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Alexandrova, Anna, Robert Northcott. It’s just a feeling: why economic models do not explain
2013, Journal of Economic Methodology, 20(3), 262-267
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Added by: Simon Fokt, Contributed by: Patricia Rich
Abstract: Julian Reiss correctly identified a trilemma about economic models: we cannot maintain that they are false, but nevertheless explain and that only true accounts explain. In this reply we give reasons to reject the second premise – that economic models explain. Intuitions to the contrary should be distrusted.

Comment: This is a good short article to read alongside Reiss' important paper on the explanation paradox, in the context of a philosophy of economics or social science class. It argues against Reiss' premise that economic models are explanatory. It draws on, but does not require, knowledge of anyone's positions in the larger debate on the status of formal models.

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Alexandrova, Anna. Making Models Count
2008, Philosophy of Science 75(3): 383-404.
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Added by: Nick Novelli

Abstract: What sort of claims do scientific models make and how do these claims then underwrite empirical successes such as explanations and reliable policy interventions? In this paper I propose answers to these questions for the class of models used throughout the social and biological sciences, namely idealized deductive ones with a causal interpretation. I argue that the two main existing accounts misrepresent how these models are actually used, and propose a new account.

Comment: A good exploration of the role of models in scientific practice. Provides a good overview of the main theories about models, and some objections to them, before suggesting an alternative. Good use of concrete examples, presented very clearly. Suitable for undergraduate teaching. Would form a useful part of an examination of modelling in philosophy of science.

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Alvarez, Maria. Kinds of Reasons: An Essay in the Philosophy of Action
2010, Oxford: Oxford University Press.
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Added by: Jie Gao
Publisher's Note: Understanding human beings and their distinctive rational and volitional capacities is one of the central tasks of philosophy. The task requires a clear account of such things as reasons, desires, emotions and motives, and of how they combine to produce and explain human behaviour. In Kinds of Reasons, Maria Alvarez offers a fresh and incisive treatment of these issues, focusing in particular on reasons as they feature in contexts of agency. Her account builds on some important recent work in the area; but she takes her main inspiration from the tradition that receives its seminal contemporary expression in the writings of G.E.M. Anscombe, a tradition that runs counter to the broadly Humean orthodoxy that has dominated the theory of action for the past forty years. Alvarez's conclusions are therefore likely to be controversial; and her bold and painstaking arguments will be found provocative by participants on every side of the debates with which she engages. Clear and directly written, Kinds of Reasons aims to stake out a distinctive position within one of the most hotly contested areas of contemporary philosophy.

Comment: This book is on the ontological nature of reasons for which we act carries on. The first two chapters are very good introductory readings on reasons broadly. Chapters 3 to 5 explore the connection between reasons and motivation. Topics include what motivates actions, whether desires are motivating reasons, and whether motivating reasons are belief. They are proper introductory reading material for courses on ethics, reasons and philosophy of action.

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Bokulich, Alisa. Distinguishing Explanatory from Nonexplanatory Fictions
2012, Philosophy of Science 79(5): 725-737.
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Added by: Jamie Collin
Abstract: There is a growing recognition that fictions have a number of legitimate functions in science, even when it comes to scientific explanation. However, the question then arises, what distinguishes an explanatory fiction from a nonexplanatory one? Here I examine two cases - one in which there is a consensus in the scientific community that the fiction is explanatory and another in which the fiction is not explanatory. I shall show how my account of "model explanations" is able to explain this asymmetry, and argue that realism - of a more subtle form - does have a role in distinguishing explanatory from nonexplanatory fictions.

Comment: This would be useful in a course on the philosophy of science or the philosophy of fiction. It is particularly useful for teaching, as it is cutting edge in the philosophy of science but not particularly technical.

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Bokulich, Alisa. How scientific models can explain
2009, Synthese 180(1): 33-45.
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Added by: Laura Jimenez
Abstract: Scientific models invariably involve some degree of idealization, abstraction, or fictionalization of their target system. Nonetheless, I argue that there are circumstances under which such false models can offer genuine scientific explanations. After reviewing three different proposals in the literature for how models can explain, I shall introduce a more general account of what I call model explanations, which specify the conditions under which models can be counted as explanatory. I shall illustrate this new framework by applying it to the case of Bohr's model of the atom, and conclude by drawing some distinctions between phenomenological models, explanatory models, and fictional models.

Comment: Interesting paper about scientific modelling. It is easy to read and could serve as an introduction to the topic. The paper explores three approaches to Model Explanations: mechanist model explanations, covering-law model explanations, and causal model explanations. The explanatory function in models is illustrated with the example of Bohr's atom. This article is recommended for undergraduate students.

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Cartwright, Nancy. How the Laws of Physics Lie
1983, Oxford University Press.
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Added by: Laura Jimenez
Publisher's Note: Nancy Cartwright argues for a novel conception of the role of fundamental scientific laws in modern natural science. If we attend closely to the manner in which theoretical laws figure in the practice of science, we see that despite their great explanatory power these laws do not describe reality. Instead, fundamental laws describe highly idealized objects in models. Thus, the correct account of explanation in science is not the traditional covering law view, but the 'simulacrum' account. On this view, explanation is a matter of constructing a model that may employ, but need not be consistent with, a theoretical framework, in which phenomenological laws that are true of the empirical case in question can be derived. Anti?realism about theoretical laws does not, however, commit one to anti?realism about theoretical entities. Belief in theoretical entities can be grounded in well?tested localized causal claims about concrete physical processes, sometimes now called 'entity realism'. Such causal claims provide the basis for partial realism and they are ineliminable from the practice of explanation and intervention in nature.

