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  1. Exploring the socio-ecology of science: the case of coral reefs.Elis Jones - 2024 - European Journal for Philosophy of Science 14 (3):1-32.
    In this paper I use data from interviews conducted with coral scientists to examine the socio-ecological dimensions of science, i.e. how science shapes and is shaped by the living world around it. I use two sets of ideas in particular: niche construction and socio-ecological value frameworks. Using these I offer socio-ecological criteria by which coral scientists evaluate the activities of coral science, more specifically which living systems are intended to benefit from coral science as an activity, and the motivations behind (...)
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  • Eight Other Questions about Explanation.Angela Potochnik - 2018 - In Alexander Reutlinger & Juha Saatsi (eds.), Explanation Beyond Causation: Philosophical Perspectives on Non-Causal Explanations. Oxford, United Kingdom: Oxford University Press.
    The tremendous philosophical focus on how to characterize explanatory metaphysical dependence has eclipsed a number of other unresolved issued about scientific explanation. The purpose of this paper is taxonomical. I will outline a number of other questions about the nature of explanation and its role in science—eight, to be precise—and argue that each is independent. All of these topics have received some philosophical attention, but none nearly so much as it deserves. Furthermore, existing views on these topics have been obscured (...)
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  • Why one model is never enough: a defense of explanatory holism.Hochstein Eric - 2017 - Biology and Philosophy 32 (6):1105-1125.
    Traditionally, a scientific model is thought to provide a good scientific explanation to the extent that it satisfies certain scientific goals that are thought to be constitutive of explanation. Problems arise when we realize that individual scientific models cannot simultaneously satisfy all the scientific goals typically associated with explanation. A given model’s ability to satisfy some goals must always come at the expense of satisfying others. This has resulted in philosophical disputes regarding which of these goals are in fact necessary (...)
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  • Scientific progress: Knowledge versus understanding.Finnur Dellsén - 2016 - Studies in History and Philosophy of Science Part A 56 (C):72-83.
    What is scientific progress? On Alexander Bird’s epistemic account of scientific progress, an episode in science is progressive precisely when there is more scientific knowledge at the end of the episode than at the beginning. Using Bird’s epistemic account as a foil, this paper develops an alternative understanding-based account on which an episode in science is progressive precisely when scientists grasp how to correctly explain or predict more aspects of the world at the end of the episode than at the (...)
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  • Introduction: Cognitive attitudes and values in science.Daniel J. McKaughan & Kevin C. Elliott - 2015 - Studies in History and Philosophy of Science Part A 53:57-61.
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  • Science and the Public.Angela Potochnik - 2024 - Cambridge University Press.
    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 (...)
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  • The Medical Model of “Obesity” and the Values Behind the Guise of Health.Kayla R. Mehl - forthcoming - Synthese 201 (6):1-28.
    Assumptions about obesity—e.g., its connection to ill health, its causes, etc.—are still prevalent today, and they make up what I call the medical model of fatness. In this paper, I argue that the medical model was established on the basis of insufficient evidence and has nevertheless continued to be relied upon to justify methodological choices that further entrench the assumptions of the medical model. These choices are illegitimate in so far as they conflict with both the epistemic and social aims (...)
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  • Understanding in Medicine.Somogy Varga - 2023 - Erkenntnis 134:1-25.
    This paper aims to clarify the nature of understanding in medicine. The first part describes in more detail what it means to understand something and links a type of understanding (i.e., objectual understanding) to explanations. The second part proceeds to investigate what objectual understanding of a disease (i.e., biomedical understanding) requires by considering the case of scurvy from the history of medicine. The main hypothesis is that grasping a mechanistic explanation of a condition is necessary for a biomedical understanding of (...)
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  • Understanding in Medicine.Varga Somogy - 2023 - Erkenntnis.
    This paper aims to clarify the nature of understanding in medicine. The first part describes in more detail what it means to understand something and links a type of understanding (i.e., objectual understanding) to explanations. The second part proceeds to investigate what objectual understanding of a disease (i.e., biomedical understanding) requires by considering the case of scurvy from the history of medi- cine. The main hypothesis is that grasping a mechanistic explanation of a condi- tion is necessary for a biomedical (...)
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  • Evaluating community science.Karen Kovaka - 2021 - Studies in History and Philosophy of Science Part A 88 (C):102-109.
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  • In Conversation with Artificial Intelligence: Aligning language Models with Human Values.Atoosa Kasirzadeh - 2023 - Philosophy and Technology 36 (2):1-24.
