Inner speech, natural language, and the modularity of the mind

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Models in Search of Targets: Exploratory Modelling and the Case of Turing Patterns

Traditional frameworks for evaluating scientific models have tended to downplay their exploratory function; instead they emphasize how models are inherently intended for specific phenomena and are to be judged by their ability to predict, reproduce, or explain empirical observations. By contrast, this paper argues that exploration should stand alongside explanation, prediction, and representation as a core function of scientific models. Thus, models often serve as starting points for future inquiry, as proofs of principle, as sources of potential explanations, and as a tool for reassessing the suitability of the target system (and sometimes of whole research agendas). This is illustrated by a case study of the varied career of reaction-diffusion models in the study of biological pattern formation, which was initiated by Alan Turing in a classic 1952 paper. Initially regarded as mathematically elegant, but biologically irrelevant, demonstrations of how, in principle, spontaneous pattern formation could occur in an organism, such Turing models have only recently rebounded, thanks to advances in experimental techniques and computational methods. The long-delayed vindication of Turing’s initial model, it is argued, is best explained by recognizing it as an exploratory tool (rather than as a purported representation of an actual target system)

Symbol Systems as Collective Representational Resources: Mary Hesse, Nelson Goodman, and the Problem of Scientific Representation

This short paper grew out of an observation—made in the course of a larger research project—of a surprising convergence between, on the one hand, certain themes in the work of Mary Hesse and Nelson Goodman in the 1950/60s and, on the other hand, recent work on the representational resources of science, in particular regarding model-based representation. The convergence between these more recent accounts of representation in science and the earlier proposals by Hesse and Goodman consists in the recognition that, in order to secure successful representation in science, collective representational resources must be available. Such resources may take the form of (amongst others) mathematical formalisms, diagrammatic methods, notational rules, or—in the case of material models—conventions regarding the use and manipulation of the constituent parts. More often than not, an abstract characterization of such resources tells only half the story, as they are constituted equally by the pattern of (practical and theoretical) activities—such as instances of manipulation or inference—of the researchers who deploy them. In other words, representational resources need to be sustained by a social practice; this is what renders them collective representational resources in the first place

Cultures of Modelling: Rudolf Peierls on ‘Model-Making in Physics’

The philosophical debate about scientific models has, over the past thirty years or so, reached a high degree of sophistication. Yet, in spite of efforts to seek common ground with scientific practice, there remains the suspicion that philosophical accounts are sometimes too ‘free-floating’, in that they do not adequately reflect scientists’ views (and actual uses) of models. The present paper deals with one such scientific perspective, due to physicist Sir Rudolf Peierls (1907-1995). Writing thoroughly from the perspective of a theoretician with a deep appreciation for experimental physics, Peierls, in a series of papers, developed a taxonomy of scientific models, which – in spite of some inevitable arbitrariness – exhibits surprising points of convergence with contemporary philosophical accounts of how scientific models function. The present paper situates Peierls’s approach within the philosophical and scientific developments of his time, engages (in an immersive way) with his proposed taxonomy, and argues that Peierls’s views – and others like them – warrant the recent philosophical shift from a focus on model-based representation to non-representational (e.g., exploratory) uses and functions of models

Styles of Reasoning in Biology: The Case of Models in Membrane and Cell Biology

This paper investigates one of the great achievements of twentiethcentury cell biology: determining the structure of the cell membrane. This case differs in important ways from the better-known case of the identification of the DNA double helix as the carrier of genetic information, especially regarding the evaluation of potential evidence in light of prior theoretical commitments. Whereas it has been argued that adherence to a structural hypothesis enabled Watson and Crick to ignore a surplus of (potentially confusing) empirical findings, similar adherence to an elegant and universal structural hypothesis, we argue, unduly shielded the so-called ‘unit-membrane’ model from legitimate challenges on the basis of known phenomena

The Exploratory Role of Idealizations and Limiting Cases in Models

In this article we argue that idealizations and limiting cases in models play an exploratory role in science. Four senses of exploration are presented: exploration of the structure and representational capacities of theory; proof-of-principle demonstrations; potential explanations; and exploring the suitability of target systems. We illustrate our claims through three case studies, including the Aharonov-Bohm effect, the emergence of anyons and fractional quantum statistics, and the Hubbard model of the Mott phase transitions. We end by reflecting on how our case studies and claims compare to accounts of idealization in the philosophy of science literature such as Michael Weisberg’s three-fold taxonomy

The Exploratory Role of Idealizations and Limiting Cases in Models

In this article we argue that idealizations and limiting cases in models play an exploratory role in science. Four senses of exploration are presented: exploration of the structure and representational capacities of theory; proof-of-principle demonstrations; potential explanations; and exploring the suitability of target systems. We illustrate our claims through three case studies, including the Aharonov-Bohm effect, the emergence of anyons and fractional quantum statistics, and the Hubbard model of the Mott phase transition. We end by reflecting on how our case studies and claims compare to accounts of idealization in the philosophy of science literature such as Michael Weisberg’s three-fold taxonomy

Der wissenschaftliche Wille zur Wahrheit: Rezension zu "Epistemische Tugenden: Zur Geschichte und Gegenwart eines Konzepts" von Andreas Gelhard, Ruben Hackler und Sandro Zanetti (Hg.)

Andreas Gelhard, Ruben Hackler, Sandro Zanetti (Hrsg.): Epistemische Tugenden - Zur Geschichte und Gegenwart eines Konzepts. Historische Wissensforschung, Bd. 11. Tübingen: Mohr Siebeck 2019. 978-3-16-154072-