This chapter contains sections titled: Highlights of Past Literature Current Work Future Work.

Philosophers of science studying scientific practice often consider it a methodological requirement that their conceptualization of "model" closely connects with the understanding and use of models by practicing scientists. Occasionally, this connection has been explicitly made (Hutten 1954, Suppes 1961, Morgan and Morrison 1999, Bailer-Jones 2002, Lehtinen and Kuorikoski 2007, Kuorikoski 2007, Morgan 2012a). These studies have been dominated by a focus on the—relatively similar forms of—mathematical models in physics and economics. Yet it has become increasingly evident that the way (...) models are conceptualized is very different in some other sciences, where philosophers' accounts of models' characteristics and .. (shrink)

The traditional sciences often bracket away ambiguity through the imposition of “enabling constraints”—making a set of assumptions and then declaring ceteris paribus. These enabling constraints take the form of uncritically examined presuppositions or “uceps.” Second order science reveals hidden issues, problems and assumptions which all too often escape the attention of the practicing scientist. These hidden values—precisely because they are hidden and not made explicit—can get in the way of the public’s acceptance of a scientific claim. A conflict in understood (...) meaning—between the scientist’s restricted claims and the public’s broader understanding of those same claims can result in cognitive dissonance or the equivalent of the Mori Uncanny Valley. Scientists often react to these differences by claiming “incommensurability” between their restricted claim and the public’s understanding. Second order science, by explicating the effects of variations in values assumed for these uceps and associated impacts on related scientific claims, can often moot these assertions of incommensurability and thereby promote greater scientific understanding. This article explores how second order science can address issues of public doubt regarding the scientific enterprise using examples from medicine, diet and climate science. (shrink)

The purpose of this article is to invigorate debate concerning the nature of analogy, and to broaden the scope of current conceptions of analogy. We argue that analogizing is not a single or even a fundamental cognitive process. The argument relies on an analysis of the history of the concept of analogy, case studies on the use of analogy in scientific problem solving, cognitive research on analogy comprehension and problem solving, and a survey of computational mechanisms of analogy comprehension. Analogizing (...) is regarded as a macrocognitive phenomenon having a number of supporting processes. These include the apperception of resemblances and distinctions, metaphor, and the balancing of semantic flexibility and inference constraint. Psychological theories and computational models have generally relied on (a) a sparse set of ontological concepts (a property called “similarity” and a structuralist categorization of types of semantic relations), (b) a single form category (i.e., the classic four-term analogy), and (c) a single set of morphological distinctions (e.g., verbal vs. pictorial analogies). This article presents a classification based on a “naturalistic” exploration of the variety of uses of analogical reasoning in pragmatically distinct contexts. The resultant taxonomy distinguishes pre-hoc, ad-hoc, post-hoc, pro-hoc, contra-hoc, and trans-hoc analogy. Each will require its own macrocognitive modeling, and each presents an opportunity for research on phenomena of reasoning that have been neglected. (shrink)

The semantic, or model-theoretic, approach to theories has recently come under criticism on two fronts: (i) it is claimed that it cannot account for the wide diversity of models employed in scientific practice—a claim which has led some to propose a “deflationary” account of models; (ii) it is further contended that the sense of “model” used by the approach differs from that given in model theory. Our aim in the present work is to articulate a possible response to these claims, (...) drawing on recent developments within the semantic approach itself. Thus, the first is answered by utilizing the notion of a “partial structure”, first introduced in this context by da Costa and French in 1990. The second claim is undermined by consideration of van Fraassen's understanding of “model” which corresponds well with that evinced by modem mathematicians. This latter discussion, in particular, has an impact on the continuing debate regarding the relative merits of the semantic and syntactic views and the developments presented here can be taken to provide further support to the former. (shrink)

