Scholars belong to multiple communities of credit simultaneously. When these communities disagree about a scholarly achievement’s credit assignment, this raises a puzzle for decision and game theoretic models of credit seeking in science. The reference class problem for credit valuation in science is the problem of determining to which of an agent’s communities—which reference class—credit determinations should be indexed for an act under some state of nature. Solving this problem requires developing rich, mutually informed theories of community and credit that are sensitive to the structure and status systems of complex, heterogeneous scholarly networks.

Mammals are usually considered unproblematic as biological individuals. This article contends the opposite. Once we consider pregnancy, criteria for biological individuality are not easily applicable in mammals and give conflicting results: mammalian pregnancy poses a problem for biological individuality. This may open fruitful new approaches to biological individuality and is of relevance to metaphysicians interested in (human) organisms.

Mammalian placental pregnancy is a neglected problem case for theories of organismality. This example is closer to home than those typically discussed within philosophy of biology. I apply evolutionary and immunological accounts of organismality to the “counting question”: How many organisms are present during a placental pregnancy? I conclude that an evolutionary approach yields the answer two, because of bottlenecking, germ-soma sequestration, and sexual recombination. By contrast, an immunological approach answers one, because of pervasive interactions across the placenta. This analysis expands and refines recent work on a biologically informed metaphysics of pregnancy, an undertheorized area of philosophy of science.

Philosophical discussions of information and specificity in biology are now commonplace, but no consensus exists about whether the privileging of genetic causation in investigation and explanation is justified. However, little effort has been expended on understanding practices when scientists experimentally measure information or causal specificity. An example of this type of practice—measuring positional information in gene expression during pattern formation in embryogenesis—shows that biologists are unconcerned with comparing the amount of information in genes with that of other factors. Instead, they focus on whether the measured causal specificity explains the phenomenon under scrutiny.

Genome-wide association studies (GWAS) of human complex traits have provided us with new estimates of heritability. These estimates foreground the question of genetic causation. After having presented in simple terms the rationale underlying this way of estimating heritability, I assess the extent to which relationships between genes and phenotypes established with GWAS satisfy several dimensions of causal relationships—namely, range of influence, specificity, and stability—distinguished within the interventionist account of causation. The upshot is that if these relationships are causal in some sense, my analysis shows the extent to which they do not represent paradigmatic causal relationships.

We address Turkheimer’s argument that genome-wide association studies of behaviors and psychiatric traits will fail to produce coherent explanations. We distinguish two major sources of potential incoherence (heterogeneity and complexity), showing how they independently threaten coherence and considering how they are being and might better be addressed with protein and other databases and network tools.

Biologists have proposed a variety of explanations for extravagant sexual displays, and controversies over explanations define the history of sexual selection research. Recently, Richard Prum has defended Darwin’s idea that the evolution of sexual displays is driven by arbitrary and nonadaptive preferences of potential mates. Prum argues that this explanation should be the null model for sexual selection research. I show that if we adopted Prum’s proposal, the inferences we could be justified in making are more modest than he claims. I also discuss problems with estimating model parameters that at present prevent his proposal from being useful in practice.

I examine the use of the term function in Aldo Leopold’s land ethic, invoked as (1) the healthy functioning of the land community, which is dependent on (2) the maintenance of the characteristic functions of populations that are parts of the land community. The latter can be understood as referring to interactions between species that are the products of coevolution (such as parasite-host, predator-prey) and, thus, in terms of the “selected effect” account of function. The performance of these functions under certain conditions maintain what Leopold took to be the healthy functioning of a land community.

What meaning does epidemiological evidence have for the individual? In evidence-based medicine, epidemiological evidence measures the patient’s risk of the outcome or the change in risk due to an intervention. The patient’s risk is commonly understood as an individual probability. The problem of understanding epidemiological evidence and risk thus becomes the challenge of interpreting individual patient probabilities. I argue that the patient’s risk is interpreted ontically, as a propensity. After exploring formidable problems with this interpretation in the medical context, I propose an epistemic reinterpretation of individual patient probabilities as credences. On this view, epidemiological evidence informs medical uncertainty.

The idea that remembering involves an engram, becoming stable and permanent via consolidation, has guided the neuroscience of memory since its inception. The shift to thinking of memory as continuous and dynamic, as part of a trend toward neural dynamics, has challenged this commitment, with some, such as Lynn Nadel, calling for “the demise of the fixed trace” and others, such as Alcino J. Silva, urging rejection of the “consolidation dogma.” Does consideration of neural dynamics offer reasons to reject engram theory? No. I argue that they are compatible. At most, shifting to a dynamic view of neural processes compels revision of the implementational details.

