Scientific Models

This manifesto introduces Systemic Physics as a new theoretical domain grounded in the principles of emergence, synergy, and ontological continuity. It serves as the most comprehensive formulation of the Systemic Continuum Paradigm (SCP) to date—an approach that redefines reality not as a collection of fundamental particles, but as a multi-layered field of threshold-bound systems whose properties arise only through structured interactions. -/- By rejecting the traditional dichotomy between "natural" and "artificial" systems, the SCP proposes that all organized ensembles—ranging from galaxies (...) to neural networks—follow the same systemic logic: properties such as gravity, intelligence, resilience, and expansion emerge only when internal synergy (ISB) crosses a Systemic Threshold (ST), at which point one dynamic monopolizes the General Systemic Balance (GSB) of that scale. -/- This paper consolidates the ontological axioms, scale-relative mechanisms, and falsifiability criteria of the SCP; it reinterprets dark matter and dark energy as phase transitions within gravitational synergy, redefines forces as monopolies of emergence, and outlines a cross-domain roadmap for scientific application. Designed for physicists, philosophers, and complexity theorists, it positions emergence not as a metaphor, but as the structural law of reality. -/- It is both a theoretical scaffold and a call to action: to build a science that measures thresholds instead of assuming absolutes, and to approach the universe not as a closed equation, but as a living architecture of unfolding systemic resonance. (shrink)

Modal Empiricism in philosophy of science proposes to understand the possibility of modal knowledge from experience by replacing talk of possible worlds with talk of possible situations, which are coarse-grained, bounded and relative to background conditions. This allows for an induction towards objective necessity, assuming that actual situations are representative of possible ones. The main limitation of this epistemology is that it does not account for probabilistic knowledge. In this paper, we propose to extend Modal Empiricism to the probabilistic case, (...) thus providing an inductivist epistemology for probabilistic knowledge. The key idea is that extreme probabilities, close to 1 and 0, serve as proxies for testing mild probabilities, using a principle of model combination. (shrink)

Integrative structure modeling is a method for using information from multiple sources to compute structural models of biomolecular systems. It proceeds via four steps: (i) defining the model representation, which determines the variables whose values will be computed; (ii) constructing a function for scoring alternative models according to how well they accommodate input information; (iii) searching a space of candidate models for acceptable models; and (iv) analyzing acceptable models to evaluate their fit with input information. These steps are iterated until (...) a model adequate for addressing biological questions is found. In this paper, we draw lessons from integrative modeling about effective integration and about modeling. We describe what it means to integrate information from multiple sources: Integration amounts to distributing information among the four steps of integrative modeling. Theory and data alike can be sources of information; this process thus generates models of information, rather than models of theory or models of data. We then propose heuristics for distributing information and designing multiple iterations of modeling. Effective iteration requires prioritizing the most reliable information and minimizing the time required to obtain an adequate model. Rather than being constructed from theory and assessed using data, models are constructed from any available information and assessed in a coherentist manner. (shrink)

The use of statistical methods to model gravitational systems is crucial to physics practice, but the extent to which thermodynamics and statistical mechanics genuinely apply to these systems is a contentious issue. This paper provides new conceptual foundations for gravitational thermodynamics by reconsidering the nature of key concepts like equilibrium and advancing a novel way of understanding thermodynamics. The challenges arise from the peculiar characteristics of the gravitational potential, leading to non-extensive energy and entropy, negative heat capacity, and a lack (...) of standard equilibrium. Hence it has been claimed that only non-equilibrium statistical mechanics is warranted in this domain, whereas thermodynamics is inapplicable. We argue instead that equilibrium statistical mechanics applies to self-gravitating systems at the relevant scale, as they display equilibrium in the form of metastable quasi-equilibrium states. We then develop a minimal framework for thermodynamics that can be applied to these systems and beyond. Thermodynamics applies in the sense that we can devise macroscopic descriptions and explanations of the behaviour of these systems in terms of coarse-grained quantities like energy and temperature within equilibrium statistical mechanics. (shrink)

The use of statistical methods to model gravitational systems is crucial to physics practice, but the extent to which thermodynamics and statistical mechanics genuinely apply to these systems is a contentious issue. This paper provides new conceptual foundations for gravitational thermodynamics by reconsidering the nature of key concepts like equilibrium and advancing a novel way of understanding thermodynamics. The challenges arise from the peculiar characteristics of the gravitational potential, leading to non-extensive energy and entropy, negative heat capacity, and a lack (...) of standard equilibrium. Hence it has been claimed that only non-equilibrium statistical mechanics is warranted in this domain, whereas thermodynamics is inapplicable. We argue instead that equilibrium statistical mechanics applies to self-gravitating systems at the relevant scale, as they display equilibrium in the form of metastable quasi-equilibrium states. We then develop a minimal framework for thermodynamics that can be applied to these systems and beyond. Thermodynamics applies in the sense that we can devise macroscopic descriptions and explanations of the behaviour of these systems in terms of coarse-grained quantities like energy and temperature within equilibrium statistical mechanics. (shrink)

