Robustness is a common platitude: hypotheses are better supported with evidence generated by multiple techniques that rely on different background assumptions. Robustness has been put to numerous epistemic tasks, including the demarcation of artifacts from real entities, countering the “experimenter’s regress,” and resolving evidential discordance. Despite the frequency of appeals to robustness, the notion itself has received scant critique. Arguments based on robustness can give incorrect conclusions. More worrying is that although robustness may be valuable in ideal evidential circumstances (i.e., (...) when evidence is concordant), often when a variety of evidence is available from multiple techniques, the evidence is discordant. †To contact the author, please write to: Jacob Stegenga, Department of Philosophy, University of California, San Diego, 9500 Gilman Drive, La Jolla, CA 92093; e‐mail: [email protected]. (shrink)

I describe two traditions of philosophical accounts of evidence: one characterizes the notion in terms of signs of success, the other characterizes the notion in terms of conditions of success. The best examples of the former rely on the probability calculus, and have the virtues of generality and theoretical simplicity. The best examples of the latter describe the features of evidence which scientists appeal to in practice, which include general features of methods, such as quality and relevance, and general features (...) of evidence, such as patterns in data, concordance with other evidence, and believability of the evidence. Two infamous episodes from biomedical research help to illustrate these features. Philosophical characterization of these latter features—conditions of success—has the virtue of potential relevance to, and descriptive accuracy of, practices of experimental scientists. (shrink)

This article examines a metaphilosophical issue, namely existing disagreements in philosophy of science about the significance of using multiple means of determination in scientific practice. We argue that this disagreement can, in part, be resolved by separating different questions that can be asked about the use of multiple means of determination, including the following: what can be concluded from the convergence of data or the convergence of claims about phenomena? Are the conclusions drawn from the convergence of data and of (...) statements about phenomena of special importance to the debate about realism and antirealism? Do inferences based on multiple means of determination have stronger epistemic force than inferences that are secured in other ways? Is the epistemic goal of deploying multiple means of determination well entrenched within the scientific community? Most of these questions can be discussed both in a formal and in an empirical perspective. If the differences in perspective are taken into account, some disagreements can be easily resolved. In part, however, the disagreements reflect historiographical challenges that are very difficult, if not impossible to meet. (shrink)

An analysis is presented of published methods that have been used by experimenters to justify the reliability of the theory of invasion of microorganisms into cultured cells. The results show that, to demonstrate this invasion, many experimenters used two or more methods that were based on independent technical and theoretical principles, and by doing so improved the reliability of the theory. Subsequently I compare this strategy of 'multiple derivability' with other strategies, discussed in the literature in relation to the mesosome, (...) a bacterial organelle that had been detected with the electron microsope, but which appeared later to be an artifact. I propose that different strategies have been applied in this problem, and multiple derivability may have been the decisive one. Finally I discuss the idea that multiple derivability may help to anchor theories in a larger network of theories. (shrink)

In 1966 the population biologist Richard Levins gave a forceful and in?uential defence of a method called “robustness analysis” (RA). RA is a way of assessing the result of a model by showing that different but related models give the same result. As Levins put it, “our truth is the intersection of independent lies” (1966, 423). Steven Orzack and Elliott Sober (1993) responded with an equally forceful critique of this method, concluding that the idea of robustness “lacks proper de?nition and (...) that its bearing on the question of whether a proposition is true is highly problematic” (533). Replies to Orzack and Sober, from Levins (1993) and Weisberg (2006b), have rejected the idea that RA, on its own, can con?rm the results of models. I argue that these replies have not properly addressed Orzack and Sober’s real criticisms, which focus not on the role of empirical data in RA but on the problem of ensuring that the models used in RA are independent. By drawing on accounts of RA in experimental science, I argue that there is in fact a fallible but viable form of RA that can both con?rm the results of models and incorporate empirical data. However, for reasons other than those of Orzack and Sober, I conclude that RA may be of limited use in model-based science, as the example of ?shery biology can show. (shrink)

