This dissertation draws upon historical studies of scientific practice and contemporary issues in the metaphysics and epistemology of science to account for the nature of physical quantities. My dissertation applies this integrated HPS approach to dimensional analysis—a logic for quantitative physical equations which respects the distinct dimensions of quantities (e.g. mass, length, charge). Dimensional analysis and its historical development serve both as subjects of study and as a sources for solutions to contemporary problems. The dissertation consists primarily of three related (...) papers on: (1) the methodological and metaphysical foundations of dimensional analysis, (2) the use of dimensional analysis in determining physical symmetries, (3) the use of dimensional analysis in securing metrological extension. (shrink)

Arguments for the effectiveness, and even the indispensability, of mathematics in scientific explanation rely on the claim that mathematics is an effective or even a necessary component in successful scientific predictions and explanations. Well-known accounts of successful mathematical explanation in physical science appeals to scientists’ ability to solve equations directly in key domains. But there are spectacular physical theories, including general relativity and fluid dynamics, in which the equations of the theory cannot be solved directly in target domains, and yet (...) scientists and mathematicians do effective work there (McLarty 2023, Elder 2023). Building on extant accounts of structural scientific explanation (Bokulich 2011, Leng 2021), I argue that philosophical accounts of the role of equations in scientific explanation need not rely on scientists’ ability to solve equations independently of their understanding of the empirical or experimental context. For instance, the process of formulating solutions to equations can involve significant appeal to information about experimental contexts (Curiel 2010) or of physically similar systems (Sterrett 2023). Working from a close analysis of work in fluid mechanics by Martin Bazant and Keith Moffatt (2005), I propose an account of heuristic structural explanation in mathematics (Einstein 1921, Pincock 2021), which explains how physical explanations can be constructed even in domains where basic equations cannot be solved directly. (shrink)

This chapter explores the relevance of empirical evidence to real causes. I argue for the claim that instrumentally mediated empirical results are causally dependent on unobservable entities. I develop this idea in the context of discussions on entity realism. As a consequence of my argument, an antirealist version of empiricism, which underlines the significance of empirical evidence but which abstains from real causation, is incoherent.

This paper draws on the phenomenological-hermeneutical approaches to philosophy of science to develop realist perspectivism, an integration of experimental realism and perspectivism. Specifically, the paper employs the distinction between “manifestation” and “phenomenon” and it advances the view that the evidence of a real entity is “explorable” in order to argue that instrumentally-mediated robust evidence indicates real entities. Furthermore, it underpins the phenomenological notion of the horizonal nature of scientific observation with perspectivism, so accounting for scientific pluralism even in the cases (...) of inconsistent models. Overall, realist perspectivism is proposed as the way to go for (phenomenologically-hermeneutically minded) philosophers of science. (shrink)

This dissertation is about human knowledge of reality. In particular, it argues that scientific knowledge is bounded by historically available instruments and theories; nevertheless, the use of several independent instruments and theories can provide access to the persistent potentialities of reality. The replicability of scientific observations and experiments allows us to obtain explorable evidence of robust entities and properties. The dissertation includes seven chapters. It also studies three cases – namely, Higgs bosons and hypothetical Ϝ-particles (section 2.4), the Ptolemaic and (...) Kepler model of the planets (section 6.7), and the special theory of relativity (chapter 7). -/- Chapter 1 is the introduction of the dissertation. Chapter 2 clarifies the notion of the real on the basis of two concepts: persistence and resistance. These concepts enable me to explain my ontological belief in the real potentialities of human-independent things and the implications of this view for the perceptual and epistemological levels of discussion. On the basis of the concept of “overlapping perspectives”, chapter 3 argues that entity realism and perspectivism are complementary. That is, an entity that manifests itself through several experimental/observational methods is something real, but our knowledge of its nature is perspectival. Critically studying the recent views of entity realism, chapter 4 extends the discussion of entity realism and provides a criterion for the reality of property tokens. Chapter 5, in contrast, develops the perspectival aspects of my view on the basis of the phenomenological-hermeneutical approaches to the philosophy of science. This chapter also elaborates my view of empirical evidence, as briefly expressed in sections 2.5 and 4.5. Chapter 6 concerns diachronic theoretical perspectives. It first explains my view of progress, according to which current perspectives are broader than past ones. Second, it argues that the successful explanations and predictions of abandoned theories can be accounted for from our currently acceptable perspectives. The case study of Ptolemaic astronomy supports the argument of this chapter. Chapter 7 serves as the conclusion of the dissertation by applying the central themes of the previous chapters to the case study of special relativity theory. I interpret frame-dependent properties, such as length and time duration, and the constancy of the speed of light according to realist perspectivism. (shrink)

