This paper defends a version of J. H. Randall’s thesis that modern empiricism is rooted in the Scholastic regressus method epitomized by Jacopo Zabarella in De Regressu (1578). Randall’s critics note that the empirical practice of Galileo and his contemporaries does not follow Zabarella. However, Zabarella’s account of the regressus is imprecise, which permitted an interpretation introducing empirical hypothesis testing into the framework. The discourse surrounding Galileo’s lunar observations in Sidereus Nuncius (1610) suggests that both Galileo and his interlocutors amended the regressus method in this way, such that a developmental narrative links Scholastic logic to Galilean science.

In this paper we examine the use of companion animals (pets) in studies of drugs and devices aimed at human and animal health and situate it within the context of philosophy of technology. We argue that companion animals serve a unique role in illuminating just what it means to use biological technologies and examine the implications for human-animal relationships. Though philosophers have often treated animals as technologies, we argue that the biomedical use of companion animals presents a new configuration of ethical and technological concerns that deserves more attention. Though it seems that companion animals solve many of the ethical dilemmas caused by the use of laboratory animals, the use of companion animals presents its own set of ethical concerns. This paper contextualizes the use of companion animals in research.

In a recent article in this journal—“Who’s Afraid of Dissent?”—Immaculada de Melo-Martín and Kristen Intemann argue that “targeting” dissent about science that is perceived to be problematic is both misguided and dangerous. I contend that their argument is unsuccessful. I present the Probability Argument to demonstrate that, in some circumstances, targeting problematic dissent will be a sound and reasonable response. Moreover, because not targeting dissent can also be misguided and dangerous, and because there are risks associated with leaning too heavily on education as a solution, it will sometimes be the case that targeting dissent is the best all-things-considered option. I sketch what is required for a more nuanced and contextual approach to evaluating and responding to dissent.

The scientific concepts of mental imagery and hallucinations are each used independently of the other in experiments; uses that simultaneously evoke and obscure their historical connections. To highlight one of these connections, I will begin by sketching episodes from the largely separate developmental trajectories of each concept. Considering these historical sketches side-by-side, I will argue that the independent uses of these concepts each inherited a shared set of interdependent associations. In doing so, I seek to illustrate the value of examining historical connections between mental imagery and hallucinations for studying the current uses of these two concepts in neuroimaging experiments.

After World War II, quite a few mathematicians were attracted to the modeling of phase transitions as this area of physics was seeing considerable mathematical difficulties. This paper studies their contributions to the physics of phase transitions, and in particular those of the by far most productive and successful of them, the Polish-American mathematician Mark Kac (1914–1984). The focus is on the resources, values, and traditions that the mathematicians brought with them and how these differed from those of contemporary physicists as well as the mathematicians’ relations with the physicists in terms of collaboration and reception of results.

Although in the sixteenth century some pharmacological powers were widely ascribed to celestial influences, alternative views of the nature of such powers began to be developed: Reductionism, according to which all pharmacological powers could be understood as combinations of the powers of elementary qualities, and emergentism, according to which some pharmacological powers are irreducible to combinations of the powers of elementary but arise out of their combination and interaction. The former view can be traced in the work of Francisco Valles (1524–1592) and Thomas Erastus (1524–1583), the latter view in the work of Girolamo Mercuriale (1530–1606) and Jacob Schegk (1511–1587).

A paradigm instructs in how to do research successfully. Analytic philosophy of science, currently dominant, models paradigmatic rational science as a system of logical inferences. It is, however, an abundantly inadequate paradigm. This paper presents an alternative paradigm: science as an organized collection of problem solving processes. This position is backed, on the one side, by a cognitive model of problem solving process applicable to all problem solving circumstances and, on the other, by a non-formal conception of rationality that provides a wider enriched notion of rational research process than is available to the analytic paradigm. The result is a very different way of looking at science and of doing history and philosophy of science. The position is developed sufficiently to display its nature and merits.

