Angela Potochnik
University of Cincinnati, Philosophy, Faculty Member
- Website: angelapotochnik.com. I am Professor of Philosophy and Director of the Center for Public Engagement with Scie... moreWebsite: angelapotochnik.com. I am Professor of Philosophy and Director of the Center for Public Engagement with Science at the University of Cincinnati. My research addresses the nature of science and its successes, the relationships between science and the public, and methods in population biology. I earned my PhD from Stanford University in 2007.edit
Science is a product of society: in its funding, its participation, and its application. This Element explores the relationship between science and the public with resources from philosophy of science. Chapter 1 defines the questions... more
Science is a product of society: in its funding, its participation, and its application. This Element explores the relationship between science and the public with resources from philosophy of science. Chapter 1 defines the questions about science's relationship to the public and outlines science's obligation to the public. Chapter 2 considers the Vienna Circle as a case study in how science, philosophy, and the public can relate very differently than they do at present. Chapter 3 examines how public understanding of science can have a variety of different goals and introduces philosophical discussions of scientific understanding as a resource. Chapter 4 addresses public trust in science, including responding to science denial. Chapter 5 considers how expanded participation in science can contribute to public trust of science. Finally, Chapter 6 casts light on how science might discharge its obligations to the public.
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Scientific literacy is an essential aspect of an undergraduate education. Recipes for Science responds to this need by providing an accessible introduction to the nature of science and scientific methods appropriate for any beginning... more
Scientific literacy is an essential aspect of an undergraduate education. Recipes for Science responds to this need by providing an accessible introduction to the nature of science and scientific methods appropriate for any beginning college student. The book is adaptable to a wide variety of different courses, such as introductions to scientific reasoning, methods courses in scientific disciplines, science education, and philosophy of science.
Recipes for Science was first published in 2018, and a thoroughly revised second edition was published in 2024. Special features include contemporary and historical case studies from many fields of physical, life, and social sciences; visual aids to clarify and illustrate ideas; text boxes to explore related topics; plenty of exercises to support student recall and application of concepts; suggestions for further readings at the end of each chapter; a glossary with helpful definitions of key terms; and a companion website with course syllabi, PowerPoint presentations, additional exercises, and original short videos on key topics.
Recipes for Science was first published in 2018, and a thoroughly revised second edition was published in 2024. Special features include contemporary and historical case studies from many fields of physical, life, and social sciences; visual aids to clarify and illustrate ideas; text boxes to explore related topics; plenty of exercises to support student recall and application of concepts; suggestions for further readings at the end of each chapter; a glossary with helpful definitions of key terms; and a companion website with course syllabi, PowerPoint presentations, additional exercises, and original short videos on key topics.
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Idealizations are assumptions made without regard for whether they are true and often with full knowledge they are false. Physicists sometimes assume a surface is a frictionless plane, or that gases are 'ideal' or 'perfect.' Biologists... more
Idealizations are assumptions made without regard for whether they are true and often with full knowledge they are false. Physicists sometimes assume a surface is a frictionless plane, or that gases are 'ideal' or 'perfect.' Biologists sometimes assume a population of animals is infinite in size. And economists sometimes assume humans are perfectly rational agents. These are all idealizations.
In this book, I motivate a strong view of idealizations' centrality to science, and I reconsider the aims of science in light of that centrality. On the account I develop, science does not pursue truth directly, but instead aims to support human cognitive and practical ends. Those are projects to which idealizations can directly contribute in a number of ways.
The first three chapters are used to develop my account of idealization's central role in science. In Chapter One, I discuss how science is shaped by its human practitioners and by the world's complexity. Together, these two ideas inspire a view of science as the search for causal patterns, a search that relies heavily on idealizations. Idealizations contribute to science in a variety of ways, including by playing a positive representational role. These ideas are developed in Chapter Two. In Chapter Three, I detail case studies that demonstrate the ubiquity of idealization in science, as well as the wide range of purposes it serves.
The last four chapters explore the implications of this account of idealization for central philosophical debates about the aims of science. Chapter Four motivates the idea that the epistemic aim of science is not truth but human understanding. Understanding is a cognitive achievement, and, unlike truth, it can be directly furthered by idealizations. In Chapter Five, I develop an account of scientific explanation that does justice to how the production of understanding depends on human cognizers. Then, in Chapter Six, I challenge classic conceptions of scientific levels of organization and develop a view that better accords with idealized representation across all fields of science. Finally, Chapter Seven shows how this account of idealization and the aims of science expands the influence of human characteristics and values on science's aims and products, while also constraining scientific and metaphysical pluralism.