This discussion centers on two desiderata: the role of measurement in information-gathering and physical interaction in scientific practice. By taking inspiration from van Fraassen’s view, we present a methodological account of perspectival measurement that addresses empirical practice where there is complex intervention, disagreeing results, and limited theory. The specific aim of our account is to provide a methodological prescription for developing measurement processes in the context of limited theory. The account should be useful to philosophers of science, who are interested (...) in the intersection between representation and intervention; scientists, who are interested in methodological suggestions for theory-development and reliability; and interdisciplinary researchers, who are interested in the intersections between the pandemic, built environments, and social processes. We apply the process-view of measurement to COVID-19, specifically, measuring replication in the SARS-CoV-2 virus. The aim is to show that our account tracks key elements—manipulation/intervention, independence, invariance, and theory-development—by organizing unfolding measurement processes. Additionally, we use our account to make prescriptive suggestions for measurement practice in the COVID-19 context by discussing the need to broaden measurement perspective on interaction, manipulation, and production. (shrink)

In experimental settings, scientists often “make” new things, in which case the aim is to intervene in order to produce experimental objects and processes—characterized as ‘effects’. In this discussion, I illuminate an important performative function in measurement and experimentation in general: intervention-based experimental production (IEP). I argue that even though the goal of IEP is the production of new effects, it can be informative for causal details in scientific representations. Specifically, IEP can be informative about causal relations in: regularities under (...) study; ‘intervention systems’, which are measurement/experimental systems; and new technological systems. (shrink)

In experimental settings, scientists often “make” new things, in which case the aim is to intervene in order to produce experimental objects and processes—characterized as ‘effects’. In this discussion, I illuminate an important performative function in measurement and experimentation in general: intervention-based experimental production. I argue that even though the goal of IEP is the production of new effects, it can be informative for causal details in scientific representations. Specifically, IEP can be informative about causal relations in: regularities under study; (...) ‘intervention systems’, which are measurement/experimental systems; and new technological systems. (shrink)

I argue for the possibility of historicized philosophy of science, and then respond to three criticisms of view: 1) history of science provides too few case examples to be useful to philosophy, 2) philosophy based on history is prone to reflexive inconsistency and 3) history of science exhibits an incoherent flux of methods.

My task in this paper is to defend the legitimacy of historicist philosophy of science, defined as the philosophic study of science that takes seriously case studies drawn from the practice of science. Historicistphilosophy of science suffers from what I call the ’evidence problem’. The worry is that case studies cannot qualify as rigorous evidence for the adjudication of philosophic theories. I explore the reasons why one might deny to historical cases a probative value, then reply to these reasons on (...) behalf of historicism. The main proponents of the view I am criticizing are Pitt (2001) and Rasmussen (2001). (shrink)

Throughout his career David Hull has sought to bring the philosophy of science into closer contact with science and especially with biological science (Hull 1969, 1997b). This effort has taken many forms. Sometimes it has meant ‘either explaining basic biology to philosophers or explaining basic philosophy to biologists’ (Hull 1996, p. 77). The first of these tasks, simple as it sounds, has been responsible for revolutionary changes. It is well known that traditional philosophy of science, modeled as it was on (...) theoretical physics, proved inadequate when philosophers turned their attention to biological science. Biological examples have driven major revisions of accounts of reduction (Hull 1974; Schaffner 1993, Ch. 9), laws of nature (Beatty et al. 1997), theories (Lloyd 1988) and natural kinds (Wilson 1999, Part III). Nor is explaining basic philosophy to biologists a task to be looked down upon. It is useful, not because philosophy has all the answers, but because scientists must think about how to do science, that is doing philosophy of science and scientists frequently reinvent philosophical views with known flaws. Early in his career Hull found biological systematists in the grip of a crude operationalism about scientific concepts and said so in the pages of Systematic Zoology (Hull 1968). For the next thirty years, as biologists debated the nature of species and the correct principles of classification, Hull added a philosophical note at the same congresses and in the same journals (Hull 1970, 1976, 1980, 1997a, 1999). (shrink)

Multiple determination is the epistemic strategy of establishing the same result by means of multiple, independent procedures. It is an important strategy praised by both philosophers of science and practicing scientists. Despite the heavy appeal to multiple determination, little analysis has been provided regarding the specific grounds upon which its epistemic virtues rest. This article distinguishes between the various dimensions of multiple determination and shows how they can be used to evaluate the epistemic force of the strategy in particular cases. (...) Distinguishing between the various dimensions helps to resolve the disagreements regarding the relevance and epistemic import of multiple determination for scientific research. It also suggests a fruitful mode of interaction between the philosophy of science and (historical) accounts of scientific practice. (shrink)