Early microbiome research found numerous associations between microbial community patterns and host physiological states. These findings hinted at community-level explanations. “Top-down” experiments, working with whole communities, strengthened these explanatory expectations. Now, “bottom-up” mechanism-seeking approaches are dissecting communities to focus on specific microbes carrying out particular biochemical activities (e.g., choline metabolism pathways, Clostridium difficile suppression). To understand the interplay between methodological and explanatory scales, we examine claims of “dysbiosis,” when host illness is proposed as the consequence of a community state. Our analysis concludes with general observations about how methodologies relate to explanations, and the implications for microbiome research.

Computer simulations are often expected to provide explanations about target phenomena. However there is a gap between the simulation outputs and the underlying model, which prevents users finding the relevant explanatory components within the model. I contend that visual representations which adequately display the simulation outputs can nevertheless be used to get explanations. In order to do so, I elaborate on the way graphs and pictures can help one to explain the behavior of a flow past a cylinder. I then specify the reasons that make more generally visual representations particularly suitable for explanatory tasks in a computer-assisted context.

This article expands upon the argument of a previous work which defended a variational account of scientific fictions. Specifically, I show that this understanding of scientific fictions can provide guidance for realist interpretations of scientific theories and models. Depending on a model’s variational properties, different ontological commitments are appropriate, providing a principled way for a realist to moderate her views according to the structural properties of a given model. This reasoning is then applied the Lee-Yang theory and Kubo-Martin-Schwinger statistics, two foundational models in quantum statistical mechanics. The Lee-Yang theory is analyzed in a way that permits a robust realist interpretation, whereas KMS statistics is shown to involve a use of fictions that shields the theory from confirmation and makes it inappropriate for strongly realist interpretation, without contradicting broadly realist commitments.

With the marginalization of cybernetics, efforts to develop a universal epistemological method ceased as well. But the question remains open as to whether cybernetics contributed to the reconceptualization of the model and the popularity of scientific modeling since the mid-twentieth century. The present study approaches this question using the example of the general model theory of the German cyberneticist Herbert Stachowiak. Although this theory failed to produce a unifying and common model concept, its characteristics point toward a change in epistemological positions that is important for today’s scientific practice and also anticipated recent developments in the philosophy of science.

This paper is intended as a contribution to the longstanding debate 1 about how to understand Kant’s appeal to pure intuition in his philosophical account of geometry. It proceeds by focusing on a notion that has been at the center of this debate, namely, the “construction” or “exhibition” of a concept in intuition. I claim that not only does Kant appeal to this notion in two different ways—in support of both an epistemological and a semantic thesis, each based in his broader philosophical project—but also that the demands placed on this notion by these appeals are in conflict. The tension between the epistemological and semantic appeals to construction-in-intuition can be clearly seen in geometrical proofs that proceed by reductio ad absurdum 2 . I conclude by considering the prospects for resolving this tension in a manner consistent with Kant’s broader philosophical ambitions.

Philosophers and scientists often cite ontic factors when explaining the methods and success of scientific inquiry. That is, the adoption of a method or approach (and its subsequent success or otherwise) is explained in reference to the kind of system in which the scientist is interested: these are explanations of why scientists do what they do, that appeal to properties of their target systems. We present a framework for understanding such “ Opticks to his Principia . Newton’s optical work is largely experiment-driven, while the Principia is primarily mathematical, so usually, each work is taken to exemplify a different kind of science. However, Newton himself often presented them in terms of a largely consistent method. We use our framework to articulate an original and plausible position: that the differences between the Opticks and the Principia are due to the kinds of systems targeted. That is, we provide an ontic-driven explanation of methodological differences. We suspect that ontic factors should have a more prominent role in historical explanations of scientific method and development.