In this chapter, I argue that genuinely abstract images do not depict but have aboutness, nevertheless. All images have aboutness in virtue of the visual configurations on their surfaces: it is through those configurations that they can convey something – they can mean something, represent something, express something, and so on. On the one hand, in depictive images, the visual configurations on the images’ surfaces depict visible objects while abstracting completely from some of their visual proper- ties. In Giovanni Bellini’s (...) Portrait of Doge Leonardo Loredan (1501), for instance, the visual configurations on the pictorial surface depict Doge Loredan’s head and torso, as seen frontally. The image, however, com- pletely abstracts from, e.g., Doge Loredan’s legs, nape, and back. On the other hand, as I shall argue, when the visual configurations on a two- dimensional surface do not depict anything at all but have aboutness in ways other than the depictive, that two-dimensional surface is a genu- inely abstract image. As I shall show, all genuinely abstract images entirely abstain from depicting but can nevertheless abstract in different measures from the visual properties of objects. The first step for an account of genuinely abstract images is to distin- guish accurately between depictive images and genuinely abstract ones. For this, one needs an account of depiction – this is provided in the first section of this chapter. In the second section, different kinds of depictive images are singled out: this facilitates focusing on images that qualify as genuinely abstract. In the third section, four ways in which genuinely abstract images have aboutness are discussed: conventionality, indexicality, exemplifica- tion, and expressivity. The fourth section concludes with some general observations on the peculiarities of genuinely abstract images. (shrink)

Models are used to explore possibilities across all scientific fields. Climate models simulate the potential future climatic conditions under various emissions scenarios, macroeconomic models investigate the implications of various fiscal and monetary policy initiatives, and infectious diseases models study the spread of viral diseases under a range of conditions. Such modeling approaches have not gone ignored by philosophers of science, but they have only recently started to explicitly address modeling the possible. So far, the discussion has been spread across a (...) variety of more or less isolated pockets of debate in the philosophy of science. Modeling the Possible: Perspectives from Philosophy of Science draws together these studies, focusing specifically on how various modeling practices probe possibilities and justify claims concerning them. -/- The volume is divided into three sections, plus an introductory chapter. The introductory chapter provides a state-of-the-art survey of the discussions of modeling possibilities within the philosophy of science, as well as an introduction to the book’s main themes and individual papers. The three sections focus on different kinds of possibility concepts, possibility spaces, and how-possibly modeling in practical situations. The chapters contained in this volume address conceptual and theoretical issues while also presenting case studies from various scientific domains: physics, evolutionary and synthetic biology, network science, climate science, economics, and epidemiology. -/- Essential reading for philosophers of science, epistemologists, and modelers in various scientific disciplines, Modeling the Possible is also suitable for anyone interested in model-based scientific inferences, their validity, and the policy conclusions derived from them. (shrink)

Scientists and philosophers alike debate whether various systems such as plants and bacteria exercise cognition. One strategy for resolving such debates is to ground claims about nonhuman cognition in evidence from mathematical models of cognitive capacities. In this article, I show that proponents of this strategy face two major challenges: demarcating phenomenological models from process models and overcoming underdetermination by model fit. I argue that even if the demarcation problem is resolved, fitting a process model to behavioral data is, on (...) its own, not strong evidence for any cognitive process, let alone processes shared with humans. (shrink)

Many recent AI systems take inspiration from biological episodic memory. Here, we ask how these ‘episodic-inspired’ AI systems might inform our understanding of biological episodic memory. We discuss work showing that these systems implement some key features of episodic memory whilst differing in important respects, and appear to enjoy behavioural advantages in the domains of strategic decision-making, fast learning, navigation, exploration and acting over temporal distance. We propose that these systems could be used to evaluate competing theories of episodic memory’s (...) operations and function. However, further work is needed to validate them as models of episodic memory and isolate the contributions of their memory systems to their behaviour. More immediately, we propose that these systems have a role to play in directing episodic memory research by highlighting novel or neglected hypotheses as pursuit-worthy. In this vein, we propose that the evidence reviewed here highlights two pursuit-worthy hypotheses about episodic memory’s function: that it plays a role in planning that is independent of future-oriented simulation, and that it is adaptive in virtue of its contributions to fast learning in novel, sparse-reward environments. (shrink)

