Angela Potochnik

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Work in Progress

Explanation and Understanding: A Response to Strevens' Depth

under review

In Depth (2009), Michael Strevens offers an account of causal explanation according to which explanatory practice is shaped by counterbalanced commitments to representing causal influence and abstracting away from overly specific details.  Here I outline Strevens’ approach to event explanation and raise one concern with that account.  I argue that what Strevens calls explanatory frameworks figure prominently in explanatory practice because, contrary to Strevens’ view, they actually improve explanations.  This suggestion is simple but has far-reaching implications.  It affects the status of explanations that cite multiply realizable properties; the explanatory role of causal factors with small effect; and Strevens’ titular explanatory virtue, depth.  This results in greater coherence with explanatory practice and accords with the emphasis that Strevens places on explanatory patterns.  Ultimately, my suggestion preserves a tight connection between explanation and the creation of understanding.

A Neurathian Conception of the Unity of Science

under review

An historically important conception of the unity of science is explanatory reductionism, according to which the unity of science is achieved by explaining all laws of science in terms of their connection to microphysical laws. There is, however, a separate tradition that advocates the unity of science. According to that tradition, the unity of science consists of the coordination of diverse fields of science, none of which is taken to have privileged epistemic status. This alternate conception has roots in Otto Neurath’s notion of unified science. In this paper, I develop a version of this coordination approach to unity and discuss its connection to Neurath’s views. The resulting conception of the unity of science achieves some aims similar to those of explanatory reductionism, but does so in a radically different way. As a result, it is immune to the criticisms of explanatory reductionism. This conception of unity is also importantly different from the view that science is disunified, and I conclude by demonstrating how the coordinate unity of science accords better with scientific practice than do conceptions of the disunity of science.


A Dispute over the Basics of Nature

in preparation

As detailed in The Genial Gene (2009), Joan Roughgarden's conception of social selection involves twenty-six empirical hypotheses regarding the evolution of a variety of traits related to sexual reproduction, gender, and the rearing of offspring.  Yet Roughgarden sets out to show something even beyond this array of empirical hypotheses.  Her contention is that cooperation is `basic to biological nature'.  In this paper, I investigate the role that this claim plays in Roughgarden's work.  This investigation clarifies the relationship between Roughgarden's social selection theory and extant sexual selection theory.  It also clarifies the nature of Roughgarden's criticisms of other accounts of the evolution of cooperation, including kin selection, reciprocal altruism, and group selection.  My purpose is twofold: this investigation helps put social selection theory into perspective, and it analyzes an episode of science where broad-scope theoretical claims are plainly entangled with empirical hypotheses.

Why Integrate Dynamics?

draft, in conjunction with a NIMBioS workshop on two-tiered models

Following up on (Roughgarden et al., 2006), Roughgarden (2009) introduces the idea of a  two-tiered approach to modeling social behavior via analogy to optimal foraging theory.  Just  as optimal foraging models represent the evolution of conditional foraging strategies, social behavior is to be represented as the evolution of conditional reproductive transactions.  This two-tiered approach explicitly represents the dynamics of social decision-making that governs individual behaviors, as well as the evolution of those social dynamics.  More generally, this conception of a two-tiered modeling approach involves explicitly representing the separate elements of the functional dynamics of a system and the evolution of that system.   Here I explore some theoretical questions regarding the development of a two-tier modeling approach.  I begin by raising the question of what motivates the proposed integration of functional and evolutionary dynamics.  I then indicate how the answer to that question influences the scope of the project.  Finally, I consider how the move to a two-tiered approach affects the feasibility of model-testing.



Publications

Levels of Explanation Reconceived

forthcoming, Philosophy of Science. 

A common argument against explanatory reductionism is that higher-level explanations are sometimes or always preferable because they are more general than reductive explanations.  Here I challenge two basic assumptions that are needed for this argument to succeed.  It cannot be assumed that higher-level explanations are more general than their lower-level alternatives, nor that higher-level explanations are general in the right way to be explanatory.  I suggest a novel form of pluralism regarding levels of explanation, according to which explanations at different levels are preferable in different circumstances because they offer different types of generality, which are appropriate in different circumstances of explanation. 