Ist der Unterschied zwischen wissenschaftlichen Gesetzen und Theorien ein qualitativer oder lediglich von quantitativer Art? Der Autor versucht zu zeigen, daß Gesetze und Theorien fundamental verschieden sind und daß die Kenntnis ihrer verschiedenen Natur notwendig für ein richtiges Wissenschaftsverständnis ist. Aus seiner Sicht sind Theorien geistige Konstruktionen mit dem Ziel, kausale Erklärungen von empirischen Gesetzen zu geben, während diese Gesetze auf der Grundlage von Messungen entdeckt werden und die Tatsachen der Wissenschaft konstituieren. Erkenntnistheoretisch sind daher Theorien und Gesetze auf verschiedenen (...) Ebenen anzusiedeln: während Gesetze Wissen liefern, liefern Theorien Verstehen. Der Kern der Theorien besteht aus Modellen, die idealisierte Abstraktionen aus Zustandsarten darstellen. Theoretische Modelle konstituieren Ontologien, die kausale Mechanismen aufzeigen. Solche Ontologien betreffen den Bedeutungsaspekt des Gegenstandsbereichs, auf den die Theorie angewendet wird, während empirische Gesetze den Ausdrucksaspekt des gleichen Gegenstandsbereichs betreffen. Theorien erklären Gesetze, indem sie zeigen, wie der Ausdrucksaspekt lediglich der natürliche Ausdruck der Auswirkungen der Kausalmechanismen in Bedeutungsaspekt sind. (shrink)

Scientific models represent aspects of the empirical world. I explore to what extent this representational relationship, given the specific properties of models, can be analysed in terms of propositions to which truth or falsity can be attributed. For example, models frequently entail false propositions despite the fact that they are intended to say something "truthful" about phenomena. I argue that the representational relationship is constituted by model users "agreeing" on the function of a model, on the fit with data and (...) on the aspects of a phenomenon that are modelled. Model users weigh the propositions entailed by a model and from this decide which of these propositions are crucial to the acceptance and continued use of the model. Thus, models represent phenomena when certain propositions they entail are true, but this alone does not exhaust the representational relationship. Therefore, the constraints that produce the choice of the relevant propositions in a model must also be examined and their analysis contributes to understanding the relationship between models and phenomena. (shrink)

: This paper contains the analysis of nine interviews with UK scientists on the topic of scientific models. Scientific models are an important, very controversially discussed topic in philosophy of science. A reasonable expectation is that philosophical conceptions of models ought to be in agreement with scientific practice. Questioning practicing scientists on their use of and views on models provides material against which philosophical positions can be measured.

: This paper gives a historical overview of the ways various trends in the philosophy of science dealt with models and their relationship with the topics of heuristics and theoretical dynamics. First of all, N. Campbell’s account of analogies as components of scientific theories is presented. Next, the notion of ‘model’ in the reconstruction of the structure of scientific theories proposed by logical empiricists is examined. This overview finishes with M. Hesse’s attempts to develop Campbell’s early ideas in terms of (...) an analogical inference. The final part of the paper points to contemporary developments on these issues which adopt a cognitivist perspective. It is indicated how discussions in the cognitive sciences might help to flesh out some of the insights philosophers of science had concerning the role models and analogies play in actual scientific theorizing. Key words: models, analogical reasoning, metaphors in science, the structure of scientific theories, theoretical dynamics, heuristics, scientific discovery. (shrink)

Two metascientific concepts that have been ― and still are ― object of philosophical analysis are the concepts of model and theory. But while the concept of scientific theory was one of the concepts to which philosophers of science devoted most attention during the 20th century, it is only in recent decades that the concept of scientific model has come to occupy a central position in philosophical reflection. However, it has done so in such a way that, at present, as (...) Jim Bogen states in the back cover of the book Scientific Models in the Philosophy of Science, by Daniela Bailer-Jones, “[t]he standard philosophical literature on the role of models in scientific reasoning is voluminous, disorganized, and confusing”. In spite of this, one of the axes that would allow us to organize at least part of this literature, and with which Bailer-Jones’ book closes, is that which is identified as one of the “contemporary philosophical issues: how theories and models relate to each other” (Bailer-Jones 2009, p. 208).That is why, in this introduction to the special issues of Metatheoria devoted to the topic of “Models and Theories in Biology”, we will present the main advances that have been made in the philosophical analysis of the concepts of model and theory in general and in biology in particular, and we will also do the same with the answers that have been given to the problem of "how theories and models relate to each other”. (shrink)