Papers by Sandra Mitchell
Through the Fractured Looking Glass
Philosophy of Science, Dec 1, 2020
I argue that diversity and pluralism are valuable not just for science but for philosophy of scie... more I argue that diversity and pluralism are valuable not just for science but for philosophy of science. Given the partiality and perspectivism of representation, pluralism preserving integration can increase accuracy. Perspectivism is often supported by appeal to visual representation. I draw further insights from multimodel sensory integration for understanding experiment-based predictions of protein structure. The epistemic lessons learned from the scientific case also apply to philosophy of science itself. Finally, I suggest that a critical, nuanced philosophical view of legitimate sources of pluralism in science has an important role to play in public discourse.
The Pragmatist Challenge
Oxford University Press eBooks, Feb 23, 2023
Pragmatism for Philosophy of Science
Oxford University Press eBooks, Feb 23, 2023
Human perspectives in health sciences and technology, 2020
The question, "Will science remain human?" expresses a worry that deep learning algorithms will r... more The question, "Will science remain human?" expresses a worry that deep learning algorithms will replace scientists in making crucial judgments of classification and inference and that something crucial will be lost if that happens. Ever since the introduction of telescopes and microscopes humans have relied on technologies to "extend" beyond human sensory perception in acquiring scientific knowledge. In this paper I explore whether the ways in which new learning technologies "extend" beyond human cognitive aspects of science can be treated instrumentally. I will consider the norms for determining the reliability of a detection instrument, nuclear magnetic resonance spectroscopy, in predicting models of protein atomic structure. Do the same norms that apply in that case be used to judge the reliability of Artificial Intelligence deep learning algorithms? Philosophers of science explore and explain how scientists acquire knowledge of nature. Most have agreed that we must give up oversimplified accounts of direct experience of "the given" (which is the English translation of the Latin datum or date) and overambitious requirements that scientific knowledge be restricted to claims that are universally true and exceptionless. As a result, many factors that enter into scientific practice have been exposed as relevant to our understanding of how knowledge of nature is constructed, how it is judged, and how it is used. For example, which observations are judged to provide reliable data? What features of phenomena are represented in an explanatory model? In which contexts and for what purposes will an explanatory model be adequate? To be sure, science is a product of human activity, both causally, through experience and experiment and inferentially, though logic, calculation, and simulation. What is investigated and how it is investigated, is shaped by decisions which are themselves dependent on and constrained by human pragmatic goals, like curing diseases, or understanding the expanse of the universe.
A Critical Reflection on Automated Science, 2020
The question, "Will science remain human?" expresses a worry that deep learning algorithms will r... more The question, "Will science remain human?" expresses a worry that deep learning algorithms will replace scientists in making crucial judgments of classification and inference and that something crucial will be lost if that happens. Ever since the introduction of telescopes and microscopes humans have relied on technologies to "extend" beyond human sensory perception in acquiring scientific knowledge. In this paper I explore whether the ways in which new learning technologies "extend" beyond human cognitive aspects of science can be treated instrumentally. I will consider the norms for determining the reliability of a detection instrument, nuclear magnetic resonance spectroscopy, in predicting models of protein atomic structure. Do the same norms that apply in that case be used to judge the reliability of Artificial Intelligence deep learning algorithms? Philosophers of science explore and explain how scientists acquire knowledge of nature. Most have agreed that we must give up oversimplified accounts of direct experience of "the given" (which is the English translation of the Latin datum or date) and overambitious requirements that scientific knowledge be restricted to claims that are universally true and exceptionless. As a result, many factors that enter into scientific practice have been exposed as relevant to our understanding of how knowledge of nature is constructed, how it is judged, and how it is used. For example, which observations are judged to provide reliable data? What features of phenomena are represented in an explanatory model? In which contexts and for what purposes will an explanatory model be adequate? To be sure, science is a product of human activity, both causally, through experience and experiment and inferentially, though logic, calculation, and simulation. What is investigated and how it is investigated, is shaped by decisions which are themselves dependent on and constrained by human pragmatic goals, like curing diseases, or understanding the expanse of the universe.
Understanding Perspectivism, 2019
This paper explores consequences of the perspectival nature of representation. In particular, it ... more This paper explores consequences of the perspectival nature of representation. In particular, it considers the relationships among multiple representational models of the same phenomenon. The epistemic value of integrative pluralism is defended by appeal to an example from experimentally based models protein structure and multi-sensory cognitive/neural integration.