    Large-scale language technologies are increasingly used in various forms of communication with humans across different contexts. One particular use case for these technologies is conversational agents, which output natural language text in response to prompts and queries. This mode of engagement raises a number of social and ethical questions. For example, what does it mean to align conversational agents with human norms or values? Which norms or values should they be aligned with? And how can this be accomplished? In this (...)
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  • How Values Shape the Machine Learning Opacity Problem.Emily Sullivan - 2022 - In Insa Lawler, Kareem Khalifa & Elay Shech (eds.), Scientific Understanding and Representation: Modeling in the Physical Sciences. New York, NY: Routledge. pp. 306-322.
    One of the main worries with machine learning model opacity is that we cannot know enough about how the model works to fully understand the decisions they make. But how much is model opacity really a problem? This chapter argues that the problem of machine learning model opacity is entangled with non-epistemic values. The chapter considers three different stages of the machine learning modeling process that corresponds to understanding phenomena: (i) model acceptance and linking the model to the phenomenon, (ii) (...)
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  • Scientific Progress: By-Whom or For-Whom?Finnur Dellsén - 2022 - Studies in History and Philosophy of Science Part A 97 (C):20-28.
    When science makes cognitive progress, who or what is it that improves in the requisite way? According to a widespread and unchallenged assumption, it is the cognitive attitudes of scientists themselves, i.e. the agents by whom scientific progress is made, that improve during progressive episodes. This paper argues against this assumption and explores a different approach. Scientific progress should be defined in terms of potential improvements to the cognitive attitudes of those for whom progress is made, i.e. the receivers rather (...)
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  • Symmetry and Reformulation: On Intellectual Progress in Science and Mathematics.Josh Hunt - 2022 - Dissertation, University of Michigan
    Science and mathematics continually change in their tools, methods, and concepts. Many of these changes are not just modifications but progress---steps to be admired. But what constitutes progress? This dissertation addresses one central source of intellectual advancement in both disciplines: reformulating a problem-solving plan into a new, logically compatible one. For short, I call these cases of compatible problem-solving plans "reformulations." Two aspects of reformulations are puzzling. First, reformulating is often unnecessary. Given that we could already solve a problem using (...)
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  • Epistemic Priority or Aims of Research? A Critique of Lexical Priority of Truth in Regulatory Science.Joby Verghese - 2022 - Croatian Journal of Philosophy 22 (64):21-37.
    A general criterion for distinguishing between epistemic and non-epistemic values is that the former promotes the attainment of truth whereas the latter does not. Daniel Steel is a proponent of this criterion, although it was initially proposed by McMullin. There are at least two consequences of this criterion; it always prioritizes epistemic values over non-epistemic values in scientific research, and it overlooks the diverse aims of science, especially the aims of regulatory or policy-oriented science. This criterion assumes the lexical priority (...)
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  • Inductive Risk, Understanding, and Opaque Machine Learning Models.Emily Sullivan - 2022 - Philosophy of Science 89 (5):1065-1074.
    Under what conditions does machine learning (ML) model opacity inhibit the possibility of explaining and understanding phenomena? In this article, I argue that nonepistemic values give shape to the ML opacity problem even if we keep researcher interests fixed. Treating ML models as an instance of doing model-based science to explain and understand phenomena reveals that there is (i) an external opacity problem, where the presence of inductive risk imposes higher standards on externally validating models, and (ii) an internal opacity (...)
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  • Foregrounding and backgrounding: a new interpretation of “levels” in science.Eric Hochstein - 2022 - European Journal for Philosophy of Science 12 (2):1-22.
    Talk of “levels” can be found throughout the sciences, from “levels of abstraction”, to “levels of organization”, to “levels of analysis”. This has led to substantial disagreement regarding the ontology of levels, and whether the various senses of levels each have genuine value and utility to scientific practice. In this paper, I propose a unified framework for thinking about levels in science which ties together the various ways in which levels are invoked in science, and which can overcome the problems (...)
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  • Revisiting abstraction and idealization: how not to criticize mechanistic explanation in molecular biology.Martin Zach - 2022 - European Journal for Philosophy of Science 12 (1):1-20.
    Abstraction and idealization are the two notions that are most often discussed in the context of assumptions employed in the process of model building. These notions are also routinely used in philosophical debates such as that on the mechanistic account of explanation. Indeed, an objection to the mechanistic account has recently been formulated precisely on these grounds: mechanists cannot account for the common practice of idealizing difference-making factors in models in molecular biology. In this paper I revisit the debate and (...)