Comment: Essential reading on realism and anti-realism about the laws of nature. Recommended for undergraduates who have prior knowledge of Humeanism about laws and for postgraduates in general. The book consists of a series of philosophical essays that can be used independently.

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Egan, Frances. Computational models: a modest role for content
2010, Studies in History and Philosophy of Science Part A 41(3): 253-259.
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Added by: Nick Novelli
Abstract: The computational theory of mind construes the mind as an information-processor and cognitive capacities as essentially representational capacities. Proponents of the view claim a central role for representational content in computational models of these capacities. In this paper I argue that the standard view of the role of representational content in computational models is mistaken; I argue that representational content is to be understood as a gloss on the computational characterization of a cognitive process.

Comment: Good paper about the relation of representation and content to computation. Best suited to higher-level courses on the subject.

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Emery, Nina. Chance, Possibility and explanation
2015, The British Journal for the Philosophy of Science 0(2015): 1–64.
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Added by: Laura Jimenez
Summary: In this paper the author argues against the common and influential view that non-trivial chances arise only when the fundamental laws are indeterministic. The problem with this view, she claims, is not that it conflicts with some antecedently plausible metaphysics of chance or that it fails to capture our everyday use of 'chance' and related terms, but rather that it is unstable. Any reason for adopting the position that non-trivial chances arise only when the fundamental laws are indeterministic is also a reason for adopting a much stronger, and far less attractive, position. Emery suggests an alternative account, according to which chances are probabilities that play a certain explanatory role: they are probabilities that explain associated frequencies.

Comment: This could serve as a secondary reading for those studying metaphysic theories of chance. Previous background in metaphysics is needed. The paper is recommended for postgraduate students.

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Potochnik, Angela. Levels of Explanation Reconceived
2010, Philosophy of Science 77(1): 59-72.
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Added by: Nick Novelli
Abstract: A common argument against explanatory reductionism is that higher-level explanations are sometimes or always preferable because they are more general than reductive explanations. Here I challenge two basic assumptions that are needed for that argument to succeed. It cannot be assumed that higher-level explanations are more general than their lower-level alternatives or that higher-level explanations are general in the right way to be explanatory. I suggest a novel form of pluralism regarding levels of explanation, according to which explanations at different levels are preferable in different circumstances because they offer different types of generality, which are appropriate in different circumstances of explanation.

Comment: An interesting anti-anti-reductionist article. Would be useful in a discussion of explanatory power or levels of explanation in a philosophy of science course.

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Vredenburg, Kate. A Unificationist Defense of Revealed Preferences
2019, Economics & Philosophy 36.1, 149-169
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Added by: Björn Freter

Abstract: Revealed preference approaches to modelling agents’ choices face two seemingly devastating explanatory objections. The no self-explanation objection imputes a problematic explanatory circularity to revealed preference approaches, while the causal explanation objection argues that, all things equal, a scientific theory should provide causal explanations, but revealed preference approaches decidedly do not. Both objections assume a view of explanation, the constraint-based view, that the revealed preference theorist ought to reject. Instead, the revealed preference theorist should adopt a unificationist account of explanation, allowing her to escape the two explanatory problems discussed in this paper.

Comment: An ingenious and clear defense of the revealed preference interpretation, probably the best one that's possible. A nice opportunity to discuss with students the intellectual gymnastics required in order to defend theoretical commitments of the contemporary economy.

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Vredenburgh, Kate. The Right to Explanation
2021, Journal of Political Philosophy 30 (2):209-229
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Added by: Deryn Mair Thomas
Abstract:

This article argues for a right to explanation, on the basis of its necessity to protect the interest in what I call informed self- advocacy from the serious threat of opacity. The argument for the right to explanation proceeds along the lines set out by an interest- based account of rights (Section II). Section III presents and motivates the moral importance of informed self- advocacy in hierarchical, non- voluntary institutions. Section IV argues for a right to so- called rule- based normative and causal explanations, on the basis of their necessity to protect that interest. Section V argues that this protection comes at a tolerable cost.

Comment: This paper asserts a right to explanation grounded in an interest in informed self-advocacy, the term the author uses to describe a cluster of abilities to represent one's interests and values to decision-makers and to further those interests and values within an institution. Vredenburgh also argues that such form of self-advocacy are necessary for hierarchical, non-voluntary institutions to be legitimate and fair - and it is on these grounds that a person may reasonably reject insitutional set-ups that prevent them from engaging in these abilities. In this sense, Vredenburgh's argument applies to a broader set of problems then simply algorithmic opacity - they may feasibly be applied to cases in which systems (such as bureacratic ones) deny an individual this right to explanation. Therefore, this paper presents an argument which would be useful as further or specialised reading in a variety of classroom contexts, including courses or reading groups addressing technological and algorithmic ethics, basic political rights, bureacratic ethics, as well as more general social and political philosophical courses. It might be interesting, for example, to use it to in an introductory social/political course to discuss with students some of the ethical questions that are particular to a 21st century context. As systems become more complex and individuals become further removed from the institutional decision-making that guides/rules/directs their lives, what right do we have to understand the processes that condition our experience? In what other situations might these rights become challenged?

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