In this book, I motivate a strong view of idealizations' centrality to science, and I reconsider the aims of science in light of that centrality. On the account I develop, science does not pursue truth directly, but instead aims to support human cognitive and practical ends. Those are projects to which idealizations can directly contribute in a number of ways.
The first three chapters are used to develop my account of idealization's central role in science. In Chapter One, I discuss how science is shaped by its human practitioners and by the world's complexity. Together, these two ideas inspire a view of science as the search for causal patterns, a search that relies heavily on idealizations. Idealizations contribute to science in a variety of ways, including by playing a positive representational role. These ideas are developed in Chapter Two. In Chapter Three, I detail case studies that demonstrate the ubiquity of idealization in science, as well as the wide range of purposes it serves.
The last four chapters explore the implications of this account of idealization for central philosophical debates about the aims of science. Chapter Four motivates the idea that the epistemic aim of science is not truth but human understanding. Understanding is a cognitive achievement, and, unlike truth, it can be directly furthered by idealizations. In Chapter Five, I develop an account of scientific explanation that does justice to how the production of understanding depends on human cognizers. Then, in Chapter Six, I challenge classic conceptions of scientific levels of organization and develop a view that better accords with idealized representation across all fields of science. Finally, Chapter Seven shows how this account of idealization and the aims of science expands the influence of human characteristics and values on science's aims and products, while also constraining scientific and metaphysical pluralism.
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This text provides an accessible introduction to the main concepts and methods of scientific reasoning. With the help of an array of contemporary and historical examples, definitions, visual aids, and exercises for active learning, the... more
This text provides an accessible introduction to the main concepts and methods of scientific reasoning. With the help of an array of contemporary and historical examples, definitions, visual aids, and exercises for active learning, the textbook helps to increase students’ scientific literacy. The first part of the book covers the definitive features of science: naturalism, experimentation, modeling, and their merits and limitations. The second part covers the main forms of inference in science: deductive, inductive, abductive, probabilistic, statistical, and causal. The book concludes with a discussion of explanation, theorizing and theory-change, and the relationship between science and society. The textbook is designed to be adaptable to a wide variety of different kinds of courses. In any of these different uses, the book helps students better navigate our scientific, 21st-century world, and it lays the foundation for more advanced undergraduate coursework in a wide variety of liberal arts and science courses.
Research Interests: Philosophy of Science, Social Sciences, Science Education, History of Science, Science, and 36 moreScientific Models, Scientific Reasoning, Nature of Science, Scientific Literacy, Elementary Science Education, Science Teaching Methods, Scientific method & Education, Scientific Inference, Scientific methodology, Science teacher education, Science and Mathematics Education, Ciencia, Ciências Da Educação, Ciencias, Science education, nature of science, Wissenschaftliche Weiterbildung, Escuela Ciencias de la Educación, Scientific Method, Ciencias de la educación, Educação em ciências, Scientific Research, Pedagogische wetenschappen, Videnskabelig Praksis, Models in science education, Ciencias Naturales, Modeling and Science Instruction, Wetenschapsfilosofie, Ciencias de la educacion, The Nature of Science and How Science Works, Science Education; Teacher Education Program; Nature of Science, Modeling in Science Education, Éducation Scientifique, Statistical Inference and Scientific Method, Bilimsel Din Eğitimi, Educazione Scientifica, and razonamiento cientifico
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Idealizations are rampant and unchecked in science. That is, they exist throughout our best representations, and there is little focus on eliminating them or controlling their influence. This is because idealizations, despite their... more
Idealizations are rampant and unchecked in science. That is, they exist throughout our best representations, and there is little focus on eliminating them or controlling their influence. This is because idealizations, despite their falsity, play a positive representational role. This account of idealization motivates a reconstrual of the aims of science. Science has a variety of epistemic and non-epistemic aims, and the ultimate epistemic aim is understanding, which can be furthered by sacrificing truth. The deemphasis of scientific truth drives a wedge between scientific results and any metaphysical implications regarding ontology, causation, or levels of organization.