In an influential paper, Wendy Parker argues that agreement across climate models isn’t a reliable marker of confirmation in the context of cutting-edge climate science. In this paper, I argue that while Parker’s conclusion is generally correct, there is an important class of exceptions. Broadly speaking, agreement is not a reliable marker of confirmation when the hypotheses under consideration are mutually consistent—when, e.g., we’re concerned with overlapping ranges. Since many cutting-edge questions in climate modeling require making distinctions between mutually consistent (...) hypotheses, agreement across models will be generally unreliable in this domain. In cases where we are only concerned with mutually exclusive hypotheses, by contrast, agreement across climate models is plausibly a reliable marker of confirmation. (shrink)

This paper aims to develop an account of the pursuitworthiness of models based on a view of models as epistemic tools. This paper is motivated by the historical question of why, in the 1960s, when many scientists hardly found QSAR models attractive, some pharmaceutical scientists pursued Quantitative Structure–Activity Relationship (QSAR) models despite the lack of potential for theoretical development or empirical success. This paper addresses this question by focusing on how models perform their heuristic functions as epistemic tools rather than (...) as potential theories. I argue that models perform their heuristic function by “constructing” phenomena from data in the sense that they allow the model users who interact with the medium of the models to recognise the phenomena as such. The constructed phenomena assist model users in identifying which conditional hypotheses that are focused on low-level regularities concerning entities such as chemical compounds are more “testworthy,” a concept that links the costs associated with hypothesis testing with the fertility of the hypothesis. (shrink)

Counterfactual reasoning has been used to account for many aspects of scientific reasoning. More recently, it has also been used to account for the scientific practice of modeling. Truth in a model is truth in a situation considered as counterfactual. When we reason with models, we reason with counterfactuals. Focusing on selected models like Bohr’s atom model or models of population dynamics, I present an account of how the imaginative development of a counterfactual supposition leads us from reality to interesting (...) model assumptions; how it guides our reasoning from these assumptions to interesting consequences for the model scenario via counterfactual entailment; and how it leads us back to conclusions on real target phenomena. (shrink)

This book -which initiates the collection "Philosophy and Science" of the National University of Quilmes Publishing House- contains almost all the papers presented at the I International Meeting "Current Perspectives of Metatheoretical Structuralism", which, with the purpose of gathering a small group of distinguished Spanish-speaking philosophers interested in discussing the epistemological and methodological problems of science from the perspective of the structuralist view, was held in Zacatecas, Mexico, from February 16 to 20, 1998.

Financial modelling is an essential tool for studying the possibility of financial transactions. This paper argues that financial models are conventional tools widely used in formulating and establishing possibility claims about a prospective investment transaction, from a set of governing possibility assumptions. What is distinctive about financial models is that they articulate how a transaction possibly could occur in a non-actual investment scenario given a limited base of possibility conditions assumed in the model. For this reason, it is argued that (...) the epistemic contribution of financial models is that of enabling the model users to envision exactly how a prospective investment could be achieved in various ways through a detailed understanding of the available transaction mechanisms. Thus, financial models provide information about the possibility of an investment scenario by showing how a specific transaction mechanism could result from a small set of initial possibility conditions assumed in the model. (shrink)

Cancer biology features the ascription of normal functions to parts of cancers. At least some ascriptions of function in cancer biology track local normality of parts within the global abnormality of the aberration to which those parts belong. That is, cancer biologists identify as functions activities that, in some sense, parts of cancers are supposed to perform, despite cancers themselves having no purpose. The present paper provides a theory to accommodate these normal function ascriptions—I call it the Modeling Account of (...) Normal Function (MA). MA comprises two claims. First, normal functions are activities whose performance by the function-bearing part contributes to the self-maintenance of the whole system and, thereby, results in the continued presence of that part. Second, MA holds that models of system-level activities that are (partly) constitutive of self-maintenance are improved by including a representation of the relevant function-bearing part and by making reference to the activity/activities that part performs which contribute(s) to those system-level activities. I contrast MA with two other accounts that seek to explicate the ascription of normal functions in biology, namely, the organizational account and the selected effects account. Both struggle to extend to cancer biology. However, I offer ecumenical readings which allow them to recover some ascriptions of normal function to parts of cancers. So, though I contend that MA excels in this respect, the purpose of this paper is served if it provides materials for bridging the gap between cancer biology, philosophy of cancer, and the literature on function. (shrink)

