One mechanism, many models: a distributed theory of mechanistic explanation

Hochstein, Eric

doi:10.1007/s11229-015-0844-8

Cited by 45 publications

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“…Second, contradictions between models is fuel for progress in developing further models. No model ever explains in a theoretical void; models explain in a distributed fashion (Hochstein 2015). But distributed explanations should not be contradictory, so one needs to build coherent representations, and in doing so, monstrous explanations should be avoided if possible.…”

Section: Unification Strategies In Cognitive Sciencementioning

confidence: 99%

Unification Strategies in Cognitive Science

Miłkowski

2016

Studies in Logic, Grammar and Rhetoric

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Abstract.Cognitive science is an interdisciplinary conglomerate of various research fields and disciplines, which increases the risk of fragmentation of cognitive theories. However, while most previous work has focused on theoretical integration, some kinds of integration may turn out to be monstrous, or result in superficially lumped and unrelated bodies of knowledge. In this paper, I distinguish theoretical integration from theoretical unification, and propose some analyses of theoretical unification dimensions. Moreover, two research strategies that are supposed to lead to unification are analyzed in terms of the mechanistic account of explanation. Finally, I argue that theoretical unification is not an absolute requirement from the mechanistic perspective, and that strategies aiming at unification may be premature in fields where there are multiple conflicting explanatory models.

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Section: Unification Strategies In Cognitive Sciencementioning

confidence: 99%

Unification Strategies in Cognitive Science

Miłkowski

2016

Studies in Logic, Grammar and Rhetoric

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“…Models which predict the occurrence of the phenomenon are often treated as explanatory in part because they put essential constraints on the sorts of mechanisms that are capable of fitting with those predictions, and thus play an essential role in their discovery (see : Piccinini 2015;Piccinini & Craver 2011;Hochstein 2016aHochstein , 2016b). Yet, ironically, it has also been argued that part of what makes the identification of mechanisms explanatory is the very fact that knowing the mechanisms of the system allows us to better predict what the occurrence of the phenomenon will be under various interventions, and in counterfactual situations (see : Woodward 2000: Woodward , 2003Craver 2006).…”

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“…Scientists rarely, if ever, point to a single model as being the explanation of a given phenomenon. Instead, they appeal to many different models when engaging in the act of explaining a complex phenomenon (for numerous examples, see : Trumpler 1997;Mitchell 2003;Weisberg 2013, p.103;Hochstein 2016a;Miłkowski 2016). Once we give up the idea that explanations must be provided by individual representations, then the holistic nature of explanation and the trade-offs made by individual models becomes reconcilable.…”

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“…This was not a one-way street either. Learning more about the underlying mechanisms of the action potential similarly allowed scientists to further refine and improve upon the regularities previously described, and to develop more accurate representations of them (for details and discussion, see : Trumpler 1997;Hochstein 2016a). In this respect, a model which satisfied one explanatory goal provided essential information that helped to guide the creation of other models used to satisfy others.…”

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Why one model is never enough: a defense of explanatory holism

