Kevin Elliott and others separate two common arguments for the legitimacy of societal values in scientific reasoning as the gap and the error arguments (respectively, the arguments from underdetermination and from inductive risk). This article poses two questions: How are these two arguments related, and what can we learn from their interrelation? I contend that we can better understand the error argument as nested within the gap because the error is a limited case of the gap with narrower features. Furthermore, this nestedness provides philosophers with conceptual tools for analyzing more robustly how values pervade science.

With the ever-growing quality of observational data in astronomy, the complexity of astrophysical models has been increasing in turn. This trend raises the question: Are there still reasons to prefer simpler models if the final goal is an actual model-target comparison? I argue for two aspects in which astrophysical research may favor models having reduced complexity: first, to address the problem of determining the values of adjustable parameters and, second, to pave the way for a validation of the model based on the modeler’s understanding of the scope of the model and the critical processes on the target’s side.

The distribution of matter in our universe is strikingly time asymmetric. Most famously, the Second Law of Thermodynamics says that entropy tends to increase toward the future but not toward the past. But what explains this time-asymmetric distribution of matter? In this article, I explore the idea that time itself has a direction by drawing from recent work on grounding and metaphysical fundamentality. I will argue that positing such a direction of time, in addition to time-asymmetric boundary conditions (such as the so-called past hypothesis), enables a better explanation of the thermodynamic asymmetry than is available otherwise.

Inmaculada de Melo-Martín and Kristen Intemann consider whether, from the perspective of the argument from inductive risk, ethical and political values might be logically, epistemically, pragmatically, or ethically necessary in the “core” of scientific reasoning. In each case, they argue that there are significant conceptual problems. In this comment, employing regulatory uses of high-throughput toxicology at the US Environmental Protection Agency as a case study, I respond to some of their claims about the notion of “pragmatic necessity.” I conclude that, while an inductive risk framework has some significant limitations, it is still conceptually and rhetorically valuable.

Ecological communities are seldom, if ever, biological individuals. They lack causal boundaries as the populations that constitute communities are not congruent and rarely have persistent functional roles regulating the communities’ higher-level properties. Instead we should represent ecological communities indexically, by identifying ecological communities via the network of weak causal interactions between populations that unfurl from a starting set of populations. This precisification of ecological communities helps identify how community properties remain invariant, and why they have robust characteristics. This respects the diversity and aggregational nature of these complex systems while still vindicating them as units worthy of investigation.

Modularity is a key concept in building and evaluating complex simulation models. My main claim is that in simulation modeling modularity tends to degenerate for reasons inherent to simulation methodology. The argument will proceed by analyzing the techniques of parameterization, tuning, and kludging. They are—to a certain extent—inevitable when building complex simulation models but erode modularity. As a result, the common account of validating simulations faces a major problem, namely, a problem of holism. In the conclusion, I will ask to what extent holism sets limits to validation.

A standard requirement on natural kinds is that they be mind independent. However, many kinds in the human and social sciences, even the natural sciences, depend on human thought. This article suggests that the mind independence requirement on natural kinds be replaced with the requirement that natural kind classifications be defeasible. The defeasibility requirement does not require that natural kinds be mind independent, so it does not exclude mind dependent scientific kinds from being natural kinds. Furthermore, the defeasibility requirement captures the idea that natural kind classifications are tools for investigating the empirical world.

In recent years, industry-funded research has come under fire because of concerns that it can be biased in favor of the funders. This article suggests that efforts by philosophers of science to analyze the concept of objectivity can provide important lessons for those seeking to evaluate and improve industry-funded research. It identifies three particularly relevant criteria for objectivity: transparency, reproducibility, and effective criticism. On closer examination, the criteria of transparency and reproducibility turn out to have significant limitations in this context, but the criterion of effective criticism suggests some important strategies for improving the objectivity of industry-funded science.

“Female sexual dysfunction” is the type of contested disease that has sparked concern about the role of the pharmaceutical industry in medical science. Many policies have been proposed to manage industry influence without carefully evaluating whether the proposed policies would be successful. We consider a proposal for incorporating citizen stakeholders into scientific research and show, via a detailed case study of the pharmaceutical regulation of flibanserin (misleadingly marketed as the “female Viagra”), that such programs can be co-opted. In closing, we use Holman’s asymmetric arms race framework as a tool for evaluating policies in industry-funded science.