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Estimating whether the Earth’s biota is in the middle of a crisis relies heavily on comparisons between present and past data about biodiversity or biodiversity surrogates. Although the past is a crucial source of information to assess the severity of the current biodiversity crisis, substantive conceptual and methodological questions remain about how paleodiversity and biodiversity are to be properly compared. I argue that to justify claims of a current biodiversity crisis is harder than it appears. More precisely, I claim that paleodiversity measurements are incommensurable with contemporary measurements, given the different ways that biodiversity is conceptualized and operationalized. I conclude by proposing three possible ways of overcoming this incommensurability problem. [ABSTRACT FROM AUTHOR]

Hasok Chang is developing a new form of pragmatic scientific realism that aims to reorient the debate away from truth and towards practice. Central to his project is replacing truth as correspondence with his new notion of 'operational coherence', which is introduced as: 1) A success term with probative value to judge and guide epistemic activities. 2) A more useful alternative than truth as correspondence in guiding scientific practice. I argue that, given its current construal as neither necessary nor sufficient for success, operational coherence is too weak and fails to satisfy both 1) and 2). I offer a stronger construal of operational coherence which aims to improve on Chang's account by tying it to systematic success. This makes operational coherence necessary and sufficient for (systematic) success. This new account, if successful, rescues 1) but not 2). I then take a step back and try to locate Chang's pragmatic realism within the broader pragmatist tradition by comparing his views to the founding fathers Peirce, James and Dewey. I also assess to what extent we should consider Chang's position 'realist', arguing that despite the many relativists threads running through it, Chang's pragmatic realism is deserving of the realist label because its aims to maximize our learning from reality, even if it falls short of what many traditional realist are happy to accept as realism. I finish with comments on the epistemology of science pointing out that there is nothing intrinsic about a practice-based philosophy of science that precludes having both operational coherence and correspondence and highlighting that given a proper understanding these two notions could, in fact, be understood as complementary. I suggest one way this could be done. [ABSTRACT FROM AUTHOR]

In this paper, I investigate how researchers evaluate their characterizations of scientific phenomena. Characterizing phenomena is an important – albeit often overlooked – aspect of scientific research, as phenomena are targets of explanation and theorization. As a result, there is a lacuna in the literature regarding how researchers determine whether their characterization of a target phenomenon is appropriate for their aims. This issue has become apparent for accounts of scientific explanation that take phenomena to be explananda. In particular, philosophers who endorse mechanistic explanation suggest that the discovery of the mechanisms that explain a phenomenon can lead to its recharacterization. However, they fail to make clear how these explanations provide warrant for recharacterizing their explananda phenomena. Drawing from cases of neurobiological research on potentiation phenomena, I argue that attempting to explain a phenomenon may provide reason to suspend judgment about its characterization, but this cannot provide warrant to recharacterize it if researchers cannot infer a phenomenon's characteristics from this explanation. To explicate this, I go beyond explanation – mechanistic or otherwise – to analyze why and how researchers change their epistemic commitments in light of new evidence. [ABSTRACT FROM AUTHOR]

We introduce a novel point of view on the 'models as mediators' framework in order to emphasize certain important epistemological questions about models in science which have so far been little investigated. To illustrate how this perspective can help answer these kinds of questions, we explore the use of simplified models in high energy physics research beyond the Standard Model. We show in detail how the construction of simplified models is grounded in the need to mitigate pressing epistemic problems concerning the uncertainty inherent in the present theoretical and experimental contexts. [ABSTRACT FROM AUTHOR]