Predictive processing (PP) and embodied cognition (EC) have emerged as two influential approaches within cognitive science in recent years. Not only have PP and EC been heralded as “revolutions” and “paradigm shifts” but they have motivated a number of new and interesting areas of research. This has prompted some to wonder how compatible the two views might be. This paper looks to weigh in on the issue of PP-EC compatibility. After outlining two recent proposals, I argue that further clarity can (...) be achieved on the issue by considering a model of scientific progress. Specifically, I suggest that Larry Laudan’s “problem solving model” can provide important insights into a number of outstanding challenges that face existing accounts of PP-EC compatibility. I conclude by outlining additional implications of the problem solving model for PP and EC more generally. (shrink)

Modern science is, to a large extent, a model-building activity. But how are models contructed? How are they related to theories and data? How do they explain complex scientific phenomena, and which role do computer simulations play here? These questions have kept philosophers of science busy for many years, and much work has been done to identify modeling as the central activity of theoretical science. At the same time, these questions have been addressed by methodologically-minded scientists, albeit from a different (...) point of view. While philosophers typically have an eye on general aspects of scientific modeling, scientists typically take their own science as the starting point and are often more concerned with specific methodological problems. There is, however, also much common ground in middle, where philosophers and scientists can engage in a productive dialogue, as the present volume demonstrates. (shrink)

Ce livre est un livre d’épistémologie de la sociologie. L’objectif est d’appliquer des méthodes analytiques pour clarifier le vocabulaire, expliciter des relations non-apparentes entre concepts, dégager la portée d’une méthode, ou souligner les incohérences d’un programme de recherche. Les questions épineuses ne sont pas écartéees: Comment clarifier des notions confuses? Peut-on mathématiser les concepts sociologiques? Peut-on pratiquer la sociologie comme on pratique les sciences naturelles? Quelle est la place du déterminisme? Chaque question est examinée à la fois dans sa structure (...) logique et sur des cas concrets. La mathématisation est étudiée sur les mécanismes agrégatifs et sur les modèles de diffusion des innovations. La sociologie expérimentale – généralement méconnue dans la sociologie française – est étudiée sur des programmes de relogement, la diffusion de l’information, ou la genèse de la solidarité sociale. Le livre aborde frontalement la question du déterminisme, du naturalisme, du matérialisme et du scientisme, réputés intenables en sociologie. L’enquête montre que leur rejet résulte généralement de confusions conceptuelles. Une fois écartées, peu d’obstacles s’opposent à leur emploi en sociologie. L’objet de ce livre est la sociologie fondamentale: ensemble des mécanismes qui structurent la production des connaissances sociologiques de base à partir de concepts, programmes ou principes, c’est-à-dire tout ce qui ne relève pas de l’expérience immédiate du terrain et des mondes sociaux. (shrink)

Convergence of model projections is often considered by climate scientists to be an important objective in so far as it may indicate the robustness of the models’ core hypotheses. Consequently, the range of climate projections from a multi-model ensemble, called “model spread”, is often expected to reduce as climate research moves forward. However, the successive Assessment Reports of the Intergovernmental Panel on Climate Change indicate no reduction in model spread, whereas it is indisputable that climate science has made improvements in (...) its modelling. In this paper, after providing a detailed explanation of the situation, we describe an epistemological setting in which a steady model spread is not doomed to be seen as negative, and is indeed compatible with a desirable evolution of climate models taken individually. We further argue that, from the perspective of collective progress, as far as the improvement of the products of a multi-model ensemble is concerned, reduction of model spread is of lower priority than model independence. (shrink)

Although there is a substantial philosophical literature on dynamical systems theory in the cognitive sciences, the same is not the case for neuroscience. This paper attempts to motivate increased discussion via a set of overlapping issues. The first aim is primarily historical and is to demonstrate that dynamical systems theory is currently experiencing a renaissance in neuroscience. Although dynamical concepts and methods are becoming increasingly popular in contemporary neuroscience, the general approach should not be viewed as something entirely new to (...) neuroscience. Instead, it is more appropriate to view the current developments as making central again approaches that facilitated some of neuroscience’s most significant early achievements, namely, the Hodgkin–Huxley and FitzHugh–Nagumo models. The second aim is primarily critical and defends a version of the “dynamical hypothesis” in neuroscience. Whereas the original version centered on defending a noncomputational and nonrepresentational account of cognition, the version I have in mind is broader and includes both cognition and the neural systems that realize it as well. In view of that, I discuss research on motor control as a paradigmatic example demonstrating that the concepts and methods of dynamical systems theory are increasingly and successfully being applied to neural systems in contemporary neuroscience. More significantly, such applications are motivating a stronger metaphysical claim, that is, understanding neural systems as being dynamical systems, which includes not requiring appeal to representations to explain or understand those phenomena. Taken together, the historical claim and the critical claim demonstrate that the dynamical hypothesis is undergoing a renaissance in contemporary neuroscience. (shrink)