Hochstein

2017

Biol Philos

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Abstract:Traditionally, a scientific model is thought to provide a good scientific explanation to the extent that it satisfies certain scientific goals that are thought to be constitutive of explanation (e.g. generating understanding, identifying mechanisms, making predictions, identifying high-level patterns, allowing us to control and manipulate phenomena). Problems arise when we realize that individual scientific models cannot simultaneously satisfy all the scientific goals typically associated with explanation. A given model's ability to satisfy some goals must always come at the expense of satisfying others. This has resulted in philosophical disputes regarding which of these goals are in fact necessary for explanation, and as such which types of models can and cannot provide explanations (e.g. dynamical models, optimality models, topological models, etc). Explanatory monists argue that one goal will be explanatory in all contexts, while explanatory pluralists argue that the goal will vary based on pragmatic considerations. In this paper, I argue that such debates are misguided, and that both monists and pluralists are incorrect. Instead of any goal being given explanatory priority over others in a given context, the different goals are all deeply dependent on one another for their explanatory power. Any model that sacrifices some explanatory goals to attain others will always necessarily undermine its own explanatory power in the process. And so when forced to choose between individual scientific models, there can be no explanatory victors. Given that no model can satisfy all the goals typically associated with explanation, no one model in isolation can provide a good scientific explanation. Instead we must appeal to collections of models. Collections of models provide an explanation when they satisfy the web of interconnected goals that justify the explanatory power of one another.What kind of information must a scientific model convey in order to provide a good scientific explanation? This question has been at the heart of many recent debates within philosophy of science (see, for example: Batterman 2002;Craver 2006;Potochnik 2007Potochnik , 2010Weber 2008;Huneman 2010;Kaplan & Craver 2011;Lange 2013;Chirimuuta 2014;Rice 2015;Povich 2016). Traditionally, the explanatory power of a theory or model in science has been thought to relate to its ability to help us satisfy certain kinds of scientific goals. While there are disagreements regarding which goals in particular ought to be considered essential for explanation, a list of frequently defended scientific goals include:(1) Successfully conveying understanding about the target phenomenon, or making it intelligible, to an audience or inquirer (Achinstein 1983;Braverman et al. 2012Waskan et al, 2014.(2) Determining when a given phenomenon is expected to occur, and under what conditions (Hempel & Oppenheim 1948;Hempel 1965;Chemero & Silberstein 2008;Rice 2015). (5) Providing information sufficient to control, manipulate, and reproduce the target phenomenon (...

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“…Hochstein, 2015;Kellert, Longino, & Waters, 2006;Parker, 2006;Wimsatt, 2007;Weisberg, 2013, pp. 103-105).…”

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Giving up on convergence and autonomy: Why the theories of psychology and neuroscience are codependent as well as irreconcilable

Hochstein

2016

Studies in History and Philosophy of Science Part A

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a b s t r a c tThere is a long-standing debate in the philosophy of mind and philosophy of science regarding how best to interpret the relationship between neuroscience and psychology. It has traditionally been argued that either the two domains will evolve and change over time until they converge on a single unified account of human behaviour, or else that they will continue to work in isolation given that they identify properties and states that exist autonomously from one another (due to the multiple-realizability of psychological states). In this paper, I argue that progress in psychology and neuroscience is contingent on the fact that both of these positions are false. Contra the convergence position, I argue that the theories of psychology and the theories of neuroscience are scientifically valuable as representational tools precisely because they cannot be integrated into a single account. However, contra the autonomy position, I propose that the theories of psychology and neuroscience are deeply dependent on one another for further refinement and improvement. In this respect, there is an irreconcilable codependence between psychology and neuroscience that is necessary for both domains to improve and progress. The two domains are forever linked while simultaneously being unable to integrate.Ó 2015 Elsevier Ltd. All rights reserved. When citing this paper, please use the full journal title Studies in History and Philosophy of ScienceThere is a long-standing debate in the philosophy of mind and the philosophy of science regarding how best to interpret the relationship between the theories and models of neuroscience, and those of psychology. Both domains are dedicated to the scientific study and explanation of cognitive behaviour, yet each domain appears to explain and predict this behaviour by appealing to distinct sets of theories and models, and by employing different kinds of concepts and categories. How then can we make sense of the relationship between these different domains, and move forward in our scientific understanding of such behaviour? Traditionally, philosophers of science have proposed one of two possible options for how this relationship might ultimately be understood, and their seemingly conflicting accounts resolved:1. As neuroscience and psychology improve and change over time, the theories and models of both domains will slowly co-evolve together, each undergoing alterations and changes until they converge on a single unified theory of cognitive behaviour (e.g. Bickle, 1998Bickle, , 2003Bickle, , 2006Boone & Piccinini, 2015;Churchland, 1989;Craver, 2007;Piccinini & Craver, 2011). 2. Neuroscience and psychology will not converge because the two domains characterize systems at different levels of organization. The theories of psychology characterize functional states of systems that can be realized in different ways by different mechanisms, while the theories of neuroscience only characterize the physical implementation of neurological mechanisms. Given that the functional properties and r...

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One mechanism, many models: a distributed theory of mechanistic explanation

Cited by 45 publications

References 53 publications

Unification Strategies in Cognitive Science

Unification Strategies in Cognitive Science

Why one model is never enough: a defense of explanatory holism

Giving up on convergence and autonomy: Why the theories of psychology and neuroscience are codependent as well as irreconcilable

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