Many realist writings exemplify the spirit of ‘recipe realism’. Here I characterise recipe realism, challenge it, and propose replacing it with ‘exemplar realism’. This alternative understanding of realism is more piecemeal, robust, and better in tune with scientists’ own attitude towards their best theories, and thus to be preferred.

Debunking arguments aim to undermine common sense beliefs by showing that they are not explanatorily or causally linked to the entities they are purportedly about. Rarely are facts about the aetiology of common sense beliefs invoked for the opposite aim, that is, to support the reality of entities that furnish our manifest image of the world. Here I undertake this sort of un-debunking project. My focus is on the metaphysics of ordinary physical objects. I use the view of perception as (...) approximate Bayesian inference to show how representations of ordinary objects can be extracted from sensory input in a rational and truth-tracking manner. Drawing an analogy between perception construed as Bayesian hypothesis testing and scientific inquiry, I sketch out how some of the intuitions that traditionally inspired arguments for scientific realism also find application with regards to proverbial tables and chairs. (shrink)

The geosciences include a wide spectrum of disciplines ranging from paleontology to climate science, and involve studies of a vast range of spatial and temporal scales, from the deep-time history of microbial life to the future of a system no less immense and complex than the entire Earth. Modeling is thus a central and indispensable tool across the geosciences. Here, we review both the history and current state of model-based inquiry in the geosciences. Research in these fields makes use of (...) a wide variety of models, such as conceptual, physical, and numerical models, and more specifically cellular automata, artificial neural networks, agent-based models, coupled models, and hierarchical models. We note the increasing demands to incorporate biological and social systems into geoscience modeling, challenging the traditional boundaries of these fields. Understanding and articulating the many different sources of scientific uncertainty – and finding tools and methods to address them – has been at the forefront of most research in geoscience modeling. We discuss not only structuralmodel uncertainties, parameter uncertainties, and solution uncertainties, but also the diverse sources of uncertainty arising from the complex nature of geoscience systems themselves. Without an examination of the geosciences, our philosophies of science and our understanding of the nature of model-based science are incomplete. (shrink)

Derived measurements involve problems of coordination. Conducting them often requires detailed theoretical assumptions about their target, while such assumptions can lack sources of evidence that are independent from these very measurements. In this paper, I defend two claims about problems of coordination. I motivate both by a novel case study on a central measurement problem in the history of physical geodesy: the determination of the earth's ellipticity. First, I argue that the severity of problems of coordination varies according to scientists' (...) predictive and experimental control over perturbations of the measurement process. Second, I identify a methodology by which scientists can solve hard problems of coordination and gradually increase their predictive control over perturbations. I dub this methodology ‘operational pluralism’ since it is driven by the introduction of alternative measurement operations that involve different physical indicators. (shrink)

Observational discrepancies in galactic rotation curves and cluster dispersion data have been interpreted to imply the existence of dark matter. Numerous efforts at its detection, however, have failed to turn up any positive result. As a dynamical theory is always operative on the assumed mass distribution to predict kinematic observations, some scientists see the discrepancy as telling against General Relativity. Among the many theories that seek to modify gravity, those that are built on Modified Newtonian Dynamics (MOND), or yield MOND (...) behaviour at appropriate scales, achieve remarkable empirical success without assuming dark matter. The continued non-detection of dark matter and the empirical success of MOND supports the claim that the current evidential and theoretical context underdetermines General Relativity. In this article, I clarify the kind of underdetermination that can be said to threaten General Relativity. Specifically, I argue that the present evidential and theoretical context increase the possibility of an unconceived alternative to GR which would be just as well supported by the available evidence. (shrink)

This paper revisits the bearing of underdetermination arguments on scientific realism. First it argues that underdetermination considerations provide good reason to doubt that science is objective in the strong sense that anyone following the its methods will be led closer and closer to the truth about any given question within the purview of those methods, as more relevant data are considered. Then it argues that scientific realism is difficult to maintain in the absence of this sort of objectivity.

I offer an explicit account of the underdetermination thesis as well as of the many challenges it poses to scientific realism; a way to answer to these challenges is explored and outlined, by shifting attention to the content of theories. I argue that, even if we have solid grounds (as I contend we do) to support that some varieties of the underdetermination thesis are true, scientific realism can still offer an adequate picture of the aims and achievements of science.

Este artigo mostra que não há uma tese de subdeterminação de teorias científicas pelos indícios observacionais, mas várias. Identificamos quatro, com significados, plausibilidades e implicações distintos. Mostra-se que as mais fortes não passam de conjeturas, e que as mais fracas são mais plausíveis, mas não possuem implicações filosóficas robustas – em particular, não implicam o antirrealismo científico –, embora forneçam indícios de alternativas teóricas sistematicamente ignoradas na ciência, bem como do emprego de critérios em parte valorativos de escolha de teorias.