ABSTRACT This article distinguishes nine senses of polarization and provides formal measures for each one to refine the methodology used to describe polarization in distributions of attitudes. Each distinct concept is explained through a definition, formal measures, examples, and references. We then apply these measures to GSS data regarding political views, opinions on abortion, and religiosity—topics described as revealing social polarization. Previous breakdowns of polarization include domain-specific assumptions and focus on a subset of the distribution’s features. This has conflated multiple, (...) independent features of attitude distributions. The current work aims to extract the distinct senses of polarization and demonstrate that by becoming clearer on these distinctions we can better focus our efforts on substantive issues in social phenomena. (shrink)

A first take, matured in later work, in modeling belief polarization.

Tony Lawson, founder of The Social Ontology Group and The Realist Workshop of Cambridge, has proposed critical realism to reorient economics. The transformation of the social world that Lawson tries, emerges from the adherence to critical realism, this is, from taking the transcendental realism of Roy Bhaskar to the social realm. With the purpose of deepening the criticisms to this movement, we will specify what is critical realism, and which are the philosophical assumptions of the mainstream according to this author. (...) We will set out the criticisms on: a) the notion of mainstream economics, b) the possibilities of economics based on social ontology, c) the realism of economic models, and d) the notions of isolation and abstraction. (shrink)

The present paper tries to show that in the discussion on whether it is better to model or not to capture truth in the social world, that is not what is mainly being discussed. We put forward that the main question in this discussion is, essentially, ontological, not methodological. As a representative of the “to model position” we will refer to Uskali Mäki’s Possible Realism, and as one ofthe “notto model position” we will consider Tony Lawson’s Critical Realism. What will (...) be argued isthat the main differences between these positions asregards methodology to access the social world, lie in the different ontologies about the social realm. It will also be introduced ifthere is any possibility of an “in between position”, or atleastthe chance of a dialogue between these different epistemological trends. (shrink)

La presente obra ofrece un análisis crítico de la filosofía de la economía de Uskali Mäki; en particular de la consideración realista científica de la economía. Se intenta a lo largo del texto responder, de algún modo, a las preguntas que plantea Lehtinen en la introducción: “¿Están los economistas aspirando en absoluto a la verdad, o están solamente jugando un juego intelectual en que tales supuestos son aceptables por alguna razón misteriosa? ¿Están estudiando la economía en serio? ¿Están simplemente desinteresados (...) en la verdad?, o ¿hay tal vez alguna otra forma de considerar sus prácticas de modelar?” p. 1. (shrink)

Entender algo sobre un mundo que se nos presenta de modo desordenado e incompleto constituye buena parte de la tarea de la filosofía y de la ciencia. La racionalidad, los modelos, y el mundo social introducen preocupaciones propias de la filosofía de la ciencia en general y de la epistemología de la economía en particular. Los aportes de Popper, Lawson, Mäki, Hayek y Cartwright se expresan en estos trazos como intentos abiertos para alcanzar a comprender nuestro mundo.

In the debate on realism of models in economics, the Austrian School and Hayekin particular, seem to have, in a certain way, remained outside. Assuming neoclassical models asunrealistic, the theory of the market as a process looks like a more realistic proposal. However, oneof the fundamental issue s in Hayek’s dissent is not so much the unrealism of the assumptions, but that the market equilibrium theory was not correctly raised, especially with regards to the perfectknowledge assumption. Despite this, in this (...) setting and in line with a previous paper (Zanotti & Borella, 2015), we will argue that Hayek’s spontaneous order may be understood as the Austrian School’s “model”, assuming Mäki’s MISS version of models (Models as Isolations and Surrogate Systems) and emphasizing the place of the ontological foundation of Hayek’s proposal when assessing his model. (shrink)

There has recently been an explosion of formal models of signalling, which have been developed to learn about different aspects of meaning. This paper discusses whether that success can also be used to provide an original naturalistic theory of meaning in terms of information or some related notion. In particular, it argues that, although these models can teach us a lot about different aspects of content, at the moment they fail to support the idea that meaning just is some kind (...) of information. As an alternative, I suggest a more modest approach to the relationship between informational notions used in models and semantic properties in the natural world. (shrink)