Explanatory Independence and Epistemic Interdependence: A Case Study of the Optimality Approach

forthcoming, The British Journal for the Philosophy of Science. 
(Original publication available at bjps.oxfordjournals.org)

The value of optimality modeling has long been a source of contention amongst population biologists.  Here I present a view of the optimality approach as at once playing a crucial explanatory role and yet also depending on external sources of confirmation.  Optimality models are not alone in facing this tension between their explanatory value and their dependence on other approaches; I suspect that the scenario is quite common in science.  This investigation of the optimality approach thus serves as a case study, on the basis of which I suggest that there is a widely felt tension in science between explanatory independence and broad epistemic interdependence, and that this tension influences scientific methodology. 


Optimality Modeling in a Suboptimal World
2009, Biology and Philosophy, 24(2): 183-197. 
(Original publication available at www.springerlink.com)

The fate of optimality modeling is typically linked to that of adaptationism: the two are thought to stand or fall together (Gould and Lewontin, 1979; Orzack and Sober, 1994).  I argue here that this is mistaken.  The debate over adaptationism has tended to focus on one particular use of optimality models, which I refer to here as their strong use.  The strong use of an optimality model involves the claim that selection is the only important influence on the evolutionary outcome in question and is thus linked to adaptationism.  However, biologists seldom intend this strong use of optimality models.  One common alternative that I term the weak use simply involves the claim that an optimality model accurately represents the role of selection in bringing about the outcome.  This and other weaker uses of optimality models insulate the optimality approach from criticisms of adaptationism, and they account for the prominence of optimality modeling (broadly construed) in population biology.  The centrality of these uses of optimality models ensures a continuing role for the optimality approach, regardless of the fate of adaptationism.


Optimality Modeling and Explanatory Generality
2007, Philosophy of Science, PSA 20th Biennial Meeting (Vancouver): Contributed Papers, 74(5): 680-691. 

The optimality approach to modeling natural selection has been criticized by many biologists and philosophers of biology.  For instance, Lewontin (1979) argues that the optimality approach is a shortcut that will be replaced by models incorporating genetic information, if and when such models become available.  In contrast, I think that optimality models have a permanent role in evolutionary study.  I base my argument for this claim on what I think it takes to best explain an event.  In certain contexts, optimality and game-theoretic models best explain some central types of evolutionary phenomena.

Revisiting Galison's 'Aufbau/Bauhaus' in Light of Neurath's Philosophical Projects
2006, with Audrey Yap, Studies in History and Philosophy of Science, Part A, 37(3): 469-488. 

Historically, the Vienna Circle and the Dessau Bauhaus were related, with members of each group familiar with the ideas of the other.  Peter Galison argues that their projects are related as well, through shared political views and methodological approach.  The two main figures that connect the Vienna Circle to the Bauhaus—and the figures upon which Galison focuses—are Rudolf Carnap and Otto Neurath.  Yet the connections that Galison develops do not properly capture the common themes between the Bauhaus and Neurath’s philosophical projects.  We demonstrate this by considering Neurath’s philosophical commitments.  We suggest different connections between Neurath’s projects and the Bauhaus, connections that are both substantive and philosophically interesting.




Dissertation

Evolution, Explanation and Unity of Science
Philosophy Dissertation, 2007, Stanford University, completed under the supervision of Elliott Sober and Michael Friedman.

Approaches to modeling evolution by natural selection include optimality models, which capture the evolution of a phenotypic trait in a population but do not reference genetic change, and genetic models, which capture the genetic dynamics of evolution.  The merits and liabilities of the optimality approach to modeling natural selection are a matter of debate in population biology.  Other biologists question the degree to which genetic models of selection are necessary when dealing with the long term evolutionary change of phenotypic traits.  In my dissertation, I examine philosophical issues related to the optimality and genetic approaches to modeling natural selection.  Two types of results emerge from this investigation.  First, I defend the value of these two separate and yet complementary approaches and argue that there is a tight relationship between them.  Second, I use this debate in biology as a case study that is well-situated to shed new light on traditional problems in philosophy of science concerning explanation, reductionism, and the unity of science.