Deprecated: wp_make_content_images_responsive is deprecated since version 5.5.0! Use wp_filter_content_tags() instead. in /home/diversityreading/public_html/wp-includes/functions.php on line 4777
Full text Read free See used
Alexandrova, Anna, , Robert Northcott. It’s just a feeling: why economic models do not explain
2013, Journal of Economic Methodology, 20(3), 262-267
Expand entry
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.

Export citation in BibTeX format
Export text citation
View this text on PhilPapers
Export citation in Reference Manager format
Export citation in EndNote format
Export citation in Zotero format
Share on Twitter Share on Facebook Share on Google Plus Share on Pinterest Share by Email More options
Full text Read free See used
Alexandrova, Anna, , . Making Models Count
2008, Philosophy of Science 75(3): 383-404.
Expand entry
Added by: Nick Novelli, Contributed by:

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.

Export citation in BibTeX format
Export text citation
View this text on PhilPapers
Export citation in Reference Manager format
Export citation in EndNote format
Export citation in Zotero format
Share on Twitter Share on Facebook Share on Google Plus Share on Pinterest Share by Email More options
Full text Read free See used
Blanchette, Patricia, , . Models and Modality
2000, Synthese 124(1): 45-72.
Expand entry
Added by: Berta Grimau, Contributed by: Patricia Blanchette

Abstract: This paper examines the connection between model-theoretic truth and necessary truth. It is argued that though the model-theoretic truths of some standard languages are demonstrably “necessary” (in a precise sense), the widespread view of model-theoretic truth as providing a general guarantee of necessity is mistaken. Several arguments to the contrary are criticized.

Comment: This text would be best used as secondary reading in an intermediate or an advanced philosophy of logic course. For example, it can be used as a secondary reading in a section on the connection between model-theoretic truth and necessary truth.

Export citation in BibTeX format
Export text citation
View this text on PhilPapers
Export citation in Reference Manager format
Export citation in EndNote format
Export citation in Zotero format
Share on Twitter Share on Facebook Share on Google Plus Share on Pinterest Share by Email More options
Full text Read free See used
Bokulich, Alisa, , . How scientific models can explain
2009, Synthese 180(1): 33-45.
Expand entry
Added by: Laura Jimenez, Contributed by:

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.

Export citation in BibTeX format
Export text citation
View this text on PhilPapers
Export citation in Reference Manager format
Export citation in EndNote format
Export citation in Zotero format
Share on Twitter Share on Facebook Share on Google Plus Share on Pinterest Share by Email More options
Full text Read free See used
Cartwright, Nancy, , . How the Laws of Physics Lie
1983, Oxford University Press.
Expand entry
Added by: Laura Jimenez, Contributed by:

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.

Export citation in BibTeX format
Export text citation
View this text on PhilPapers
Export citation in Reference Manager format
Export citation in EndNote format
Export citation in Zotero format
Share on Twitter Share on Facebook Share on Google Plus Share on Pinterest Share by Email More options
Full text Read free See used
Chuang, Liu, , . Models, fiction and fictional models
2014, In Guichun Guo, Chuang Liu (eds.) Scientific Explanation and Methodology in Science, World Scientific Publishing Co.
Expand entry
Added by: Laura Jimenez, Contributed by:

Summary: The use of models to scientifically represent and study reality is widely recognized with good reasons as indispensable for the practice of science. Because models, unlikely pure verbal representation, are justifiably regarded as vehicles of representation that are not truth-apt, philosophical questions are natural raised concerning the nature of such vehicles and how they represent. A sizeable literature generated in recent years explores the possibility that ”scientific models are works of fiction”. Idealization and other similar strategies are often taken to be the means by which models are made. Arguing against this last claim, the thesis of this article is that most models in science are not fictional. The author argues against the idea that idealization is the means by which models of typically unobservable systems or mechanisms are made.

Comment: Interesting paper about scientific modeling and scientific representation. Useful for undergraduates and postgraduates courses in philosophy of science.