Rather than assume a unitary cybernetics, I ask how its disunity mattered to the history of the human sciences in the United States from about 1940 to 1980. I compare the work of four prominent social scientists – Herbert Simon, George Miller, Karl Deutsch, and Talcott Parsons – who created cybernetic models in psychology, economics, political science, and sociology with the work of anthropologist Gregory Bateson, and relate their interpretations of cybernetics to those of such well-known cyberneticians as Norbert Wiener, (...) Warren McCulloch, W. Ross Ashby, and Heinz von Foerster. I argue that viewing cybernetics through the lens of disunity – asking what was at stake in choosing a specific cybernetic model – shows the complexity of the relationship between first-order cybernetics and the postwar human sciences, and helps us rethink the history of second-order cybernetics. (shrink)

In this article I give a critical evaluation of the use and limitations of null-model-based hypothesis testing as a research strategy in the biological sciences. According to this strategy, the null model based on a randomization procedure provides an appropriate null hypothesis stating that the existence of a pattern is the result of random processes or can be expected by chance alone, and proponents of other hypotheses should first try to reject this null hypothesis in order to demonstrate their own (...) hypotheses. Using as an example the controversy over the use of null hypotheses and null models in species co-occurrence studies, I argue that null-model-based hypothesis testing fails to work as a proper analog to traditional statistical null-hypothesis testing as used in well-controlled experimental research, and that the random process hypothesis should not be privileged as a null hypothesis. Instead, the possible use of the null model resides in its role of providing a way to challenge scientists’ commonsense judgments about how a seemingly unusual pattern could have come to be. Despite this possible use, null-model-based hypothesis testing still carries certain limitations, and it should not be regarded as an obligation for biologists who are interested in explaining patterns in nature to first conduct such a test before pursuing their own hypotheses. (shrink)

Our paper studies the anatomy of the discovery of the Higgs boson at the Large Hadron Collider and its influence on the broader model landscape of particle physics. We investigate the phases of this discovery, which led to a crucial reconfiguration of the model landscape of elementary particle physics and eventually to a confirmation of the standard model. A keyword search of preprints covering the electroweak symmetry breaking sector of particle physics, along with an examination of physicists own understanding of (...) the discovery as documented in semiannual conferences, has allowed us an empirical investigation of its model dynamics. From our analyses we draw two main philosophical lessons concerning the nature of scientific reasoning in a complex experimental and theoretical environment. For one, from a confirmation standpoint, some SM alternatives could be considered even more confirmed by the Higgs discovery than the SM. Nevertheless, the SM largely remains the commonly accepted account of EWSB. We present criteria for comparing degrees of confirmation and expose some limits of a purely logical approach to understanding the Higgs discovery as a victory for the SM. Second, we understand the persistence of SM alternatives in the face of disfavourable evidence by borrowing the Lakatosian concept of a research programme, where the core idea behind a group of models survives, while other aspects adapt to incoming data. In order to apply this framework to the model landscape of EWSB, we must introduce a new category of research programme, the model-group, and we test its viability using the example of composite Higgs models. (shrink)

South Korean high school students are being taught Einstein’s Special Theory of Relativity. In this article, I examine the portrayal of this theory in South Korean high school physics textbooks and discuss an alternative method used to solve the analyzed problems. This examination of how these South Korean textbooks present this theory has revealed two main flaws: First, the textbooks’ contents present historically fallacious backgrounds regarding the origin of this theory because of a blind dependence on popular undergraduate textbooks, which (...) ignore the revolutionary aspects of the theory in physics. And second, the current ingredients of teaching this theory are so simply enumerated and conceptually confused that students are not provided with good opportunities to develop critical capacities for evaluating scientific theories. Reviewing textbooks used in South Korea, I will, first, claim that the history of science contributes to understand not merely the origins but also two principles of this theory. Second, in addition to this claim, I argue that we should distinguish not only hypotheses from principles but also phenomena from theoretical consequences and evidence. Finally, I suggest an alternative way in which theory testing occurs in the process of evaluation among competitive theories on the basis of data, not in the simple relation between a hypothesis and evidence. (shrink)

