Microbes,mathematics, and models

Microbial model systems have a long history of fruitful use in fields that include evolution and ecology. In order to develop further insight into modelling practice, we examine how the competitive exclusion and coexistence of competing species have been modelled mathematically and materially over the course of a long research history. In particular, we investigate how microbial models of these dynamics interact with mathematical or computational models of the same phenomena. Our cases illuminate the ways in which microbial systems and equations work as models, and what happens when they generate inconsistent findings about shared targets. We reveal an iterative strategy of comparative modelling in different media, and suggest reasons why microbial models have a special degree of epistemic tractability in multimodel inquiry.     

Local reduction in physics

A conventional wisdom about the progress of physics holds that successive theories wholly encompass the domains of their predecessors through a process that is often called “reduction.” While certain influential accounts of inter-theory reduction in physics take reduction to require a single “global” derivation of one theory׳s laws from those of another, I show that global reductions are not available in all cases where the conventional wisdom requires reduction to hold. However, I argue that a weaker “local” form of reduction, which defines reduction between theories in terms of a more fundamental notion of reduction between models of a single fixed system, is available in such cases and moreover suffices to uphold the conventional wisdom. To illustrate the sort of fixed-system, inter-model reduction that grounds inter-theoretic reduction on this picture, I specialize to a particular class of cases in which both models are dynamical systems. I show that reduction in these cases is underwritten by a mathematical relationship that follows a certain liberalized construal of Nagel/Schaffner reduction, and support this claim with several examples. Moreover, I show that this broadly Nagelian analysis of inter-model reduction encompasses several cases that are sometimes cited as instances of the “physicist׳s” limit-based notion of reduction.     

Inconsistent idealizations and inferentialism about scientific representation

Inferentialists about scientific representation hold that an apparatus's representing a target system consists in the apparatus allowing “surrogative inferences” about the target. I argue that a serious problem for inferentialism arises from the fact that many scientific theories and models contain internal inconsistencies. Inferentialism, left unamended, implies that inconsistent scientific models have unlimited representational power, since an inconsistency permits any conclusion to be inferred. I consider a number of ways that inferentialists can respond to this challenge before suggesting my own solution. I develop an analogy to exploitable glitches in a game. Even though inconsistent representational apparatuses may in some sense allow for contradictions to be generated within them, doing so violates the intended function of the apparatus's parts and hence violates representational “gameplay”.     

A structural interpretation of measurement and some related epistemological issues

Measurement is widely applied because its results are assumed to be more reliable than opinions and guesses, but this reliability is sometimes justified in a stereotyped way. After a critical analysis of such stereotypes, a structural characterization of measurement is proposed, as partly empirical and partly theoretical process, by showing that it is in fact the structure of the process that guarantees the reliability of its results. On this basis the role and the structure of background knowledge in measurement and the justification of the conditions of object-relatedness (“objectivity”) and subject-independence (“intersubjectivity”) of measurement are specifically discussed.     

普通物理双语教学模型探索

本文阐明了对普通物理实施双语教学的重要性。对普通物理双语教学过程中各个环节进行了探索和实践,期望进一步推进我院双语教学的步伐和改善双语教学模式。     

Accountability and values in radically collaborative research

This paper discusses a crisis of accountability that arises when scientific collaborations are massively epistemically distributed. We argue that social models of epistemic collaboration, which are social analogs to what Patrick Suppes called a “model of the experiment,” must play a role in creating accountability in these contexts. We also argue that these social models must accommodate the fact that the various agents in a collaborative project often have ineliminable, messy, and conflicting interests and values; any story about accountability in a massively distributed collaboration must therefore involve models of such interests and values and their methodological and epistemic effects.     

Models, scientific realism, the intelligibility of nature, and their cultural significance

In this article, I will view realist and non-realist accounts of scientific models within the larger context of the cultural significance of scientific knowledge. I begin by looking at the historical context and origins of the problem of scientific realism, and claim that it is originally of cultural and not only philosophical, significance. The cultural significance of debates on the epistemological status of scientific models is then related to the question of ‘intelligibility’ and how science, through models, can give us knowledge of the world by presenting us with an ‘intelligible account/picture of the world’, thus fulfilling its cultural-epistemic role. Realists typically assert that science can perform this role, while non-realists deny this. The various strategies adopted by realists and non-realists in making good their respective claims, is then traced to their cultural motivations. Finally I discuss the cultural implications of adopting realist or non-realist views of models through a discussion of the views of Rorty, Gellner, Van Fraassen and Clifford Hooker on the cultural significance of scientific knowledge.     

Representing with imaginary models: Formats matter

Models such as the simple pendulum, isolated populations, and perfectly rational agents, play a central role in theorising. It is now widely acknowledged that a study of scientific representation should focus on the role of such imaginary entities in scientists’ reasoning. However, the question is most of the time cast as follows: How can fictional or abstract entities represent the phenomena? In this paper, I show that this question is not well posed. First, I clarify the notion of representation, and I emphasise the importance of what I call the “format” of a representation for the inferences agents can draw from it. Then, I show that the very same model can be presented under different formats, which do not enable scientists to perform the same inferences. Assuming that the main function of a representation is to allow one to draw predictions and explanations of the phenomena by reasoning with it, I conclude that imaginary models in abstracto are not used as representations: scientists always reason with formatted representations. Therefore, the problem of scientific representation does not lie in the relationship of imaginary entities with real systems. One should rather focus on the variety of the formats that are used in scientific practice.     

Models as products of interdisciplinary exchange: Evidence from evolutionary game theory

The development of evolutionary game theory (EGT) is closely linked with two interdisciplinary exchanges: the import of game theory into biology, and the import of biologists’ version of game theory into economics. This paper traces the history of these two import episodes. In each case the investigation covers what exactly was imported, what the motives for the import were, how the imported elements were put to use, and how they related to existing practices in the respective disciplines. Two conclusions emerged from this study. First, concepts derived from the unity of science discussion or the unification accounts of explanation are too strong and too narrow to be useful for analysing these interdisciplinary exchanges. Secondly, biology and economics—at least in relation to EGT—show significant differences in modelling practices: biologists seek to link EGT models to concrete empirical situations, whereas economists pursue conceptual exploration and possible explanation.