Export citation in BibTeX format
Export text citation
View this text on PhilPapers
Export citation in Reference Manager format
Export citation in EndNote format
Export citation in Zotero format
Share on Twitter Share on Facebook Share on Google Plus Share on Pinterest Share by Email More options
Full text Read free See used
Elgin, Catherine, , . Understanding and The Facts
2007, Philosophical Studies 132: 33-42.
Expand entry
Added by: Giada Fratantonio, Contributed by:

Abstract: If understanding is factive, the propositions that express an understanding are true. I argue that a factive conception of understanding is unduly restrictive. It neither reflects our practices in ascribing understanding nor does justice to contemporary science. For science uses idealizations and models that do not to mirror the facts. Strictly speaking, they are false. By appeal to exemplification, I devise a more generous, flexible conception of understanding that accommodates science, reflects our practices, and shows a sufficient but not slavish sensitivity to the facts.

Comment: This paper could be used in an undergraduate or graduate course on epistemology, philosophy of science, or any area in which the nature of understanding is at issue. The paper is quite brief and not particularly technical. It makes a good case for a claim that initially sounds very counterintuitive, so can serve as a good prompt for a discussion.

Export citation in BibTeX format
Export text citation
View this text on PhilPapers
Export citation in Reference Manager format
Export citation in EndNote format
Export citation in Zotero format
Share on Twitter Share on Facebook Share on Google Plus Share on Pinterest Share by Email More options
Full text Read free See used
Hesse, Mary, , . Models and analogies in science
1966, University of Notre dame Press.
Expand entry
Added by: Laura Jimenez, Contributed by:

Summary: In this book Hesse argues, contra Duhem, that models and analogies are integral to understanding scientific practice in general and scientific advancement in particular, especially how the domain of a scientific theory is extended and how theories generate genuinely novel predictions. Hesse thinks that, in order help us to understand a new system or phenomenon, we will often create an analogical model that compares this new system or phenomenon with a more familiar system or phenomenon. Hesse distinguishes different types of analogies according to the kinds of similarity relations in which two objects enter: Positive analogies, negative analogies, and neutral analogies. The crux of the argument is that the recognition of similarities of meaning between paired terms and the recognition of similar causal relations within two analogies plays an essential role in theoretical explanation and prediction in science.

Comment: This book is an accessible introduction to the topic of scientific modelling. Useful for teaching in undergraduate courses.

Export citation in BibTeX format
Export text citation
View this text on PhilPapers
Export citation in Reference Manager format
Export citation in EndNote format
Export citation in Zotero format
Share on Twitter Share on Facebook Share on Google Plus Share on Pinterest Share by Email More options
Full text Read free See used
Hesse, Mary, , . Models in Physics
1953, British Journal for the Philosophy of Science 4(15): 198-214.
Expand entry
Added by: Laura Jimenez, Contributed by:

Summary: In this article Hesse defends the idea that scientific theories are hypothetico-deductive in form. She examines this hypothetico-deductive method by considering some examples from nineteenth-century mathematical physics. By means of these examples she brings out two points about scientific hypothesis. The first is that mathematical formalisms, when used as hypotheses in the description of physical phenomena, may function like the mechanical models of an earlier stage in physics, without having in themselves any mechanical or other physical interpret. The second point is that most physicists do not regard models as literal descriptions of nature, but as standing in a relation of analogy to nature.

Comment: A really good paper about models in science, mathematical formalism and hypothesis. Highly recomended for postgraduates studying philosophy of physics, although it could also be readable by undergraduates (last years) with previous knowledge of scientific modelling.

Export citation in BibTeX format
Export text citation
View this text on PhilPapers
Export citation in Reference Manager format
Export citation in EndNote format
Export citation in Zotero format
Share on Twitter Share on Facebook Share on Google Plus Share on Pinterest Share by Email More options
Full text Read free See used
Hesse, Mary, , . The Hunt for Scientific Reason
1980, PSA: Proceedings of the Biennial Meeting of the Philosophy of Science Association 1980: 3-22.
Expand entry
Added by: Laura Jimenez, Contributed by:

Abstract: The thesis of underdetermination of theory by evidence has led to an opposition between realism and relationism in philosophy of science. Various forms of the thesis are examined, and it is concluded that it is true in at least a weak form that brings realism into doubt. Realists therefore need, among other things, a theory of degrees of confirmation to support rational theory choice. Recent such theories due to Glymour and Friedman are examined, and it is argued that their criterion of “unification” for good theories is better formulated in Bayesian terms. Bayesian confirmation does, however, have consequences that tell against realism. It is concluded that the prospects are dim for scientific realism as usually understood.