Proponents of ontic conceptions of explanation require all explanations to be backed by causal, constitutive, or similar relations. Among their justifications is that only ontic conceptions can do justice to the ‘directionality’ of explanation, i.e., the requirement that if X explains Y , then not-Y does not explain not-X . Using topological explanations as an illustration, we argue that non-ontic conceptions of explanation have ample resources for securing the directionality of explanations. The different ways in which neuroscientists rely on multiplexes (...) involving both functional and anatomical connectivity in their topological explanations vividly illustrate why ontic considerations are frequently (if not always) irrelevant to explanatory directionality. Therefore, directionality poses no problem to non-ontic conceptions of explanation. (shrink)

We argue that the main results of scientific papers may appropriately be published even if they are false, unjustified, and not believed to be true or justified by their author. To defend this claim we draw upon the literature studying the norms of assertion, and consider how they would apply if one attempted to hold claims made in scientific papers to their strictures, as assertions and discovery claims in scientific papers seem naturally analogous. We first use a case study of (...) William H. Bragg’s early 20th century work in physics to demonstrate that successful science has in fact violated these norms. We then argue that features of the social epistemic arrangement of science which are necessary for its long run success require that we do not hold claims of scientific results to their standards. We end by making a suggestion about the norms that it would be appropriate to hold scientific claims to, along with an explanation of why the social epistemology of science—considered as an instance of collective inquiry—would require such apparently lax norms for claims to be put forward. (shrink)

Scientific results are often presented as ‘surprising’ as if that is a good thing. Is it? And if so, why? What is the value of surprise in science? Discussions of surprise in science have been limited, but surprise has been used as a way of defending the epistemic privilege of experiments over simulations. The argument is that while experiments can ‘confound’, simulations can merely surprise (Morgan, 2005). Our aim in this paper is to show that the discussion of surprise can (...) be usefully extended to thought experiments and theoretical derivations. We argue that in focusing on these features of scientific practice, we can see that the surprise-confoundment distinction does not fully capture surprise in science. We set out how thought experiments and theoretical derivations can bring about surprises that can be disruptive in a productive way, and we end by exploring how this links with their future fertility. (shrink)

Debate about the epistemic prowess of historical science has focused on local underdetermination problems generated by a lack of historical data; the prevalence of information loss over geological time, and the capacities of scientists to mitigate it. Drawing on Leonelli’s recent distinction between ‘phenomena-time’ and ‘data-time’ I argue that factors like data generation, curation and management significantly complexifies and undermines this: underdetermination is a bad way of framing the challenges historical scientists face. In doing so, I identify circumstances of epistemic (...) scarcity where underdetermination problems are particularly salient, and discuss cases where legacy data—data generated using differing technologies and systems of practice—are drawn upon to overcome underdetermination. This suggests that one source of overcoming underdetermination is our knowledge of science’s past. Further, data-time makes agnostic positions about the epistemic fortunes of scientists working under epistemic scarcity more plausible. But agnosticism seems to leave philosophers without much normative grip. So, I sketch an alternative approach: focusing on the strategies scientists adopt to maximize their epistemic power in light of the resources available to them. (shrink)

We critically engage two traditional views of scientific data and outline a novel philosophical view that we call the pragmatic-representational view of data. On the PR view, data are representations that are the product of a process of inquiry, and they should be evaluated in terms of their adequacy or fitness for particular purposes. Some important implications of the PR view for data assessment, related to misrepresentation, context-sensitivity, and complementary use, are highlighted. The PR view provides insight into the common (...) but little-discussed practices of iteratively reusing and repurposing data, which result in many datasets’ having a phylogeny—an origin and complex evolutionary history—that is relevant to their evaluation and future use. We relate these insights to the open-data and data-rescue movements, and highlight several future avenues of research that build on the PR view of data. (shrink)

In 2012, the Geological Time Scale, which sets the temporal framework for studying the timing and tempo of all major geological, biological, and climatic events in Earth’s history, had one-quarter of its boundaries moved in a widespread revision of radiometric dates. The philosophy of metrology helps us understand this episode, and it, in turn, elucidates the notions of calibration, coherence, and consilience. I argue that coherence testing is a distinct activity preceding calibration and consilience, and I highlight the value of (...) discordant evidence and trade-offs scientists face in calibration. The iterative nature of calibration, moreover, raises the problem of legacy data. (shrink)

