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Morgan’s original canon (1894) was intended as a prophylactic against an anthropomorphic bias that he thought stemmed from the double inductive method, which explains seemingly identical behavior in animals and humans in terms of the same underlying causes. However, his defense of the method of va...

In this paper, I introduce a novel approach to a problem that is, in the dominant literature, often thought to admit of only a partial solution. The problem of quantity is the problem of explaining why it is that certain properties and relations that we encounter in science and in everyday life, can...

Climate scientists frequently employ heavily idealized models. How should these models be interpreted? Some philosophers have promoted a possibilist interpretation, where climate models stand in for possible scenarios that could occur, but don't provide information about how probable those scenarios...

How should universities evaluate scientific research? This paper critically assesses the quantitative approach to the evaluation of scientific outputs based on publication metrics. First, I provide an overview of the standard indicators, such as Impact Factor and h-index. Secondly, I show that one l...

It is commonly believed that symmetry principles explain conservation laws. Since conservation laws can be mathematically derived from symmetries and vice versa, the explanatory asymmetry deserves philosophical justification. Marc Lange (2007) claims that symmetries are meta-laws that govern and hen...

The relationship between Indigenous knowledge and science is a topic of increasing global discussion, especially regarding climate and environmental sciences. A lot of this discussion has centred around comparing or contrasting the two on a range of counts, such as epistemic merit, methodological ov...

I draw attention to an under-theorized problem for the application of machine learning models in science, which I call semantic opacity. Semantic opacity occurs when the knowledge needed to translate the output of an unsupervised model into scientific concepts depends on theoretical assumptions abou...

The replication crisis describes an ongoing phenomenon, particularly in the social and medical sciences, in which there is a high frequency of unsuccessful replications which has been a cause of deep concern in the fields in question. But how did we get here? What exactly is at issue in this “cris...

Recent work in the metaphysics of race that’s focused on the nature and reality of race as understood in the dominant race talk of current American English speakers—hereafter US race talk—has produced three main categories of race theories. Biological anti-realists—like Appiah (1992), Blum (...

We discuss two different ways that the term “analog” (as opposed to “digital”) is used in the methodology of computer science and those engineering disciplines that are related to computer science. We show that formal models of computation on real numbers provide, indeed, an explication of w...

Causal models provide a promising framework for analyzing actual causation. Such analyses must include how a model should map onto the world. While universally endorsed that a model must be accurate – saying only true things – the implications of this aren’t explored. I argue that, surprisingl...

Shifts are a well-known feature of the literature on spacetime symmetries. Recently, discussions have focused on so-called dynamic shifts, which by analogy with static and kinematic shifts enact arbitrary linear accelerations of all matter (as well as a change in the gravitational potential). But in...

We examine arguments for and against the use of mechanistic evidence in assessing treatment efficacy and find that advocates of EBM+ and their critics have largely been talking past each other due to difference in focus. We explore aducanumab for the treatment of Alzheimer’s disease as a case whic...

We study the epistemic success of different data collection strategies. We develop a computational multi-agent model of the scientific process that jointly formalizes its core aspects: data collection, data explanation, and social learning. We find that agents who choose new experiments at random de...

Scientists have started to use algorithms to manufacture a consensus from divergent scientific judgments. One area in which this has been done is the interpretation of MRI images. This paper consists of a normative epistemic analysis of this new practice. It examines a case study from medical imagin...

Reciprocal causation is the view that adaptive evolution is a bidirectional process, whereby organisms and environments impinge on each other through cycles of niche construction and natural selection. I argue, however, that reciprocal causation is incompatible with the recent view that natural sele...

Breeds are classifications of domestic animals that share a set of conventional phenotypic traits. We claim that, despite classifying biological entities, animal breeds are social kinds. Breeds originate in a social mechanism (artificial selection) by which humans dominate the agency of certain anim...

The persistent pervasiveness of small studies in empirical fields is regularly deplored in scientific discussions. Taken individually, higher-powered studies are more likely to be truth-conducive. However, are they also beneficial for the wider performance of truth-seeking communities? We study the ...

A central problem for machine learning (ML) models is that they are “black boxes” and epistemically opaque. This means the inner workings of these models—how the model internally represents the data to reach a certain decision—are opaque or a “black box” to experts. This is concerning in...

Like Austin’s “performatives”, some models are used not merely to represent, but also to change their targets. This paper argues that Austin’s analysis can inform model evaluation: if models are evaluated with respect to whether they are adequate for particular purposes (Parker 2020), and if...

I argue that thinking with good reason that a hypothesis $H$ is the best available explanation for some phenomenon does not entail that we are justified in believing $H$. Thus, inference to the best explanation does not in general give us justified belief. My argument is distinct from the so-called ...