Comment: Good article to study in depth the concepts of realism, underdetermination, confirmation and Bayesian theory. It will be most useful for postgraduate students in philosophy of science.

Export citation in BibTeX format
Export text citation
View this text on PhilPapers
Export citation in Reference Manager format
Export citation in EndNote format
Export citation in Zotero format
Share on Twitter Share on Facebook Share on Google Plus Share on Pinterest Share by Email More options
Full text Read free See used
Leonelli, Sabina, , . What distinguishes data from models?
2019, European Journal for Philosophy of Science 9 (2):22.
Expand entry
Added by: Sara Peppe, Contributed by:

Abstract: I propose a framework that explicates and distinguishes the epistemic roles of data and models within empirical inquiry through consideration of their use in scientific practice. After arguing that Suppes’ characterization of data models falls short in this respect, I discuss a case of data processing within exploratory research in plant phenotyping and use it to highlight the difference between practices aimed to make data usable as evidence and practices aimed to use data to represent a specific phenomenon. I then argue that whether a set of objects functions as data or models does not depend on intrinsic differences in their physical properties, level of abstraction or the degree of human intervention involved in generating them, but rather on their distinctive roles towards identifying and characterizing the targets of investigation. The paper thus proposes a characterization of data models that builds on Suppes’ attention to data practices, without however needing to posit a fixed hierarchy of data and models or a highly exclusionary definition of data models as statistical constructs.

Comment: This article deepens the role of model an data in the scientific investigation taking into account the scientific practice. Obviously, a general framework of the themes the author takes into account is needed.

Export citation in BibTeX format
Export text citation
View this text on PhilPapers
Export citation in Reference Manager format
Export citation in EndNote format
Export citation in Zotero format
Share on Twitter Share on Facebook Share on Google Plus Share on Pinterest Share by Email More options
Full text Read free See used
Morrison, Margaret, , . Spin: All is not what it seems
2007, Studies in History and Philosophy of Science Part B 38(3): 529-55.
Expand entry
Added by: Laura Jimenez, Contributed by:

Abstract: Spin is typically thought to be a fundamental property of the electron and other elementary particles. Although it is defined as an internal angular momentum much of our understanding of it is bound up with the mathematics of group theory. This paper traces the development of the concept of spin paying particular attention to the way that quantum mechanics has influenced its interpretation in both theoretical and experimental contexts. The received view is that electron spin was discovered experimentally by Stern and Gerlach in 1921, 5 years prior to its theoretical formulation by Goudsmit and Uhlenbeck. However, neither Goudsmit nor Uhlenbeck, nor any others involved in the debate about spin cited the Stern-Gerlach experiment as corroborating evidence. In fact, Bohr and Pauli were emphatic that the spin of a single electron could not be measured in classical experiments. In recent years experiments designed to refute the Bohr-Pauli thesis and measure electron spin have been carried out. However, a number of ambiguities surround these results – ambiguities that relate not only to the measurements themselves but to the interpretation of the experiments. After discussing these various issues the author raises some philosophical questions about the ontological and epistemic status of spin.

Comment: The goal of the paper is to uncover and isolate how spin presents problems for traditional realism and to illustrate the power that theories like quantum mechanics have for shaping both philosophical questions and answers. It is adequate for higher-level postgraduate courses in Philosophy of Science.

