Archive for the ‘Science in Practice’ Category

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Randomization and its constraints: A critical look at the current reserach practices in social psychology

August 29, 2014

Taku Iwatsuki

Abstract: In this talk, I investigate the importance of randomization in the context of social psychological research. I compare the costs and the benefits of randomization, and argue that the current research practices in social psychology seem to put too much emphasis on the use of randomization. The talk will be structured as follows: First, I briefly explain what randomization is and what role it typically plays in social psychological research. Next, I explore its methodological benefits in the context of causal inference through critical examination of arguments for randomization. Then, I investigate what the costs of randomization are, focusing on the constraints it imposes on other aspects of research design and eventually on psychological theorizing based on such research. Finally, comparing these costs and benefits, I conclude that the use of more diverse research designs with less emphasis on the use of randomization seems to be necessary for developing better psychological theories.

 

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Realism, Instrumentalism, and Uses of Models in Science

January 13, 2014

Yoichi Ishida

Abstract: This paper argues in support of Howard Stein’s idea that in successful scientific research, a scientist uses a model according to the methodological principles of realism and instrumentalism despite the tension that they create among the scientist’s uses of the model over time. After giving precise formulations of the realist and instrumentalist methodological principles, I argue for my thesis through a detailed analysis of successful scientific research done by Seymour Benzer in the 1950s and 60s. I then argue that epistemic realism or epistemic instrumentalism—forms of realism and instrumentalism familiar in the philosophical literature—by itself prohibits a scientist from adopting both the realist and instrumentalist methodological principles. Stein’s conjecture thus poses new challenges to realists and instrumentalists, and I briefly suggest possible avenues of response that realists and instrumentalists may take.
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Day-O-WIPs Beta

June 17, 2013

The second installment of the “Day-O-WIPs” series:

“Toward a Philosophy of Synthetic Science” Julia Bursten

“Can Genes be Darwinian Individuals?” Haixin Dang

“Group Theory or No Group Theory: Understanding Atomic Spectra” Joshua Hunt

“Dynamical Models: A Type of Mathematical Explanation in Neuroscience and Medicine” Lauren Ross

“The Wax & the Mechanical Mind: Reexamining Hobbes’s Objections to Descartes’ Meditations” Marcus Adams

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Toward a Philosophy of Synthetic Science: Lessons from Nanosynthesis

May 30, 2013

Julia Bursten

Philosophers of science have spilled much ink discussing how scientific theories and models work. A vast majority of the theories and models they have studied have come from parts of science whose theories only describe the natural world, such as general relativity, quantum field theories, or population genetics. Consequently, philosophers of science have often overlooked the structure and function of theories and models in “synthetic” sciences such as chemistry, materials science, and engineering, where part of scientific practice is making something new, over and above describing what is already out there. Getting clearer on how models and theories work in synthetic sciences will benefit practitioners of those sciences as they develop new theories and models, as well as illuminating recent debates in philosophy of science about the structure and function of scientific theories and models.

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Surface Tensions: Challenges to Philosophy of Science from Nanoscience

January 31, 2013

Julia Bursten

Abstract: A traditional view of the structure of scientific theories, on which philosophers of science have based their accounts of explanation, modeling, and inter-theory relations, holds that scientific theories are composed of universal natural laws coupled with initial and boundary conditions. In this picture, universal laws play the most significant role in scientific reasoning. Initial and boundary conditions are rarely differentiated and their role in reasoning is largely overlooked. In this talk, I use the problem of modeling surfaces in nanoscience to show why this dismissal is deeply problematic both for philosophers of science and for scientists themselves.

In macroscopic-scale modeling, surfaces are treated as boundaries in the mathematical sense-that is, as infinitesimally thin borders of a system that confine its interior. As such, surface structure and behavior is usually modeled in an idealized manner that ignores most of the physics and chemistry occurring there. At the nanoscale, however, the structure and behavior of these surfaces significantly constrains the structure and behavior of the interior in more complex ways. Three important conclusions emerge:

1. The very concept surface changes as a function of scale, and other central concepts in nanoscience also behave in this scale-dependent manner.
2. The traditional view of theory described above does not adequately capture the nature of nanomaterials modeling, which requires attention to multiple models constructed at different characteristic scales. These component models do not comport well with a single set of universal laws, as the standard view suggests. Instead, boundary behaviors become crucial and models are designed to capture these behaviors.
3. The projects of nanomaterials modeling and synthesis dictate that divisions between boundaries and interiors must be continually adjusted. Overlooking this problem has led to failures of experimental design and interpretation of data.