skip to content

Department of History and Philosophy of Science


CamPoS (Cambridge Philosophy of Science) is a network of academics and students working in the philosophy of science in various parts of the University of Cambridge, including the Department of History and Philosophy of Science and the Faculty of Philosophy. The Wednesday afternoon seminar series features current research by CamPoS members as well as visitors to Cambridge and scholars based in nearby institutions. In the 2022–23 year, CamPoS is being organised by Jacob Stegenga (HPS) and Neil Dewar (Philosophy).

Seminars are held on Wednesdays, 1.00–2.30pm in Seminar Room 2.

Easter Term 2023

26 April

Michael Townsen Hicks (University of Birmingham)
Laws unconstrained: against minimal primitivism about laws of nature

Recently a number of authors (Adlam (2022), Chen and Goldstein (2022), building on the views of Mauldin (2007) and Schaffer (2016)) have argued that laws of nature should be seen as primitive modal constraints on physical reality. The idea is that laws are primitives which make some things necessary, and we as philosophers should refrain from speculating more deeply about their nature. We should, nonetheless, speculate enough to deny both Humean attempts to reduce laws to non-modal facts and Dispositionalist attempts to reduce global laws to locally instantiated modal properties. The view aims to retain the explanatory power of governing laws while divorcing them from any connections to dodgy metaphysics of properties or time which might not be supported by future (or current) physics.

In this talk, I argue that this primitive proposal faces numerous difficulties. By rejecting any account of the structure of laws, the view makes it harder to see how laws play their distinctive roles in explanation and induction. By combining a metaphysically necessary connection between laws and their instances with a strident quietism about the nature of laws, the view makes metaphysical necessity even harder to understand. I conclude with some quite general remarks on the viability of primitivist or purely structuralist views of laws of nature and nomological modality.

3 May

Thomas Pradeu (CNRS)
Can present-day philosophers make scientific contributions? From philosophy in science to conceptual and theoretical thinking in science

Despite the widespread idea of a growing divorce between philosophy and science during the 20th and 21st centuries, there have been many calls recently for a reconnection between them. There are in fact many ways through which philosophy can impact science. In this talk, I focus on one peculiar and often overlooked impact of philosophy on science: some philosophers use philosophical tools to produce science (Laplane et al., PNAS, 2019). Such use of philosophical tools to attempt to make scientific contributions is what I have called 'philosophy in science'. In recent work, we have shown that philosophy in science is a relatively small but clearly identifiable trend in recent philosophy of science, characterized by its specific methodologies, authors, and problems (Pradeu et al., BJPS, forthcoming). 'Philosophy in science' is not just scientifically informed philosophy of science. It is related to complementary science (Chang 1999, 2004) and philosophy of science in practice, although it is distinct from them. In this talk, I will offer a detailed examination of what philosophy in science is, and assess its impact on science. Finally, I will show that philosophy in science is better understood as part of a wider phenomenon, namely conceptual and theoretical thinking in science, done by philosophers and scientists alike.

10 May

Nick Huggett (University of Illinois Chicago)
Ways of branchmaking

I will use a simple model to explore the way in which 'branches' form and propagate locally by decoherence in quantum mechanics, aiming to clarify some of the puzzles people have had about the version of the Everrett interpretation explicated by David Wallace. My focus is on understand branches as physical (not purely formal) structures, but I will remain neutral on the further question of whether they really constitute distinct 'worlds'. (Based on joint work with Nadia Blackshaw and James Ladyman.)

17 May

Shaun Nichols (Cornell University)
Not for me: on the external function of guilt

The standard way of thinking about emotions in cognitive science starts with their function. The function of the fear program, for instance, is to help the individual evade imminent dangers. This functionalist proposal illuminates the character of the fear program, e.g., the kinds of things that elicit fear, and the kinds of responses that fear produces. The functionalist approach has been extremely productive, but it faces a puzzle with the emotion of guilt, for it's unclear what function the guilt program serves for the individual. As Deem & Ramsey put it: 'It seems that it is good for you that others are guilt-prone..., it is less clear that being guilt-prone is good for the individuals themselves' (2016, 571). Extant functionalist attempts to solve this puzzle (e.g., Frank 1988) have important shortcomings. To resolve the puzzle, we argue that the functional approach has been overly restrictive. Some cognitive systems need to be understood in terms of the functions those systems serve, not for the individual himself, but for others. That is, some cognitive systems have functions that are external to the individual. Just as the function of an artifact needs to be understood in terms of the interests of the artisan, so too the function of some cognitive systems needs to be understood in terms of the interests of those (e.g., parents, partners, or teachers) who crafted or shaped the cognitive system. This provides an alternative way of thinking about the function of the guilt program. On the external approach, we need to consider the function of guilt from the perspective of those who installed or edited the guilt program in the individual. From that perspective, it's plausible that a primary function of the guilt program is precisely to protect the individual(s) who stand to be harmed by the agent's action.

24 May

Stephan Hartmann (MCMP, LMU Munich)
Bayesian explanationism

Peter Lipton famously argued that we want our scientific theories to be lovely and likely, that is, we want them to provide good explanations and to be very probable (if not true). Unfortunately, there is a tension between these two epistemic virtues, and it is not clear how they are related. Thus, the question arises whether the Bayesian (who prefers likely theories) and the explanationist (who prefers lovely theories) can be friends, as Lipton claims. Although much ink has been spilled over this question, in this talk I want to take a fresh look at it and make two points: First, I argue that successfully providing an explanation is an example of non-empirical evidence in favor of the theory in question. This point can be made more precise by a simple Bayesian model, which also provides (as a bonus point, so to speak) a justification for the bonus point approach to explanationism inspired by van Fraassen and championed by Douven – at least if certain conditions are met. Second, I investigate how the strength of an explanation – its explanatory power – can be measured in Bayesian terms, and show how this all fits nicely into a coherentist epistemology of science.

31 May

Caspar Jacobs (Merton College, Oxford)
In defence of dimensions

The distinction between dimensions and units in physics is commonplace. But what are dimensions? The most popular view is that they are no more than a tool for keeping track of the values of quantities under a change of units. This 'anti-realist' view is supported by an argument from underdetermination: one can assign dimensions to quantities in many different ways, all of them empirically equivalent. In contrast, I argue that dimensions are real, so there are knowable matters of fact about a quantity's dimensions. The argument I provide is a form of inference to the best explanation. In particular, the technique of dimensional analysis is explanatory, but it only works if we assume that the relevant quantities have certain dimensions. Since these dimensions support explanations, we have reason to believe that they are real.