7 de noviembre de 2016

CfP: Inferentialism, Bayesianism, and Scientific Explanation

The Munich Center for Mathematical Philosophy invites abstracts for the following event:
Inferentialism, Bayesianism, and Scientific Explanation
MCMP, LMU Munich
January 25-26, 2017

What makes a given explanation successful? Many philosophers of science have tried to answer this question, but there is no consensus answer. In this workshop, we will assess the prospects of taking a novel approach to answering this question. Specifically, we will discuss whether and how an inferentialist account of explanation can be combined with Bayesian resources to deliver an adequate account of scientific explanation. This involves assessing not only whether the inferentialist can capture aspects of explanation that are often thought to resist Bayesian treatment (e.g., Inference to the Best Explanation and the asymmetry of explanation), but also whether inferentialism avoids problems that are thought to plague ontic accounts of explanation (e.g., an untenable insensitivity to contextual and pragmatic factors). Since it may not be entirely clear what the commitments of the inferentialist are in the context of scientific explanation, we likewise hope to consider what exactly it means to be an inferentialist about explanation.

Call for extended abstracts

We invite submissions of extended abstracts for talks to be presented at a workshop on “Inferentialism, Bayesianism and Scientific Explanation.” (Workshop details, including a description of themes that will be covered, can be found on the website, http://www.mcmp.philosophie.uni-muenchen.de/events/workshops/container/inf_bay_scie-workshop/index.html.) Submissions should include a title and an extended abstract (about 500 words including references) and should be prepared for blind peer review. Please send all submissions to Reuben.Stern@lrz.uni-muenchen.de by 30 November. All submissions will receive a response by 7 December.

Dates and Deadines

Submission deadline: 30 November 2016
Workshop: 25-26 January 2017