Export citation in BibTeX format
Export text citation
View this text on PhilPapers
Export citation in Reference Manager format
Export citation in EndNote format
Export citation in Zotero format
Share on Twitter Share on Facebook Share on Google Plus Share on Pinterest Share by Email More options
Full text Read free See used
Morrison, Margaret and, , Mary S. Morgan. Models as mediating instruments
1999, In M. S. Morgan and M. Morrison (eds.), Models as Mediators: Perspectives on Natural and Social Science. Cambridge University Press.
Expand entry
Added by: Jamie Collin, Contributed by:

Summary: Morrison and Morgan argue for a view of models as ‘mediating instruments’ whose role in scientific theorising goes beyond applying theory. Models are partially independent of both theories and the world. This autonomy allows for a unified account of their role as instruments that allow for exploration of both theories and the world.

Comment: Useful as a primary or secondary reading in an advanced undergraduate course on philosophy of science, particularly within a section on scientific modeling. The paper is particularly useful in teaching because it is not unduly technical.

Export citation in BibTeX format
Export text citation
View this text on PhilPapers
Export citation in Reference Manager format
Export citation in EndNote format
Export citation in Zotero format
Share on Twitter Share on Facebook Share on Google Plus Share on Pinterest Share by Email More options
Full text Read free See used
Nelson, Julie, , . Feminism and economics
1995, Journal of Economic Perspectives, 9(2), 131-148.
Expand entry
Added by: Simon Fokt, Contributed by: Patricia Rich

Introduction: An article in The Chronicle of Higher Education of June 30, 1993, reported, “Two decades after it began redefining debates” in many other disciplines, “feminist thinking seems suddenly to have arrived in economics.” Many economists, of course, did not happen to be in the station when this train arrived, belated as it might be. Many who might have heard rumor of its coming have not yet learned just what arguments are involved or what it promises for the refinement of the profession. The purpose of this essay is to provide a low-cost way of gaining some familiarity.

Comment: This text provides a good overview, as well as an argument regarding how the field of economics reflects masculine values, and how the field could be improved by removing this bias. It makes sense to read the text with students who have some familiarity with economics itself. It should be noted that the field of economics actually has changed in some of the ways the author recommends, since the time of publication, but the article is still relevant and provokes plenty of discussion.

Export citation in BibTeX format
Export text citation
View this text on PhilPapers
Export citation in Reference Manager format
Export citation in EndNote format
Export citation in Zotero format
Share on Twitter Share on Facebook Share on Google Plus Share on Pinterest Share by Email More options
Full text Read free See used
Nersessian, Nancy, , . Creating Scientific Concepts
2008, MIT Press.
Expand entry
Added by: Laura Jimenez, Contributed by:

Publisher’s Note: How do novel scientific concepts arise? In Creating Scientific Concepts, Nancy Nersessian seeks to answer this central but virtually unasked question in the problem of conceptual change. She argues that the popular image of novel concepts and profound insight bursting forth in a blinding flash of inspiration is mistaken. Instead, novel concepts are shown to arise out of the interplay of three factors: an attempt to solve specific problems; the use of conceptual, analytical, and material resources provided by the cognitive-social-cultural context of the problem; and dynamic processes of reasoning that extend ordinary cognition. Focusing on the third factor, Nersessian draws on cognitive science research and historical accounts of scientific practices to show how scientific and ordinary cognition lie on a continuum, and how problem-solving practices in one illuminate practices in the other.

Comment: Nersessian’s book has a two-fold foundation, first, the empirical analysis of two cases of scientific thinking (one from Maxwell and one from a verbal protocol of a scientist); second, philosophical and cognitive analysis of the overall picture of meaning change in science that is the result of her work. The book presents her argument via an introductory chapter, followed by five chapters that develop the argument. Chapter 4 is particularly interesting for the cognitive-scientist: in this chapter Nersessian develops her account of the basic cognitive processes that underlie model-based reasoning. The new approach to mental modeling and analogy, together with Nersessian’s cognitive-historical approach, make Creating Scientific Concepts equally valuable to cognitive science and philosophy of science. The book is accessible and well-written, and should be a relatively quick read for anyone with a previous background in the mentioned fields. It is mainly recommended for postgraduate courses.

Export citation in BibTeX format
Export text citation
View this text on PhilPapers
Export citation in Reference Manager format
Export citation in EndNote format
Export citation in Zotero format
Share on Twitter Share on Facebook Share on Google Plus Share on Pinterest Share by Email More options