Workshop: Biases and Values in Science (14 July 2017)
This workshop will be a platform for discussing recent work on the interconnection between (a) different kinds of biases and (b) moral and political values in science and philosophy.
Attendance is free, but registration is required: Alexander.Reutlinger@lrz.uni-muenchen.de.
- Andreas Kapsner (LMU/MCMP)
- Maria Kronfeldner (Central European University)
- Franziska Reinhard (LMU/MCMP)
- Alexander Reutlinger (LMU/MCMP)
- Shanna Slank (University of Wisconsin-Madison/MCMP)
- Daniel Steel (University of British Columbia)
- Alexander Reutlinger (LMU/MCMP)
14 July 2017
|10:00 - 11:00||Daniel Steel: Wishful Thinking and Values in Science|
|11:15 - 12:15||Franziska Reinhard: Epistemically Valuable Research and the Role of Standards in Science|
|12:15 - 14:00||Lunch|
|14:00 - 15:00||Alexander Reutlinger: What Is Epistemically Wrong With Biased Research?|
|15:00 - 16:00||Shanna Slank: Imposters and Frauds: A New Explanation for the Imposter Phenomenon|
|16:00 - 16:30||Coffee Break|
|16:30 - 17:30||Maria Kronfeldner: Thick Concepts, Naked Numbers and Disappearing Evidence – Two Reasons Why the Purist Approach to Thick Concepts in Science Fails|
|17:30 - 18:30||Andreas Kapsner: Wrap-up and General Discussion|
Thick Concepts, Naked Numbers and Disappearing Evidence: Two Reasons Why the Purist Approach to Thick Concepts in Science Fails
Thick concepts are value-laden, i.e., concepts that have an evaluative and a descriptive aspect. The concept of aggression is a standard case in point. When a psychologist writes that “boys are more aggressive than girls” then this is not a purely descriptive claim. Purists claim that science can and should purify such thick concepts, by establishing (what I call) naked numbers, i.e., an operationalized counterpart. An example would be an A-index that objectively measures the respective behavioral trait meant with the term “aggression”, ideally without even involving this value-laden lay term. This talk will present two reasons why the purist approach must fail. (1) Reducing thick concepts to naked numbers has been rejected as a solution for making science value-free (e.g. by Dupré) since the connection to the original conception and thus the values involved (e.g. what lay people call aggression) needs to be made somewhere in the process of knowledge production, so that the knowledge produced stays socially significant, i.e., provides reasons for action. (2) The conceptual decisions in using thick concepts or in reducing them to naked numbers cannot be made objectively (i.e., completely free of bias), since different concepts or operationalizations let one see different evidences. Therefore, whenever a phenomenon is reconstituted and its definition changed, some evidence can be made to disappear. Such disappearance of evidence will be shown to be necessarily biased and often value-laden.top
Much of scientific research is guided by standards and regulations, especially when it comes to clinical trials or risk assessment studies. What can these standards tell us about the epistemic value of the resulting research? Wilholt (2009) identifies the epistemic shortcoming of biased research as the violation of conventional standards accepted in a scientific community. In this talk, I will critically analyze this proposal. In particular, I will argue that it does not allow one to draw a distinction between two types of standards that guide research: actual conventions on the one hand, and methodological consequences resulting from background knowledge of the target on the other. I will provide a concrete example of a risk assessment study and argue that, while both kinds of standards have their role to play in scientific inquiries, only the latter are a guide to the epistemic value of research.top
Biased research occurs frequently in the sciences. It is a major challenge for present-day philosophy of science to improve our understanding of biases in science. I will address on the following question: what precisely is epistemically defective (that is, unjustified or irrational) about biased research? In light of a specific example of a preference bias, I defend the claim that biased research is epistemically defective because biased research fails to provide evidence for the hypothesis to be tested, contrary to the assertions of the scientists carrying out biased research projects. I support this claim by drawing on major accounts of evidence and confirmation.top
Within the literature on Imposter Phenomenon (“IP”) (or “Imposter Syndrome”), discussion of the phenomenon focuses exclusively on explanations that cite individual-centric causes – e.g., that IP-individuals have inaccurate beliefs about the extent to which they are causally responsible for their successes. In this talk, I argue that this focus is overly narrow and results in an unsatisfactory picture of the phenomenon insofar as it neglects the possibility that IP-individuals’ environments (including non-IP-individuals) may causally contribute to the presence of the phenomenon. I claim further that this neglect is especially important if it is the case that non-IP-individuals also have inaccurate beliefs about the causal structure of their successes. Here, I draw on Alessandra Tanesin’s work on intellectual arrogance as I propose a relational-environmental hypothesis about the causal underpinnings of IP. I then conclude by speculating about the social and institutional features of philosophy (as compared to other professions both within and outside of academia) that may make it especially vulnerable to IP (given the explanation I propose). In particular, I consider whether philosophy is especially biased towards the epistemically arrogant.top
This article examines the concept of wishful thinking in philosophical literature on science and values. It suggests that this term tends to be used in an overly broad manner that fails to distinguish between separate types of bias, mechanisms that generate biases, and general theories that might explain those mechanisms. I explain how confirmation bias is distinct from wishful thinking, and why it is more useful for examining the relationship between cognitive bias and beliefs about the existence of injustices.
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