Some realistic models of neural spiking take into account spike timing, yet the practical relevance of spike timing is often unclear. In Eugene Izhikevich’s model, timing plays a crucial role by allowing for the natural formation of polychronous circuits. In such circuits, individual elements may figure in a number of distinct assemblies, their role in each determined by their timing relative to other neurons. I show that this reflects a distinct organizational principle from notions of pluripotency, redundancy, or reuse and argue that properly understanding this phenomenon requires a shift to a time-sensitive, process-based view of computation.

In human conscious experience, many features are present in combination: objects are presented through the senses, information from different sensory modalities is integrated, events are marked with value, and we have a sense of our own location and state. Which of these might come before others in plausible evolutionary trajectories, or do they form a tight package of correlated features that cannot readily be dissociated? I take a comparative approach to these questions, focusing on a distinction between sensory and evaluative aspects of experience and looking at the distribution of subjectivity-relevant features in a range of invertebrate animals.

Memes have been proposed to explain wide swathes of human culture and language use. I argue that what is really doing the explanatory work in many of these cases is a basic mechanism of information transmission, which is distinct from memetic evolution by natural selection in significant ways. Perhaps the most significant of these is that information transmission depends primarily on the interests of the users of information, rather than the reproductive interests of the informational entities—‘memes’—themselves. Although my main target is memetic approaches, this argument also applies to some other, nonmemetic, theories of cultural evolution.

In this article I bring the recent philosophical literature on theoretical equivalence to bear on dualities in physics. Focusing on electromagnetic duality, which is a simple example of S-duality in string theory, I show that the duality fits naturally into at least one framework for assessing equivalence—that of categorical equivalence—but that it fails to meet a necessary condition for equivalence on that account. The reason is that the duality does not preserve “empirical content” in the required sense; instead, it takes models to models with “dual” empirical content. I conclude by discussing how one might react to this.

It has been suggested that we can tell whether two theories are equivalent by comparing the structure that they ascribe to the world. If two theories posit different structures, then they must be inequivalent. The aim of this article is to evaluate the extent to which this desideratum holds for the different standards of equivalence that are currently on the table.

The Cold Dark Matter model faces many controversies at small scales, as simulations fail to reproduce the observed properties of dark matter (DM) halos. Since rival DM models differ on their predictions about the structure of DM halos, understanding their mass distribution is crucial for determining the nature of DM. However, only numerical approaches to determining what a hypothesis implies for the mass distribution are possible. Hence, simulations are a crucial part of evaluating DM rival models, as is assessing their reliability. I argue that robustness analysis is not a sufficient criterion for the trustworthiness of cosmological simulations.

Astrophysics faces methodological challenges as a result of being a predominantly observation-based science without access to traditional experiments. In light of these challenges, astrophysicists frequently rely on computer simulations. Using collisional ring galaxies as a case study, I argue that computer simulations play three roles in reasoning in astrophysics: (1) hypothesis testing, (2) exploring possibility space, and (3) amplifying observations.

Computer simulations of the formation and evolution of large-scale structure in the universe are integral to the enterprise of modern cosmology. Establishing the reliability of these simulations has been extremely challenging, primarily because of epistemic opacity. In this setting, robustness analysis defined by requiring converging outputs from a diverse ensemble of simulations is insufficient to determine simulation validity. We propose an alternative path of structured code validation that applies eliminative reasoning to isolate and reduce possible sources of error, a potential path that is already being explored by some cosmologists.

Signature-based model-independent (SBMI) searches for new physics form an explorative component of High Energy Physics experiments that aims at avoiding biases toward beyond-the-standard-model theories. In order to maximize their chances of meeting their objectives, however, SBMI searches must be guided by theory about the target phenomena. They correspond to strategy-driven experiments as defined by Koray Karaca, in contrast to Friedrich Steinle’s conception of explorative experiments. A concept of type II safeness is proposed to explain how the objectives of the experiment introduce theory dependence in the search strategy. Empirical evidence obtained from Large Hadron Collider experiments can therefore not avoid dependence on theory.

Since the discovery of the Higgs boson in 2012, particle physicists have not found any statistically significant deviations from the Standard Model. This has led to a shift of emphasis from model testing to exploration and an increasing popularity of ‘model-independent’ experimental approaches. Our goal is to analyze this shift by focusing on particle and event signatures. A differentiated picture of experimentation emerges between the extremes of theory guidance and theory-free exploration. Using the example of the top quark, we distinguish four types of motivations for the study of physics processes.