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  • Scientific representation in practice: Models and creative similarity.Julia Sanchez-Dorado - 2019 - Dissertation,
    The thesis proposes an account of the means of scientific representation focused on similarity, or more specifically, on the notion of “creative similarity”. I first distinguish between two different questions regarding the problem of representation: the question about the constituents and the question about the means of representation (following Suárez 2003; van Fraassen 2008). I argue that, although similarity is not a good candidate for constituent of representation, it can satisfactorily answer the question about the means of representation if adequately (...)
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  • Theorizing Participatory Research.Andrew Evans & Angela Potochnik - forthcoming - In Emily Anderson (ed.), Ethical Issues in Stakeholder-Engaged Health Research. Springer.
    A wide variety of scientific research projects include public participation in roles going beyond the classic use of subjects in human subjects research. “Participatory research” is an umbrella term for such projects. In this chapter, we begin by surveying the variety of participatory research approaches across fields. We examine what goals participatory research projects seek to achieve, both of social and scientific value. Next, we apply this theoretical framework to challenges that participatory research faces. We then survey three typologies of (...)
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  • Truth and reality: How to be a scientific realist without believing scientific theories should be true.Angela Potochnik - 2022 - In Insa Lawler, Kareem Khalifa & Elay Shech (eds.), Scientific Understanding and Representation: Modeling in the Physical Sciences. New York, NY: Routledge.
    Scientific realism is a thesis about the success of science. Most traditionally: science has been so successful at prediction and guiding action because its best theories are true (or approximately true or increasing in their degree of truth). If science is in the business of doing its best to generate true theories, then we should turn to those theories for explanatory knowledge, predictions, and guidance of our actions and decisions. Views that are popular in contemporary philosophy of science about scientific (...)
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  • Understanding Physics: ‘What?’, ‘Why?’, and ‘How?’.Mario Hubert - 2021 - European Journal for Philosophy of Science 11 (3):1-36.
    I want to combine two hitherto largely independent research projects, scientific understanding and mechanistic explanations. Understanding is not only achieved by answering why-questions, that is, by providing scientific explanations, but also by answering what-questions, that is, by providing what I call scientific descriptions. Based on this distinction, I develop three forms of understanding: understanding-what, understanding-why, and understanding-how. I argue that understanding-how is a particularly deep form of understanding, because it is based on mechanistic explanations, which answer why something happens in (...)
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  • The multifaceted role of imagination in science and religion. A critical examination of its epistemic, creative and meaning-making functions.Ingrid Malm Lindberg - 2021 - Dissertation, Uppsala University
    The main purpose of this dissertation is to examine critically and discuss the role of imagination in science and religion, with particular emphasis on its possible epistemic, creative, and meaning-making functions. In order to answer my research questions, I apply theories and concepts from contemporary philosophy of mind on scientific and religious practices. This framework allows me to explore the mental state of imagination, not as an isolated phenomenon but, rather, as one of many mental states that co-exist and interplay (...)
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  • Does environmental science crowd out non-epistemic values?Kinley Gillette, Stephen Andrew Inkpen & C. Tyler DesRoches - 2021 - Studies in History and Philosophy of Science Part A 87 (C):81-92.
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  • A Defense of Truth as a Necessary Condition on Scientific Explanation.Christopher Pincock - 2021 - Erkenntnis 88 (2):621-640.
    How can a reflective scientist put forward an explanation using a model when they are aware that many of the assumptions used to specify that model are false? This paper addresses this challenge by making two substantial assumptions about explanatory practice. First, many of the propositions deployed in the course of explaining have a non-representational function. In particular, a proposition that a scientist uses and also believes to be false, i.e. an “idealization”, typically has some non-representational function in the practice, (...)
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  • Epistemic Dependence and Understanding: Reformulating through Symmetry.Josh Hunt - 2023 - British Journal for the Philosophy of Science 74 (4):941-974.
    Science frequently gives us multiple, compatible ways of solving the same problem or formulating the same theory. These compatible formulations change our understanding of the world, despite providing the same explanations. According to what I call "conceptualism," reformulations change our understanding by clarifying the epistemic structure of theories. I illustrate conceptualism by analyzing a typical example of symmetry-based reformulation in chemical physics. This case study poses a problem for "explanationism," the rival thesis that differences in understanding require ontic explanatory differences. (...)