In this paper, I address the issue of scientific modelling in contemporary linguistics, focusing on the generative tradition. In so doing, I identify two common varieties of linguistic idealisation, which I call determination and isolation respectively. I argue that these distinct types of idealisation can both be described within the remit of Weisberg’s :639–659, 2007) minimalist idealisation strategy in the sciences. Following a line set by Blutner :27–35, 2011), I propose this minimalist idealisation analysis for a broad construal of the (...) generative linguistic programme and thus cite examples from a wide range of linguistic frameworks including early generative syntax, Minimalism, the parallel architecture and optimality theory. Lastly, I claim that from a modelling perspective, the dynamic turn in syntax can be explained as a continuation, as opposed to a marked shift, of the generative modelling paradigm. Seen in this light, my proposal is an even broader construal of the generative tradition, along scientific modelling lines. Thus, I offer a lens through which to appreciate the scientific contribution of generative grammar, amid an increased resistance to some of its core theoretical posits, in terms of a brand of structural realism in the philosophy of science and specifically scientific modelling. (shrink)

Theoretical astrophysics emerged as a significant research programme with the construction of a series of stellar models by A. S. Eddington. This paper examines the controversies surrounding those models as a way of understanding the development and justification of new theoretical technologies. In particular, it examines the challenges raised against Eddington by James Jeans, and explores how the two astronomers championed different visions of what it meant to do science. Jeans argued for a scientific method based on certainty and completeness, (...) whereas Eddington called for a method that valued exploration and further investigation, even at the sake of secure foundations. The first generation of stellar models depended on the validity of Eddington's approach – the physics and many of the basic facts of stars were poorly understood and he justified his models through their utility for future research and their robustness under challenging use. What would become theoretical astrophysics depended heavily on this phenomenological outlook, which Jeans dismissed as not even science. This was a dispute about the practice of theory, and it would be this methodological debate that made theoretical astrophysics viable. (shrink)

One persistent challenge in scientific practice is that the structure of the world can be unstable: changes in the broader context can alter which model of a phenomenon is preferred, all without any overt signal. Scientific discovery becomes much harder when we have a moving target, and the resulting incorrect understandings of relationships in the world can have significant real-world and practical consequences. In this paper, we argue that it is common (in certain sciences) to have changes of context that (...) lead to changes in the relationships under study, but that standard normative accounts of scientific inquiry have assumed away this problem. At the same time, we show that inference and discovery methods can “protect” themselves in various ways against this possibility by using methods with the novel methodological virtue of “diligence.” Unfortunately, this desirable virtue provably is incompatible with other desirable methodological virtues that are central to reliable inquiry. No scientific method can provide every virtue that we might want. (shrink)

Precaution is a relevant and much-invoked value in environmental risk analysis, as witnessed by the ongoing vivid discussion about the precautionary principle (PP). This article argues (i) against purely decision-theoretic explications of PP; (ii) that the construction, evaluation, and use of scientific models falls under the scope of PP; and (iii) that epistemic and decision-theoretic robustness are essential for precautionary policy making. These claims are elaborated and defended by means of case studies from climate science and conservation biology.

Using Sneed's metatheory an attempt is made to reconstruct Hodgkin and Huxley's theory of excitation of cell membranes. The structure of this theory is uncovered by defining set-theoretical predicates for the partial potential models, potential models, and models of the theory. The function of permeability is said to be the only theoretical function with respect to this theory. The main underlying assumptions of the theory are briefly outlined.

Experimental activity is traditionally identified with testing the empirical implications or numerical simulations of models against data. In critical reaction to the ‘tribunal view’ on experiments, this essay will show the constructive contribution of experimental activity to the processes of modeling and simulating. Based on the analysis of a case in fluid mechanics, it will focus specifically on two aspects. The first is the controversial specification of the conditions in which the data are to be obtained. The second is conceptual (...) clarification, with a redefinition of concepts central to the understanding of the phenomenon and the conditions of its occurrence. (shrink)

The papers collected here are the result of an INTERNATIONAL SYMPOSIUM: Data · Phenomena · Theories: What’s the notion of a scientific phenomenon good for? held in Heidelberg in September 2008. The event was organized by the research group Causality, Cognition, and the Constitution of Scientific Phenomena in cooperation with Philosophy Department at the University of Heidelberg (Peter McLaughlin and Andreas Kemmerling) and the IWH Heidelberg. The symposium was supported by the Emmy-Noether-Programm der Deutschen Forschungsgemeinschaft and by Stiftung Universitat Heidelebrg (...) . The workshop was held in honor of Daniela Bailer-Jones, who died on 13 November 2006 at the age of 37 (cf. my 2007 Daniela Bailer-Jones ). Bailer-Jones was an Emmy Noether fellow, and the symposium was arranged and run by those who were working in her research group at the time of her death: Monika Dullstein, Jochen Apel, and Pavel Radchencko. To them goes the credit for the conception, planning, and carrying out of the symposium. (shrink)

