There are two traditions of thinking about idealization offering almost opposite views on their functioning and epistemic status. While one tradition views idealizations as epistemic deficiencies, the other one highlights the epistemic benefits of idealization. Both of these, however, identify idealization with misrepresentation. In this article, we instead approach idealization from the artifactual perspective, comparing it to the distortion-to-reality accounts of idealization, and exemplifying it through the case of the Hodgkin and Huxley model of nerve impulse. From the artifactual perspective, (...) the epistemic benefits and deficiencies introduced by idealization frequently come in a package due to the way idealization draws together different resources in model construction. Accordingly, idealization tends to be holistic in that it is not often easily attributable to just some specific parts of the model. Instead, the idealizing process tightly embeds theoretical concepts and formal tools into the construction of a model. (shrink)

The description of how individual models in families of models are related to each other is crucial for the general philosophical understanding of model-based scientific practice. We focus on the Capital Asset Pricing Models (CAPM) family, a cornerstone in financial economics, to provide a descriptive analysis of model relations within a family. We introduce the concepts of theoretical and empirical complementarity to characterise model relations. Our complementarity analysis of model relations has two types of payoff. Specifically regarding the CAPM, our (...) analysis reveals why this model family, which has been empirically contested, has yet remained popular and important: the different models that have been added over time have made new empirically and theoretically complementary contributions to the model family. More generally, our analysis reveals the dynamic character of model-based scientific practice. Characterising relations between models as theoretically and/or empirically complementary yields three hitherto underappreciated lessons: (i) actual modelling purposes are not always primarily epistemic, (ii) a model's individual import is relative, not absolute, and (iii) there is an important interplay between theory and data models. Faithfully characterising scientific modelling in this way facilitates subsequent analysis of models' epistemic import. (shrink)

We track and analyze the re-situation of scientific knowledge in the field of human population genomics ancestry studies. We understand re-situation as a process of accommodating the direct or indirect transfer of objects of knowledge from one site/situation to other sites/situations. Our take on the concept borrows from Mary S. Morgan’s work on facts traveling while expanding it to include other objects of knowledge such as models, data, software, findings, and visualizations. We structure a specific case study by tracking the (...) re-situation of these objects between three research projects studying human population diversity reported in three articles in Science, Genome Research and PLoS Genetics between 2002 and 2005. We characterize these three engagements as a unit of analysis, a “skirmish,” in order to compare: the divergence of interests in how life-scientists answer similar research questions and to track the challenging transformation of workflows in research laboratories as these scientific objects are re-situated individually or in bundles. Our analysis of the case study shows that an accurate understanding of re-situation requires tracking the whole bundle of objects in a project because they interact in particular key ways. The absence or dismissal of these interactions opens the door to unforeseen trade-offs, misunderstandings and misrepresentations about research design and workflow and what these say about the questions asked and the findings produced. (shrink)

This paper defends the viability of de-idealization strategies in economic modeling against recent criticism. De-idealization occurs when an idealized assumption of a theoretical model is replaced with a more realistic one. Recently, some scholars have raised objections against the possibility or fruitfulness of de-idealizing economic models, suggesting that economists do not employ this kind of strategy. We present a detailed case study from the theory of industrial organization, discussing three different models, two of which can be construed as de-idealized versions (...) of the first. We conclude that recent pessimism about de-idealization in economics is largely unfounded, and that de-idealization strategies are not only possible but also widely employed in economics. (shrink)

Idealization is commonly understood as distortion: representing things differently than how they actually are. In this paper, we outline an alternative artifactual approach that does not make misrepresentation central for the analysis of idealization. We examine the contrast between the Hodgkin-Huxley (1952a, b, c) and the Heimburg-Jackson (2005, 2006) models of the nerve impulse from the artifactual perspective, and argue that, since the two models draw upon different epistemic resources and research programs, it is often difficult to tell which features (...) of a system the central assumptions involved are supposed to distort. Many idealizations are holistic in nature. They cannot be locally undone without dismantling the model, as they occupy a central position in the entire research program. Nor is their holistic character mainly related to the use of mathematical and statistical modeling techniques as portrayed by Rice (2018, 2019). We suggest that holistic idealizations are implicit theoretical and representational assumptions that can only be understood in relation to the conceptual and representational tools exploited in modeling and experimental practices. Such holistic idealizations play a pivotal role not just in individual models, but also in defining research programs. -/- . (shrink)