Scientists obtain a great deal of the evidence they use by observingnatural and experimentally generated objects and effects. Much of thestandard philosophical literature on this subject comes from20th century logical positivists and empiricists, theirfollowers, and critics who embraced their issues and accepted some oftheir assumptions even as they objected to specific views. Theirdiscussions of observational evidence tend to focus on epistemologicalquestions about its role in theory testing. This entry follows theirlead even though observational evidence also plays important andphilosophically interesting roles (...) in other areas including scientificdiscovery and the application of scientific theories to practicalproblems. (shrink)

What is possible, according to the empiricist conception, is what our evidence positively allows; and what is necessary is what it compels. These notions, along with logical possibility, are the only defensible notions of possibility and necessity. In so far as nomic and metaphysical possibilities are defensible, they fall within empirical possibility. These empirical conceptions are incompatible with traditional possible world semantics. Empirically necessary propositions cannot be defined as those true in all possible worlds. There can be empirical possibilities without (...) empirical necessities. The duality of possibility and necessity can be degenerate and can even be falsified. (shrink)

In this paper the truth is studied in the frame of autonomous systems theory. The method of the truth verification is worked out in its functional aspect. The verification is based on comparison of the predicted inner state of the autonomous agent, that is the cognitive subject, to the achieved inner state of the agent. The state is achieved as the result of performing the action in the real world—the agent’s environment. The action design is created on the basis of (...) the agent’s model of the world. The truth is defined as the adequacy of the model of the real world in the context of the goal that is assumed to be reached as the effect of the performed action. The concepts of the cognitive subject, the truth bearings and the knowledge are redefined. The classical problems of aletheiology and epistemology are discussed in the light of the proposed approach. The cybernetic construct of an autonomous agent allows the researcher to consider a wide class of cognitive entities, which, in the previous approaches, have been limited only to human beings as cognitive subjects. (shrink)

Neuroscience has become increasingly reliant on multi-subject research in addition to studies of unusual single patients. This research has brought with it a challenge: how are data from different human brains to be combined? The dominant strategy for aggregating data across brains is what I call the ‘cartographic approach’, which involves mapping data from individuals to a spatial template. Here I characterize the cartographic approach and argue that one of its key steps, registration, should be carried out in a way (...) that is sensitive to the target of investigation. Because registration aims to align homologous brain locations, but not all homologous locations can be simultaneously aligned, a multiplicity of registration methods is required to meet the needs of researchers investigating different phenomena. I call this position ‘registration pluralism’. Registration pluralism has potential implications for neuroscientific practice, three of which I discuss here. This work shows the importance of reflecting more carefully on data aggregation methods, especially in light of the substantial individual differences that exist between brains. (shrink)

The philosophical interest in experimental practice in neuroscience has brought renewed attention to the study of the development and use of techniques and tools for data production. John Bickle has argued that the construction and progression of theories in neuroscience are entirely dependent on the development and ingenious use of research tools. In Bickle's account, theory plays a tertiary role, as it depends on what the tools allow researchers to manipulate, and the tools, in turn, are developed not in order (...) to test theories but as solutions to engineering problems. However, Bickle's account is not entirely precise in explaining what informs researchers' decision-making in their atheoretical laboratory tinkering. Identifying the sources that guide researchers in tool development and use is crucial if one wishes to contribute to the philosophical or meta-scientific understanding of experimental practice in neuroscience. In the following paper, I claim that decision-making in tools' development and use in neuroscience is doubly guided. Pre-existing theory and concepts determine information's relevance, whereas tools' functioning in controlled situations determines information's reliability. Accordingly, experimenters' decision-making is situated both in the context of analysing, modelling or interpreting information and in the context of producing information. I study the case of the tungsten microelectrode developed by David Hubel during the 1950s. First, I show that pre-existing theory and concepts determine in advance what information would be relevant to obtain from the microelectrode. Second, I show that Hubel's tinkering follows the guidelines derived from the very structure of what we recognise as reliable experimentally produced information. Finally, I suggest that data-production processes allow experimenters to assess what to expect from an experimental system in terms of concept- and theory-generation and confirmation, thereby endorsing Bickle's tenet on the tertiary role of theory in neuroscience. (shrink)