Designing models of complex phenomena is a difficult task in engineering that can be tackled by composing a number of partial models to produce a global model of the phenomena. We propose to embed the partial models in software agents and to implement their composition as a cooperative negotiation between the agents. The resulting multiagent system provides a global model of a phenomenon. We applied this approach in modelling two complex physiological processes: the heart rate regulation and the glucose-insulin metabolism. (...) Beyond the effectiveness demonstrated in these two applications, the idea of using models associated to software agents to give reason of complex phenomena is in accordance with current tendencies in epistemology, where it is evident an increasing use of computational models for scientific explanation and analysis. Therefore, our approach has not only a practical, but also a theoretical significance: agents embedding models are a technology suitable both to representing and to investigating reality. (shrink)

It has become increasingly clear that natural phenomena cannot be formally deduced from laws but that almost every phenomenon has its own particular way of being linked to higher-level generalizations, usually via approximations, normalizations and corrections. This article deals with the following problem: if there are no general principles to link laws to phenomena, and if each phenomenon has its own way of being explained, how can we -- or how can a theory -- explain any new phenomenon? I will (...) argue that while particular explanations only apply to the specific phenomena they describe, parts of such explanations can be productively reused in explaining new phenomena. This leads to a view on theory, which I call maximalism, according to which new phenomena are understood in terms of previous phenomena. On the maximalist view, a theory is not a system of axioms or a class of models, but a dynamically updated corpus of explanations. New phenomena are explained by combining fragments of explanations of previous phenomena. I will give an instantiation of this view, based on a corpus of phenomena from classical and fluid mechanics, and show that the maximalist approach is not only used but also needed in scientific practice. (shrink)

Unlike basic sciences, scientific research in advanced technologies aims to explain, predict, and (mathematically) describe not phenomena in nature, but phenomena in technological artefacts, thereby producing knowledge that is utilized in technological design. This article first explains why the covering-law view of applying science is inadequate for characterizing this research practice. Instead, the covering-law approach and causal explanation are integrated in this practice. Ludwig Prandtl's approach to concrete fluid flows is used as an example of scientific research in the engineering (...) sciences. A methodology of distinguishing between regions in space and/or phases in time that show distinct physical behaviours is specific to this research practice. Accordingly, two types of models specific to the engineering sciences are introduced. The diagrammatic model represents the causal explanation of physical behaviour in distinct spatial regions or time phases; the nomo-mathematical model represents the phenomenon in terms of a set of mathematically formulated laws. (shrink)

Can Science do without a Theory? The main questions that are discussed are as follows: 1) Do we have - as a matter of fact - a general philosophy of science which is comprehensive and powerful enough to present a solution to all the relevant methodological and metatheoretical problems arising within the sciences? 2) Do scientists feel a need for such a general metatheoretical tool? 3) In the probable case of a negative answer to both questions posed above: what, if (...) any, is the legitimate status of the philosophy of science? It is argued in some detail that at least three types of models have failed, at least as far as their advisory function for scientific action in realistic situational settings is concerned: the ideal language model (Wittgenstein, Carnap), methodological falsificationism (Popper), and behavioral theories of scientific action. From the standpoint of the history of science it is plainly obvious that science has always been ahead of its purported metatheory and that important advances within the latter had been implicit in real scientific action at least for centuries. (shrink)

My favorite opponent in this debate once made a remarkable concession, not that it interfered with business as usual:No sensible social scientist believes any particular specification, coefficient estimate, or standard error. Social science theories ... imply that specifications and parameters constant over situations do not exist ... One searches for qualitative theory ... not for quantitative specifications Achen (1987, p.149). . With Hooke's law and the like, we are estimating parameters in specifications that are constant across time—at least to a (...) very good degree of approximation But see Cartwright (1983). . What are the social scientists doing when they estimate non-existent parameters, and put standard errors on the output? How can that help them search for qualitative theory? Those are among the first of my questions, and I never get answers. (shrink)

The received view about emergence and reduction is that they are incompatible categories. I argue in this paper that, contrary to the received view, emergence and reduction can hold together. To support this thesis, I focus attention on dynamical systems and, on the basis of a general representation theorem, I argue that, as far as these systems are concerned, the emulation relationship is sufficient for reduction (intuitively, a dynamical system DS1 emulates a second dynamical system DS2 when DS1 exactly reproduces (...) the whole dynamics of DS2). This representational view of reduction, contrary to the standard deductivist one, is compatible with the existence of structural properties of the reduced system that are not also properties of the reducing one. Therefore, under this view, by no means are reduction and emergence incompatible categories but, rather, complementary ones. (shrink)