The object world of the social sciences is complex, historical and self-reflexive. It generates n... more The object world of the social sciences is complex, historical and self-reflexive. It generates nonlinear effects, it is unique, and it is able to understand the theories developed about it and respond to them intentionally. Recognizing the emergent, historically contingent and self-organizing nature of the social world, and developing responsive policy vehicles for managing its complexity, requires a shift in our conception of science in general and of economics in particular. Die Gegenstandswelt der Sozialwissenschaften ist komplex, historisch und reflexiv. Sie unterliegt nicht-linearen Effekten, es gibt sie immer nur einmal, sie versteht die über sie entwickelten Theorien und reagiert auf sie mit eigenem Willen. Den emergenten, historisch kontingenten und selbstorganisierenden Charakter der sozialen Welt zu erkennen und Politikinstrumente zu finden, die ihrer Komplexität gerecht werden, erfordert ein verändertes Konzept von Wissenschaft im Allgemeinen und von Wirtschaftstheorie i...
Self Organization and Adaptation in Insect Societies
PSA: Proceedings of the Biennial Meeting of the Philosophy of Science Association
Page 1. Self Organization and Adaptation in Insect Societies1 Robert E. Page, Jr. and Sandra D. M... more Page 1. Self Organization and Adaptation in Insect Societies1 Robert E. Page, Jr. and Sandra D. Mitchell University of California, Davis and University of California, San Diego 1. Introduction The social organization of insect ...
Modes of Explanation: Complex Phenomena
Modes of Explanation, 2014
Philosophy of Science, Jun 1, 2000
JSTOR is a not-for-profit service that helps scholars, researchers, and students discover, use, a... more JSTOR is a not-for-profit service that helps scholars, researchers, and students discover, use, and build upon a wide range of content in a trusted digital archive. We use information technology and tools to increase productivity and facilitate new forms of scholarship. For more information about JSTOR, please contact
Exporting Causal Knowledge in Evolutionary and Developmental Biology
Philosophy of Science, 2008
Ceteris paribus laws
Page 1. CETERIS PARIBUS LA1 Edited by JOHN EARMAN, CLARK CLYMOUR ANDSANDRA MITCHELL Kluwer Academ... more Page 1. CETERIS PARIBUS LA1 Edited by JOHN EARMAN, CLARK CLYMOUR ANDSANDRA MITCHELL Kluwer Academic Publishers Page 2. rz -.&&*^*&Q Page 3. Page 4. Page 5. Ceterus Paribus Laws Edited by John Earman ...
The Import of Uncertainty
Modularity—More Than a Buzzword? Modularity in Development and Evolution Gerhard Schlosser and Günter P. Wagner , eds Chicago: University of Chicago Press, 2003 (600 pp; $35.00 pbk; ISBN 0226738558) Modularity: Understanding the Development and Evolution of Natural Complex Systems Werner Callebau...
Biological Theory, 2006
Ceterus Paribus Laws, 2002
It has been claimed that ceteris paribus laws, rather than strict laws are the proper aim of the ... more It has been claimed that ceteris paribus laws, rather than strict laws are the proper aim of the special sciences. This is so because the causal regularities found in these domains are exception-ridden, being contingent on the presence of the appropriate conditions and the absence of interfering factors. I argue that the ceteris paribus strategy obscures rather than illuminates the important similarities and differences between representations of causal regularities in the exact and inexact sciences. In particular, a detailed account of the types and degrees of contingency found in the domain of biology permits a more adequate understanding of the relations among the sciences.
The Superorganism Metaphor: Then and Now
Biology as Society, Society as Biology: Metaphors, 1995
Apidologie, 1998
Division of labor is one of the most fascinating phenomena found in social insects and is probabl... more Division of labor is one of the most fascinating phenomena found in social insects and is probably responsible for their tremendous ecological success. We show how major features of this division of labor may represent self-organized properties of a complex system where individuals share an information data base (a stimulus environment), make independent decisions about how to respond to the current condition of that data base (stimulus environment), and alter the data base by their actions. We argue that division of labor can emerge from such systems even without a history of natural selection, that in fact such ordered behavior is an inescapable property of group living. We then show how natural selection can operate on self-organized complex systems (social organization
Philosophy of Science, 2014
Multilevel research strategies characterize contemporary molecular inquiry into biological system... more Multilevel research strategies characterize contemporary molecular inquiry into biological systems. We outline conceptual, methodological and explanatory dimensions of these multilevel strategies in microbial ecology, systems biology, protein research, and developmental biology. This review of emerging lines of inquiry in these fields suggests that multilevel research in molecular life sciences has significant implications for philosophical understandings of explanation, modelling, and representation.
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Papers by Sandra Mitchell