The pipe organ presented early modern science with a pneumatic black box of suggestive dimensions: while producing musical pitches and intervals that corresponded with those of an acoustic device like the monochord, pipe dimensions approached, but yet confounded clear association with the behavior of strings. Nevertheless, investigators like Vincenzo Galilei (c.1520–1591) and Marin Mersenne (1588–1648) continued to rely conceptually upon the monochord and the traditional ratios associated with it in their attempts to discipline the complex variables attending the acoustic properties of pipes. Thus, while certain conventions of historiography associate Vincenzo and Mersenne with a “disenchantment” of Pythagorean traditions that ostensibly retarded the development of an early modern physico-mathematics, their ratios of pipe scaling reveal instead a robust and evolving contribution of Pythagoreanism to mathematical reading of the Book of Nature.

The first manuscript of The Structure of Scientific Revolutions , probably written in late 1958, is available in the Kuhn Archive at MIT (Massachusetts Institute of Technology) 1 . It is the first version of Chapter 1, which is the introduction to the book, and is completely different from the version that was published. In this article, I turn to the manuscript to show that at that time Kuhn considered the comparison between the image of science and the image of art as the most appropriate way to announce his project: to change the image of science by bringing it closer to the image of art. As I try to demonstrate, this appeal to the history of art is not merely occasional. And it allows us to understand Kuhn’s intriguing retrospective statement, according to which Structure was a belated product of his discovery of the parallels between science and art. Some passages from Kuhn’s unpublished manuscript are transcribed in the article.

This study examines how working scientists themselves understand, conceptualize, apply, and communicate norms and standards for good research practice. Drawing on semi-structured, detailed narrative interviews with more than 80 scientists, we highlight various topics of concern, including tensions between methodological requirements for good research practice and individual career goals, uncertainty about how exactly certain acknowledged methodological imperatives—such as replication—should be interpreted and turned into practice and the delegation of the responsibilty for ensuring good practice.

Bacon discussed three different types of laws of nature: (1) particular laws governing one element or phenomenon (such as the law of the gravity of water); (2) the laws of the multiplication of species; and, (3) the universal law of nature. Each set of laws has its own explanatory function: (1) the particular laws account for the unique features of individuals and species; (2) the laws of multiplication explain the common features of matter and how individuals affect one another physically; and (3) the law of universal nature regulates these interactions and keep them in balance. Bacon’s laws share common features with early modern conception of laws. For example, they can be restated as if/then sentences and cover future events; some support counterfactuals; and all are endowed with explanatory power and free from space-time limitations. When considered together, they form a system, ordered in hierarchical relations. The different levels of laws cover three aspects of Aristotelian causality: formal, efficient, and final. The law of universal nature is a metaphysical axiom, necessary for upholding the very idea of a nature governed by laws. This indicates that Bacon conceived of nature as orderly and predictable; he presented a conception of a lawful nature and showed an understanding of what it takes to be lawful to a degree that had not been seen before.

Drawing on fourteen months of ethnographic work, we analyze three population-making technologies ( denuncias , biobanks, and bodies) that have emerged as dominant tools both on the part of governments and human rights advocates to capture the missing migrants. We conclude that missing migrants are a Population of Cognition that is both made legible and unknowable through specific technologies and delineations of crisis.

The process by which scientists adopt and use socially constructed categories to classify their human subjects is complex. Scientists have used a wide variety of seemingly incongruous racial, ethnic, geographic, linguistic and national categories in their studies of human biological variation. This article details the epistemic rationale behind the system of classification found in mid-twentieth century human biology. The populationist rationale, I argue, entails agnosticism towards the reality of categories and supported the use of flexible standards around sampling and labeling. Looking closely at the categories used in projects in Latin America illustrates how the distinction between “primitive” and “industrialized” structured the classification system used by researchers to render populations productive.

This article analyzes the role of fertility surveyors as framing specialists, who in the 1940s portrayed Latin American populations as likely to change their attitudes regarding birth control. A heterogeneous group of social scientists, clinical workers, and their financial supporters, all of whom were interested in population limitation and women’s health issues, were involved in the deployment of the fertility survey, a tool that played an essential role justifying the promotion of birth control methods and population limitation policies. This group also included locals who became involved in research alongside US experts, albeit as unequal partners.