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  • Novel & worthy: creativity as a thick epistemic concept.Julia Sánchez-Dorado - 2020 - European Journal for Philosophy of Science 10 (3):1-23.
    The standard view in current philosophy of creativity says that being creative has two requirements: being novel and being valuable. The standard view on creativity has recently become an object of critical scrutiny. Hills and Bird have specifically proposed to remove the value requirement from the definition, as it is not clear that creative objects are necessarily valuable or creative people necessarily praiseworthy. In this paper, I argue against Hills and Bird, since eliminating the element of value from the explanation (...)
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  • The Aims and Structures of Research Projects That Use Gene Regulatory Information with Evolutionary Genetic Models.Steve Elliott - 2017 - Dissertation, Arizona State University
    At the interface of developmental biology and evolutionary biology, the very criteria of scientific knowledge are up for grabs. A central issue is the status of evolutionary genetics models, which some argue cannot coherently be used with complex gene regulatory network (GRN) models to explain the same evolutionary phenomena. Despite those claims, many researchers use evolutionary genetics models jointly with GRN models to study evolutionary phenomena. This dissertation compares two recent research projects in which researchers jointly use the two kinds (...)
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  • Explicating Objectual Understanding: Taking Degrees Seriously.Christoph Baumberger - 2019 - Journal for General Philosophy of Science / Zeitschrift für Allgemeine Wissenschaftstheorie 50 (3):367-388.
    The paper argues that an account of understanding should take the form of a Carnapian explication and acknowledge that understanding comes in degrees. An explication of objectual understanding is defended, which helps to make sense of the cognitive achievements and goals of science. The explication combines a necessary condition with three evaluative dimensions: an epistemic agent understands a subject matter by means of a theory only if the agent commits herself sufficiently to the theory of the subject matter, and to (...)
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  • Understanding from Machine Learning Models.Emily Sullivan - 2022 - British Journal for the Philosophy of Science 73 (1):109-133.
    Simple idealized models seem to provide more understanding than opaque, complex, and hyper-realistic models. However, an increasing number of scientists are going in the opposite direction by utilizing opaque machine learning models to make predictions and draw inferences, suggesting that scientists are opting for models that have less potential for understanding. Are scientists trading understanding for some other epistemic or pragmatic good when they choose a machine learning model? Or are the assumptions behind why minimal models provide understanding misguided? In (...)
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  • Speech Act Theory and the Multiple Aims of Science.Paul L. Franco - 2019 - Philosophy of Science 86 (5):1005-1015.
    I draw upon speech act theory to understand the speech acts appropriate to the multiple aims of scientific practice and the role of nonepistemic values in evaluating speech acts made relative to those aims. First, I look at work that distinguishes explaining from describing within scientific practices. I then argue speech act theory provides a framework to make sense of how explaining, describing, and other acts have different felicity conditions. Finally, I argue that if explaining aims to convey understanding to (...)
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  • Bottled Understanding: The Role of Lab Work in Ecology.Adrian Currie - 2020 - British Journal for the Philosophy of Science 71 (3):905-932.
    It is often thought that the vindication of experimental work lies in its capacity to be revelatory of natural systems. I challenge this idea by examining laboratory experiments in ecology. A central task of community ecology involves combining mathematical models and observational data to identify trophic interactions in natural systems. But many ecologists are also lab scientists: constructing microcosm or ‘bottle’ experiments, physically realizing the idealized circumstances described in mathematical models. What vindicates such ecological experiments? I argue that ‘extrapolationism’, the (...)
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  • Representationalism is a dead end.Guilherme Sanches de Oliveira - 2018 - Synthese 198 (1):209-235.
    Representationalism—the view that scientific modeling is best understood in representational terms—is the received view in contemporary philosophy of science. Contributions to this literature have focused on a number of puzzles concerning the nature of representation and the epistemic role of misrepresentation, without considering whether these puzzles are the product of an inadequate analytical framework. The goal of this paper is to suggest that this possibility should be taken seriously. The argument has two parts, employing the “can’t have” and “don’t need” (...)
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  • Psa 2018.Philsci-Archive -Preprint Volume- - unknown
    These preprints were automatically compiled into a PDF from the collection of papers deposited in PhilSci-Archive in conjunction with the PSA 2018.
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  • Should Scientific Realists Embrace Theoretical Conservatism?Finnur Dellsén - 2018 - Studies in History and Philosophy of Science Part A:30-38.