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The concept of hierarchical organization is commonplace in science. Subatomic particles compose atoms, which compose molecules; cells compose tissues, which compose organs, which compose organisms; etc. Hierarchical organization is... more
The concept of hierarchical organization is commonplace in science. Subatomic particles compose atoms, which compose molecules; cells compose tissues, which compose organs, which compose organisms; etc. Hierarchical organization is particularly prominent in ecology, a field of research explicitly arranged around levels of ecological organization. The concept of levels of organization is also central to a variety of debates in philosophy of science. Yet many difficulties plague the concept of discrete hierarchical levels. In this paper, we show how these difficulties undermine various implications ascribed to hierarchical organization, and we suggest the concept of scale as a promising alternative to levels. Investigating causal processes at different scales offers a way to retain a notion of quasi-levels that avoids the difficulties inherent in the classic concept of hierarchical levels of organization. Throughout, our focus is on ecology, but the results generalize to other invocations of hierarchy in science and philosophy of science.
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Philosophical accounts of scientific explanation tend to focus on developing a conception of the kind of dependence that is explanatory, e.g., nomic, causal-mechanical, difference-making, etc. Disagreements about other features of... more
Philosophical accounts of scientific explanation tend to focus on developing a conception of the kind of dependence that is explanatory, e.g., nomic, causal-mechanical, difference-making, etc. Disagreements about other features of explanation are often presented as secondary issues linked to specific accounts of explanatory dependence. As a result, many features of explanatory practices about which philosophers disagree have not received sufficient attention. This chapter articulates several of those features—eight, to be exact—and discusses some of the ideas that have been raised about each. The purpose of this chapter is not to defend any one conception of any of these features, but to distinguish among the relatively distinct features of explanation about which philosophers disagree and, for each, to clarify what is at stake. Most of these disagreements have little to do with the nature of explanatory dependence and, in particular, whether or not explanation is causal in nature.
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Scientific explanations must bear the proper relationship to the world: they must depict what, out in the world, is responsible for the explanandum. But explanations must also bear the proper relationship to their audience: they must be... more
Scientific explanations must bear the proper relationship to the world: they must depict what, out in the world, is responsible for the explanandum. But explanations must also bear the proper relationship to their audience: they must be able to create human understanding. With few exceptions, philosophical accounts of explanation either ignore entirely the relationship between explanations and their audience or else demote this consideration to an ancillary role. In contrast, I argue that considering an explanation’s communicative role is crucial to any satisfactory account of explanation.
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In this article, I first outline the view developed in my recent book on the role of idealization in scientific understanding. I discuss how this view leads to the recognition of a number of kinds of variability among scientific... more
In this article, I first outline the view developed in my recent book on the role of idealization in scientific understanding. I discuss how this view leads to the recognition of a number of kinds of variability among scientific representations, including variability introduced by the many different aims of scientific projects. I then argue that the role of idealization in securing understanding distances understanding from truth but that this understanding nonetheless gives rise to scientific knowledge. This discussion will clarify how my view relates to three other recent books on understanding by Henk de Regt, Catherine Elgin, and Kareem Khalifa.
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Michael Strevens offers an account of causal explanation according to which explanatory practice is shaped by counterbalanced commitments to representing causal influence and abstracting away from overly specific details. In this paper, I... more
Michael Strevens offers an account of causal explanation according to which explanatory practice is shaped by counterbalanced commitments to representing causal influence and abstracting away from overly specific details. In this paper, I challenge a key feature of that account. I argue that what Strevens calls explanatory frameworks figure prominently in explanatory practice because they actually improve explanations. This suggestion is simple but has far-reaching implications. It affects the status of explanations that cite multiply realizable properties; changes the explanatory role of causal factors with small effect; and undermines Strevens’ titular explanatory virtue, depth. This results in greater coherence with explanatory practice and accords with the emphasis that Strevens places on explanatory patterns. Ultimately, my suggestion preserves a tight connection between explanation and the creation of understanding by taking into account explanations’ role in communication.
