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Yet Another Great Workshop on Idealization, Causation, and Explanation (27 May 2017)

Speakers

Organizers

Program

TimeEvent
11:00 - 11:45 Casey McCoy: Understanding the Progress of Science
11:45 - 12:30 Roland Poellinger: Analogy, Extrapolation, and Causal Similarity
12:30 - 14:00 Lunch
14:00 - 14:45 Pauline van Wierst: The Paradox of Phase Transitions in the Light of Constructive Mathematics
14:45 - 15:30 Patricia Palacios: Had We But World Enough, and Time... But We Don’t! Justifying the Thermodynamic and Infinite-Time Limits in Statistical Mechanics
15:30 - 16:00 Coffee Break
16:00 - 16:45 Ben Eva and Reuben Stern: Causal Explanatory Power and Its Limits
16:45 - 17:30 Michael Strevens: Idealization: From Explanation to Prediction
17:30 - 18:00 Coffee Break
18:00 - 18:45 General Discussion

Abstracts

Causal Explanatory Power and Its Limits

Ben Eva and Reuben Stern

In recent work, we use structural equation models to propose and defend a framework for assessing the explanatory power of causal explanations. Here, we evaluate how and whether our framework can be generalized to apply to non-causal explanations that are backed by asymmetric synchronic dependency relations (e.g., supervenience relations). Then we ask whether there are kinds of explanatory success that are not tracked by considerations of explanatory power, and briefly consider how and whether structural equation models can be used to capture these kinds of success.top

Understanding the Progress of Science

Casey McCoy

We propose a novel analysis of the progress of science based substantially on the problem-solving approaches advocated by Kuhn and Laudan. Unlike these authors, however, we explicitly connect problem-solving to a particular epistemological aim of science, namely understanding, a distinctive epistemological good which we characterize as the possession of a kind of ability. In this we follow approaches common in virtue epistemology. We argue that there is a natural connection between such an account of understanding and the problem-solving approach to progress, especially in that solving scientific problems serves as a robust indication of understanding, yet does not reduce to the mere acquisition of knowledge.top

Had We But World Enough, and Time... But We Don’t! Justifying the Thermodynamic and Infinite-Time Limits in Statistical Mechanics

Patricia Palacios

Recently, there has been a fervent discussion around the use of the thermodynamic limit in the theory of phase transitions. On the other hand, the use of the infinite-time limit in statistical mechanics has not received the same attention in the philosophical literature. In this talk, I will compare the use of the thermodynamic limit in the theory of phase transitions with the infinite-time limit in the explanation of the approach to equilibrium. In the case of phase transitions, I will argue that the use of the thermodynamic limit can be justified pragmatically, since this limit is controllable. However, I will contend that the justification of the infinite-time limit is less straightforward. Even so, I will suggest a way to provide a pragmatic justification for the infinite-time limit. This goes back to the work of Ehrenfest and Ehrenfest (2002 [1911]), who pointed out the necessity of adapting the time-scale of the analysis to the phenomenon we want to describe. I will show that an adequate choice of time-scale can, in many cases, help define a topology in which the limit actually converges. I will show, furthermore, that in these cases, finite time averages take the same values as the infinite time averages.top

Analogy, Extrapolation, and Causal Similarity

Roland Poellinger

Analogical arguments are ubiquitous vehicles of knowledge transfer in science and medicine, especially for the purpose of extrapolating causal behavior from observed phenomena to hypothetical target systems. If analogy is to be based on similarity considerations, though, causal knowledge about study and target system must be made comparable. In this talk I will explore some ideas on how similarity of causal models can possibly be captured in a formal way.top

Idealization: From Explanation to Prediction

Michael Strevens

Every model leaves out or distorts some factors that are causally connected to its target phenomena -- the phenomena that it seeks to predict or explain. If we want to make predictions, and we want to base decisions on those predictions, what is it safe to omit or to simplify, and what ought a causal model to capture fully and correctly? A schematic answer: the factors that matter are those that make a difference to the target phenomena. There are several ways to understand the notion of difference-making. Which are the most useful to the forecaster, to the decision-maker? This paper advances a view.top

The Paradox of Phase Transitions in the Light of Constructive Mathematics

Pauline van Wierst

In this talk we will discuss the “paradox of phase transitions”: our best (statistical mechanical) theories of phase transitions seem to tell us that phase transitions require an infinite system, whereas we know – given the atomic theory of matter - that the systems around us, which we see display phase transitions every day, are finite. In all of the many noteworthy contributions to the philosophical debate on phase transitions (e.g. Bangu 2015, Batterman 2005, Butterfield 2011, Callender 2001, Norton 2012, 2014), the classical mathematical framework in which these theories of phase transitions are formulated is left unquestioned. However, classical mathematics - in virtue of the notion of actual infinity upon which it is based – is highly idealized and can therefore be considered itself already philosophically problematic – especially within the context of the statistical mechanics of bounded systems. I maintain that, to fully understand the paradox of phase transitions - and, consequently, its philosophical significance -, we should understand to which extent the idealization contained in classical mathematics contributes to this paradox.
To this aim, we will consider in this talk a mathematical framework alternative to the classical one: constructivism. Constructive mathematics is motivated by the idea that actual infinity is not indispensable for mathematics. We will consider whether this rejection of actual infinity makes constructive mathematics - at least from a philosophical point of view - a better tool than classical mathematics in the context of statistical-mechanical theories of phase transitions - meaning that when these theories are formulated within constructive mathematics (some of) the philosophical problems which arise in their classical counterparts do not occur.

References

  • Bangu, S. (2015), Why does water boil? Fictions in scientific explanation, in U. M. et al., ed., ‘Recent Developments in Philosophy of Science’, Springer, pp. 319–330.
  • Batterman, R. (2005), ‘Critical phenomena and breaking drops: Infinite idealizations in physics’, Studies in the History and Philosophy of Modern Physics 36, 225–244.
  • Butterfield, J. (2011), ‘Less is different:Emergence and reduction reconciled’, Foundations of Physics 41, 1065–1135.
  • Callender, C. (2001), ‘Taking thermodynamics too seriously’, Studies in History and Philosophy of Modern Physics 32(4), 539–533.
  • Norton, J. (2012), ‘Approximation and idealization: Why the difference matters’, Philosophy of Science 79, 207–232.
  • Norton, J. (2014), Infinite idealizations, in F. Stadtler, ed., ‘Vienna Circle Institute Yearbook’, Springer, Dordrecht-Heidelberg-London-New York.

Location

Main University Building
Geschwister-Scholl-Platz 1
D-80539 München
Room C 016

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