Mathematical models and their modeling frameworks developed to advance knowledge in one discipline are sometimes sourced to answer questions or solve problems in another discipline. Studying this aspect of cross-disciplinary transfer of knowledge objects, philosophers of science have weighed in on the question of whether knowledge about how a mathematical model is previously applied in one discipline is necessary for the success of reapplying said model in a different discipline. However, not much has been said about whether the answer to (...) that epistemological question applies to the reapplication of a modeling framework. More generally, regarding the nature of the production of knowledge in science, a metaphysical question remains to be explored whether historical contingencies associated with a mathematical construct have a genuine impact on the nature—as opposed to sociological practices or individual psychology—of advancing scientific knowledge with said construct. Focusing on this metaphysical question, this paper analyzes the use of mathematical logic in the development of the Chomsky hierarchy and subsequent reapplications of said hierarchy; with these examples, this paper develops the notion of “spillovers” as a way to detect cross-disciplinary justifications for better understanding the relations between reapplications of the same mathematical construct across disciplines. (shrink)

The history of developmental biology is interwoven with debates as to whether mechanistic explanations of development are possible or whether alternative explanatory principles or even vital forces need to be assumed. In particular, the demonstrated ability of embryonic cells to tune their developmental fate precisely to their relative position and the overall size of the embryo was once thought to be inexplicable in mechanistic terms. Taking a causal perspective, this Element examines to what extent and how developmental biology, having turned (...) molecular about four decades ago, has been able to meet the vitalist challenge. It focuses not only on the nature of explanations but also on the usefulness of causal knowledge – including the knowledge of classical experimental embryology – for further scientific discovery. It also shows how this causal perspective allows us to understand the nature and significance of some key concepts, including organizer, signal and morphogen. This title is also available as Open Access on Cambridge Core. (shrink)

In this article we develop a pragmatist-inspired notion of intelligence that should lead to a better understanding of the notion of scientific expertise. The notion of intelligence is drawn from Dewey and is therefore used here in its technical sense. Our thesis is that scientific knowledge is a necessary but not sufficient condition for scientific expertise; intelligence should also be added. Conceived of as the capacity to apply general knowledge to particulars, we reach the conclusion that intelligence is a necessary (...) requirement for scientific experts in the wake of Dewey’s logic of inquiry. In particular, we argue that an all-important task that scientific experts are asked to accomplish, and which puts their expertise to the test, is to transform indeterminate situations into problematic situations, and that such a goal can only be achieved if scientific experts succeed in paying attention to all the contingent and precarious aspects that make the situation they face unique. (shrink)

This paper defends the viability of de-idealization strategies in economic modeling against recent criticism. De-idealization occurs when an idealized assumption of a theoretical model is replaced with a more realistic one. Recently, some scholars have raised objections against the possibility or fruitfulness of de-idealizing economic models, suggesting that economists do not employ this kind of strategy. We present a detailed case study from the theory of industrial organization, discussing three different models, two of which can be construed as de-idealized versions (...) of the first (the so-called Bertrand model of oligopoly). We conclude that recent pessimism about de-idealization in economics is largely unfounded, and that de-idealization strategies are not only possible but also widely employed in economics. (shrink)

This paper contributes to the philosophical accounts of generalisation in formal modelling by introducing a conceptual framework that allows for recognising generalisations that are epistemically beneficial in the sense of contributing to the truth of a model result or component. The framework is useful for modellers themselves because it is shown how to recognise different kinds of generalisation on the basis of changes in model descriptions. Since epistemically beneficial generalisations usually de-idealise the model, the paper proposes a reformulation of the (...) well-known distinction between abstraction and idealisation. A reformulated notion of abstraction is needed because the extant accounts yield wrong judgments when model-modifications introduce implicit assumptions. (shrink)