Archive for May, 2017

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“A Fork in the Middle Path: Explaining the Success of Mature Physical Theories” (5/3/17)

May 24, 2017

Shahin Kaveh

Abstract: The problem of explaining the success of science has been debated for a long time. This debate has led not only to different answers to this question, but also to different interpretations of the question itself, each of which calls for a different type of answer. Recently, Stanford has summarized this debate and identified a “Middle Path” when it comes to explaining success, characterized by the commitment that the success of the successful theory must be explained through a systematic relationship between the theory’s constructs and the inner workings of the system, whatever this relationship may be (the Maddy-Wilson principle). However, a survey of the views on the offer shows that only two types of Middle Path explanations have been offered: ones that draw on Truthlikeness, and ones that give up on fleshing out this systematic relationship in any general terms at all. I aim to offer a third way within the Middle Path, in which one can satisfy the Maddy-Wilson principle without drawing on Truthlikeness.

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“A Pluralist View of Biological Individuality” (4/28/17)

May 24, 2017

Haixin Dang

Abstract: In this paper, I focus on one family of views: the so-called monist accounts of biological individuality, which have been most prominently defended by Ellen Clarke (2013) and Peter Godfrey-Smith (2009).  These accounts of biological individuality are monist because they assume that there ought to be one unified concept of the biological individual: there is only one correct way to pick out the fundamental units of the living.  I argue that the monist view is problematic and instead defend a pluralist view of biological individuality.  I argue, first of all, that within the purportedly monist account, the kinds of mechanisms/criteria defended by Clarke and Godfrey-Smith in fact picks out more than the narrow class of entities they believe they have identified.  I then defend a pluralist view by showing that, once we think beyond the scope of population genetics, we will find that there exist many different kinds of biological individuals. 

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“Technique-Driven Research: Clarifying the nature of exploratory experimentation” (4/6/17)

May 24, 2017

David Colaco

Abstract: Recently, historians and philosophers of science have sought to account for experimental research that is not driven by the evaluation of theory, but instead is motivated by the desire to explore.  Along these lines, I discuss how techniques can drive research and allow scientists to explore systems.  I describe the preparation technique CLARITY, which drives cutting-edge microscopy research in neuroscience.  Though technique-driven research is exploratory and experimental, it fails to satisfy the conditions of several popular accounts of exploratory experimentation.  In light of this discrepancy, I critically assess these accounts, and reappraise what conditions are necessary for exploratory research.

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“Incompressible Patterns: CRISPR vs Dennett” (3/30/17)

May 24, 2017

Katie Creel

Abstract: Dennett’s classic paper defines “Real Patterns” as present in data if
“there is a description of the data that is more efficient than the
bit map, whether or not anyone can concoct it.” (Dennett 1991, 34)
However, compressibility is not the right criterion for pattern
realism. A better pattern ontology is one based on informational
relationships between the pattern and the perceiver of the pattern,
whether human, biological, or machine.

A simple compression algorithm such as Huffman coding should be
perfect for Dennett’s purposes. It can compress text into an efficient
lossless binary tree in which letters are assigned unique codes based
on their frequency. Instead, Huffman coding illustrates the problem
with compression as a metric: lack of generalizability. If the
algorithm were only used once, it could compress a novel into one
character: “W” for all of War and Peace. But this would be no
informational savings. What makes compression work is that the “cost”
of the compression algorithm is amortized over many uses.

Further, any discrete chunk of randomness can be recognized as a
pattern if it has the right informational relationship with its
recognizer. Such recognition relationships between random sequences
and detectors occur in genetic material. New tools for genetic
manipulation such as CRISPR use a recognition relationship with
sequences of base pairs to snip and replace precise segments of DNA.
Using case studies, I suggest that we should think of patterns as
representing the informational relationship between pattern and
recognizer.