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Research Interests: Philosophy and Aufbau
Levels of organization and their use in science have received increased philosophical attention of late, including challenges to the well-foundedness or widespread usefulness of levels concepts. One kind of response to these challenges... more
Levels of organization and their use in science have received increased philosophical attention of late, including challenges to the well-foundedness or widespread usefulness of levels concepts. One kind of response to these challenges has been to advocate a more precise and specific levels concept that is coherent and useful. Another kind of response has been to argue that the levels concept should be taken as a heuristic, to embrace its ambiguity and the possibility of exceptions as acceptable consequences of its usefulness. In this chapter, I suggest that each of these strategies faces its own attendant downsides, and that pursuit of both strategies (by different thinkers) compounds the difficulties. That both kinds of approaches are advocated is, I think, illustrative of the problems plaguing the concept of levels of organization. I end by suggesting that the invocation of levels may mislead scientific and philosophical investigations more than it informs them, so our use of the levels concept should be updated accordingly.
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In this paper, I first outline the view developed in my recent book on the role of idealization in scientific understanding. I discuss how this view leads to the recognition of a number of kinds of variability among scientific... more
In this paper, I first outline the view developed in my recent book on the role of idealization in scientific understanding. I discuss how this view leads to the recognition of a number of kinds of variability among scientific representations, including variability introduced by the many different aims of scientific projects. I then argue that the role of idealization in securing understanding distances understanding from truth, but that this understanding nonetheless gives rise to scientific knowledge. This discussion will clarify how my view relates to three other recent books on understanding by Henk de Regt, Catherine Elgin, and Kareem Khalifa.
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One of biology's fundamental aims is to generate understanding of the living world around—and within—us. In this chapter, I aim to provide a relatively nonpartisan discussion of the nature of explanation in biology, grounded in widely... more
One of biology's fundamental aims is to generate understanding of the living world around—and within—us. In this chapter, I aim to provide a relatively nonpartisan discussion of the nature of explanation in biology, grounded in widely shared philosophical views about scientific explanation. But this discussion also reflects what I think is important for philosophers and biologists alike to appreciate about successful scientific explanations, so some points will be controversial, at least among philosophers. I make three main points: (1) causal relationships and broad patterns have often been granted importance to scientific explanations, and they are in fact both important; (2) some explanations in biology cite the components of or processes in systems that account for the systems’ features, whereas other explanations feature large-scale or structural causes that influence a system; and (3) there can be multiple different explanations of a given biological phenomenon, explanations that respond to different research aims and can thus be compatible with one another even when they may seem to disagree.
Debate about cognitive science explanations has been formulated in terms of identifying the proper level(s) of explanation. Views range from reductionist, favoring only neuroscience explanations, to mechanist, favoring the integration of... more
Debate about cognitive science explanations has been formulated in terms of identifying the proper level(s) of explanation. Views range from reductionist, favoring only neuroscience explanations, to mechanist, favoring the integration of levels, to pluralist, favoring the preservation of even the most general, high-level explanations. We challenge this framing. We suggest that these are not different levels of explanation at all but, rather, different styles of explanation that capture different, cross-cutting patterns in cognitive phenomena. Which pattern is explanatory depends on both the cognitive phenomenon under investigation and the research interests occasioning the explanation. This reframing changes how we should answer the basic questions of which cognitive science approaches explain and how these explanations relate to one another. On this view, we should expect different approaches to offer independent explanations in terms of their different focal patterns and the value of those explanations to partly derive from the broad patterns they feature.
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We affirm Connolly et al.'s insight, in “Process, Mechanism, and Modeling in Macroecology, ” that “explicit representation of causal structure” is central to ecology. However, in our view, these authors' exclusive focus on mechanistic and... more
We affirm Connolly et al.'s insight, in “Process, Mechanism, and Modeling in Macroecology, ” that “explicit representation of causal structure” is central to ecology. However, in our view, these authors' exclusive focus on mechanistic and process-based models overlooks a number of other important modeling approaches that explicitly represent causal structure. We thus argue that the advantages Connolly et al. tout for mechanistic and process-based models are better attributed to a much broader class of models: causal models.
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Explanations must bear the proper relationship to the world: they must capture what, out in the world, is responsible for the explanandum. At issue among traditional accounts of explanation is how to construe that responsibility relation,... more
Explanations must bear the proper relationship to the world: they must capture what, out in the world, is responsible for the explanandum. At issue among traditional accounts of explanation is how to construe that responsibility relation, viz., what it is upon which the explanandum depends. But this does not tell us everything we need to know in order to determine the content of scientific explanations. Just as explanations must bear the proper relationship to the world, they must also bear the proper relationship to the individuals for which they are generated. With few exceptions, philosophers either ignore entirely the relationship between explanations and their audience, or else demote this consideration to a secondary role. In contrast, I argue that considerations of an explanation's communicative purpose are necessary in order to get a satisfactory account of explanation off the ground.
