proposed framework might facilitate such a dialogue. (shrink)

دليل مُرتَّب أبجديًا للمصطلحات الأساسية، وكذلك لأشهر الأعلام، في المجالات المختلفة لفلسفة العلم. يُغطي الكتاب أبرز المشكلات، والمواقف، والتصورات، والحجج التي كانت مثار مناقشات واسعة بين الفلاسفة. والهدف الأساسي له هو فهم المناقشات الحالية من خلال تتبع وتفسير تطوراتها التاريخية وارتباطاتها بالمسائل الفلسفية الأبعد. ومع أن الكتاب يفترض مسبقًا وجود خلفية معرفية بفلسفة العلم لدى القارئ، إلا أنه مفيد بالقدر ذاته لكل من المبتدئين من دارسي فلسفة العلم، والمتخصصين ذوي الخبرات الواسعة، فضلاً عن عامة القُراء. وسوف يجد القارئ من خلال (...) تصفحه للكتاب تفسيرات مُركزة، وتحليلات دقيقة، وأمثلة توضيحية، ومشكلات مفتوحة، وأخيرًا وليس آخرًا، حججًا ذات بينة. وغني عن الذكر أن فلسفة العلم هي في حد ذاتها فرعٌ معرفي مزدهر، وهذا الكتاب بمثابة وسيلة عملية وتصورية فعالة للولوج داخل هذا الفرع المعرفي المميز واستكشاف أغواره. (shrink)

Until recently philosophy of physics has been overshadowed by the idea that the important philosophical issues that can be derived from physics are related only to fundamental theories, such as quantum mechanics and relativity. Applied fields of physics were deemed as unimportant. The argument for such a position lays in thinking that these applied fields of physics depend in their theoretical representations on fundamental theories and hence are reducible to these fundamental theories. It would be hard to defend such a (...) position, keeping in mind that applied fields of physics have a life of its own totally separate from fundamental physics and have in fact a lot to say to philosophers. The field of polymers is one of the branches of applied physics that has a lot to say to philosophers. It is a field of physics where theoreticians failed to present a coherent theory that can capture the different ways polymers can be built. This paper examines the difficulties that keep theoreticians away from having such a theory, revealing what kind of philosophical lessons polymers might have. The main thesis is: even in the cases where a theory predict the possibility of developing a specific type of polymers that was not previously known, the exact model that represent the outcome polymer theoretically will not be even in principle derivable from the theory that predicted its existence in the first place. (shrink)

An essay review of Michael Weisberg's Simulation and Similarity.

Models represent their target systems in one way or another. But what does it mean for a model to represent something beyond itself? This paper details different aspects of this problem and argues that the semantic view of theories does not provide us with an adequate response to any of these.

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)

The developmental trend in many fields of contemporary science is toward integrated general theories. These trends are viewed as essential components of the nature of science rather than expressions of arbitrary preferences of scientists. The law-like factors which lead science toward reliance on general theories include empirical as well as rational components. A model is proposed which exhibits the balance of the relevant factors as calling for increasing use of theories the primitive terms of which are progressively more abstract and (...) general, though no less precise and empirically adequate. (shrink)

Summary According to the so-called Starnberger Group1, the amenability of a science to science policy measures, conceptualised by the Group in terms of finalization , depends crucially on conditions intrinsic to the science not invariably present at every stage of its development. Finalization is possible only at junctures where the science in question faces methodologically divergent alternative lines of development. The most significant kind of case depends on the presence of completed , or classical , theories.