    A prominent type of scientific realism holds that some important parts of our best current scientific theories are at least approximately true. According to such realists, radically distinct alternatives to these theories or theory-parts are unlikely to be approximately true. Thus one might be tempted to argue, as the prominent anti-realist Kyle Stanford recently did, that realists of this kind have little or no reason to encourage scientists to attempt to identify and develop theoretical alternatives that are radically distinct from (...)
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  • Explicating objectual understanding: taking degrees seriously.Christoph Baumberger - 2019 - Journal for General Philosophy of Science / Zeitschrift für Allgemeine Wissenschaftstheorie 1 (3):367-388.
    The paper argues that an account of understanding should take the form of a Carnapian explication and acknowledge that understanding comes in degrees. An explication of objectual understanding is defended, which helps to make sense of the cognitive achievements and goals of science. The explication combines a necessary condition with three evaluative dimensions: An epistemic agent understands a subject matter by means of a theory only if the agent commits herself sufficiently to the theory of the subject matter, and to (...)
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  • Problems and Questions in Scientific Practice.Steve Elliott - manuscript
    THIS IS AN EARLY DRAFT OF MY PAPER "RESEARCH PROBLEMS" PUBLISHED IN BJPS IN 2021. PLEASE REFER TO THAT PAPER INSTEAD OF THIS ONE. -/- Philosophers increasingly study how scientists conduct actual scientific projects and the goals they pursue. But as of yet, there are few accounts of goals that can be used to identify different kinds, and specific instances, of goals pursued by scientists. I propose that there are at least four distinct kinds of goals pursued by scientists: ameliorating (...)
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  • Beyond Explanation: Understanding as Dependency Modeling.Finnur Dellsén - 2018 - British Journal for the Philosophy of Science (4):1261-1286.
    This paper presents and argues for an account of objectual understanding that aims to do justice to the full range of cases of scientific understanding, including cases in which one does not have an explanation of the understood phenomenon. According to the proposed account, one understands a phenomenon just in case one grasps a sufficiently accurate and comprehensive model of the ways in which it or its features are situated within a network of dependence relations; one’s degree of understanding is (...)
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  • Scientific progress: Four accounts.Finnur Dellsén - 2018 - Philosophy Compass 13 (11):e12525.
    Scientists are constantly making observations, carrying out experiments, and analyzing empirical data. Meanwhile, scientific theories are routinely being adopted, revised, discarded, and replaced. But when are such changes to the content of science improvements on what came before? This is the question of scientific progress. One answer is that progress occurs when scientific theories ‘get closer to the truth’, i.e. increase their degree of truthlikeness. A second answer is that progress consists in increasing theories’ effectiveness for solving scientific problems. A (...)
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  • When Do Scientific Explanations Compete? Steps Toward a Heuristic Checklist.Todd Jones & Michael Pravica - 2017 - Metaphilosophy 48 (1-2):96-122.
    It's not uncommon for scientists to give different explanations of the same phenomenon, but we currently lack clear guidelines for deciding whether to treat such accounts as competitors. This article discusses how science studies can help create tools and guidelines for thinking about whether explanations compete. It also specifies how one family of discourse rules enables there to be differing accounts that appear to compete but don't. One hopes that being more aware of the linguistic mechanisms making compatible accounts appear (...)
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  • Sustainability and the Infinite Future: A Case Study of a False Modeling Assumption in Environmental Economics.Daniel Steel - 2017 - Erkenntnis 82 (5):1065-1084.
    This essay examines the issue of false assumptions in models via a case study of a prominent economic model of sustainable development, wherein the assumption of an infinite future plays a central role. Two proposals are found to be helpful for this case, one based on the concept of derivational robustness and the other on understanding. Both suggest that the assumption of an infinite future, while arguably legitimate in some applications of the model, is problematic with respect to what I (...)
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  • Modelling the mind: Nietzsche’s epistemic ends in his account of drive interaction.Toby Tricks - 2024 - Inquiry: An Interdisciplinary Journal of Philosophy 67 (5):1296-1319.
    Nietzsche offers us an account of how different drives interact with one another; it is rich but also appears to risk the homunculus fallacy. Competing attempts to deflect this charge on his behalf share an implicit consensus about the ‘epistemic ends’ of the account: they assume Nietzsche is trying to provide true explanations of psychological phenomena. I argue against this consensus. I claim that Nietzsche's characterisations of drive interaction are to be taken as fictive and are not intended to have (...)
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