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Causal accounts of scientific explanation are currently broadly accepted (though not universally so). My first task in this paper is to show that, even for a causal approach to explanation, significant features of explanatory practice are... more
Causal accounts of scientific explanation are currently broadly accepted (though not universally so). My first task in this paper is to show that, even for a causal approach to explanation, significant features of explanatory practice are not determined by settling how causal facts bear on the phenomenon to be explained. I then develop a broadly causal approach to explanation that accounts for the additional features that I argue an explanation should have. This approach to explanation makes sense of several aspects of actual explanatory practice, including the widespread use of equilibrium explanations, the formulation of distinct explanations for a single event, and the tight relationship between explanations of events and explanations of causal regularities.
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ABSTRACT In recent years, philosophy of science has witnessed a significant increase in attention directed toward the field’s social relevance. This is demonstrated by the formation of societies with related agendas, the organization of... more
ABSTRACT In recent years, philosophy of science has witnessed a significant increase in attention directed toward the field’s social relevance. This is demonstrated by the formation of societies with related agendas, the organization of research symposia, and an uptick in work on topics of immediate public interest. The collection of papers that follows results from one such event: a 3-day colloquium on the subject of socially engaged philosophy of science (SEPOS) held at the University of Cincinnati in October 2012. In this introduction, we first survey the recent history of philosophy of science’s social involvement (or lack thereof) and contrast this with the much greater social involvement of the sciences themselves. Next, we argue that the field of philosophy of science bears a special responsibility to contribute to public welfare. We then introduce as a term of art “SEPOS” and articulate what we take to be distinctive about social engagement, with reference to the articles in this collection as exemplars. Finally, we survey the current state of social engagement in philosophy of science and suggest some practical steps for individuals and institutions to support this trajectory.
Research Interests: Philosophy and Erkenntnis
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ABSTRACT Recent philosophy of science has witnessed a shift in focus, in that significantly more consideration is given to how scientists employ models. Attending to the role of models in scientific practice leads to new questions about... more
ABSTRACT Recent philosophy of science has witnessed a shift in focus, in that significantly more consideration is given to how scientists employ models. Attending to the role of models in scientific practice leads to new questions about the representational roles of models, the purpose of idealizations, why multiple models are used for the same phenomenon, and many more besides. In this paper, I suggest that these themes resonate with central topics in feminist epistemology, in particular prominent versions of feminist empiricism, and that model-based science and feminist epistemology each has crucial resources to offer the other’s project.
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Roundtable review of Joan Roughgarden's _The Genial Gene: Deconstructing Darwinian Selfishness._
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Research Interests: Philosophy and Erkenntnis
ABSTRACT The value of optimality modeling has long been a source of contention amongst population biologists. Here I present a view of the optimality approach as at once playing a crucial explanatory role and yet also depending on... more
ABSTRACT The value of optimality modeling has long been a source of contention amongst population biologists. Here I present a view of the optimality approach as at once playing a crucial explanatory role and yet also depending on external sources of confirmation. Optimality models are not alone in facing this tension between their explanatory value and their dependence on other approaches; I suspect that the scenario is quite common in science. This investigation of the optimality approach thus serves as a case study, on the basis of which I suggest that there is a widely felt tension in science between explanatory independence and broad epistemic interdependence, and that this tension influences scientific methodology.
Research Interests: Philosophy and Case Study
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The fate of optimality modeling is typically linked to that of adaptationism: the two are thought to stand or fall together (Gould and Lewontin, Proc Relig Soc Lond 205:581–598, 1979; Orzack and Sober, Am Nat 143(3):361–380, 1994). I... more
The fate of optimality modeling is typically linked to that of adaptationism: the two are thought to stand or fall together (Gould and Lewontin, Proc Relig Soc Lond 205:581–598, 1979; Orzack and Sober, Am Nat 143(3):361–380, 1994). I argue here that this is mistaken. The debate over adaptationism has tended to focus on one particular use of optimality models, which