Scientists have used models for hundreds of years as a means of describing phenomena and as a basis for further analogy. In Scientific Models in Philosophy of Science, Daniela Bailer-Jones assembles an original and comprehensive philosophical analysis of how models have been used and interpreted in both historical and contemporary contexts. Bailer-Jones delineates the many forms models can take (ranging from equations to animals; from physical objects to theoretical constructs), and how they are put to use. She examines early mechanical (...) models employed by nineteenth-century physicists such as Kelvin and Maxwell, describes their roots in the mathematical principles of Newton and others, and compares them to contemporary mechanistic approaches. Bailer-Jones then views the use of analogy in the late nineteenth century as a means of understanding models and to link different branches of science. She reveals how analogies can also be models themselves, or can help to create them. The first half of the twentieth century saw little mention of models in the literature of logical empiricism. Focusing primarily on theory, logical empiricists believed that models were of temporary importance, flawed, and awaiting correction. The later contesting of logical empiricism, particularly the hypothetico-deductive account of theories, by philosophers such as Mary Hesse, sparked a renewed interest in the importance of models during the 1950s that continues to this day. Bailer-Jones analyzes subsequent propositions of: models as metaphors; Kuhn's concept of a paradigm; the Semantic View of theories; and the case study approaches of Cartwright and Morrison, among others. She then engages current debates on topics such as phenomena versus data, the distinctions between models and theories, the concepts of representation and realism, and the discerning of falsities in models. (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 examines the process of modelling a complex empirical phenomenon in modern astrophysics: extended extragalactic radio sources. I show that modelling is done piecemeal, addressing selected striking or puzzling features of that phenomenon separately and individually. The result is various independent and separate sub-models concerned only with limited aspects of the same phenomenon. Because the sub-models represent features of the same physical phenomenon, they need to be reasonably consistent with each other - a criterion not always fully adhered to (...) - and there needs to be a way to conceptually `re-unite' the sub-models to form an overall-model. Visualisation, that is, supplying a concrete interpretation of abstract, theoretical sub-models, aids this modelling process. My case study further endorses the view that modelling is `work in progress', i.e. a form of developing knowledge whereby models represent, not replicate, a phenomenon. (shrink)

Der Begriff ‘Modell’ leitet sich vom Lateinischen ‘modulus’ (das Maß) ab, im Italienischen existiert seit dem 16. Jh. ‘modello’ und R. Descartes verwendet im 17. Jh. ‘modèlle’. Während der Begriff in Architektur und Kunst schon seit der Renaissance gängig ist, wird er in den Naturwissenschaften erst im 19. Jh. verwendet.1 Dort greifen wissenschaftliche Modelle die für eine gegebene Problemstellung als wesentlich erachteten Charakteristika (Eigenschaften, Beziehungen, etc.) eines Untersuchungsgegenstandes heraus und machen diesen so einem Verständnis bzw. einer weiterführenden Untersuchung zugänglich. Es (...) ist üblich, zwischen Skalenmodellen, Analogmodellen und theoretischen Modellen zu unterscheiden. (shrink)

Kausales Denken spielt sowohl im Alltag wie auch im wissenschaftlichen Forschungsprozess eine zentrale Rolle. Es erlaubt uns, Phänomene vorherzusagen, zu kontrollieren und zu verstehen. Kausales Denken geht über die Angabe der Ursachen eines Phänomens hinaus: Wollen wir verstehen, warum ein Fahrrad fährt, so versuchen wir, Schritt für Schritt nachzuvollziehen, wie die einzelnen Bestandteile des Fahrrads zusammenwirken, um miteinander die Bewegung zu produzieren. Wir sind an dem Mechanismus interessiert, durch den das Phänomen zustande kommt. Dieses Vorgehen wird in der Wissenschaftsphilosophie wie (...) auch in der Kognitionspsychologie mit Hilfe mechanistischer Theorien kausalen Denkens beschrieben. Der Sammelband bringt erstmals Vertreter beider Disziplinen in sechs aufeinander abgestimmten Beiträgen zusammen. Neben einer Diskussion der Kernmerkmale mechanistischen Denkens stehen insbesondere Fragen nach dem Erwerb mechanistischer Denkstrukturen und nach der Rolle von Handlungen und Handlungserfahrungen im Fokus. (shrink)

In the first half of the 20th century, scientific models were hardly mentioned in philosophy of science. Models were not thought to be central elements of science, in contrast to theories. This attitude can be better understood when considering philosophical trends - Operationalism and Logical Empiricism - and scientific developments - the advent of quantum theory and relativity theory. This paper traces the philosophical currents and positions that prevented models from being recognized as playing an important role in science. It (...) goes on to examine why the hostile attitude towards models slowly tempered in the 1950s. The contributions of Mary Hesse and Ernest Hutten are shown to foreshadow recent debates that have arisen in the context of the philosophical study of scientific models. /// Segundo a autora, na primeira metade do século XX, os modelos científicos praticamente não eram mencionados em Filosofia da Ciência. Os modelos não eram considerados como elementos centrais da Ciência, ao contrário das teorias. Para a autora, uma tal atitude pode ser melhor compreendida se se atender ao influxo de importantes movimentos filosóficos, como sejam o Operacionalismo e o Empirismo Lógico, bem como ao impacto de alguns desenvolvimentos científicos, como sejam o aparecimento da teoria quântica e da teoria da relatividade. Nesse sentido, o presente artigo visa estabelecer as correntes filosóficas e as posições científicas que contribuíram para que os modelos não fossem reconhecidos no importante papel que desempenham no desenvolvimento da Ciência. De um modo especial, a autora examina com particular cuidado o lento processo de redução da hostilidade em relação aos modelos durante a década de 50 do século xx. Assim, o artigo mostra de um modo especial até que ponto os contributos de Mary Hesse e de Ernest Hutten foram antecipadores de alguns dos debates mais recentes que se sucederam no contexto do estudo filosófico dos modelos científicos. (shrink)