Mark Povich
Biographic Data
| ID | 1061807 |
|---|---|
| NAME | Mark Povich |
| GIVEN NAMES | Mark |
| FAMILY NAME | Povich |
| SIGNATURE | POVICH M |
| AFFILIATIONS | Washington University in St. Louis |
| ORCID | 0000-0001-8124-4311 |
| VERIFIED | Yes |
| TOTAL WORKS | 8 |
| TOTAL CITATIONS | 50 |
| AUTHOR COUNT | 8 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2015 |
| LATEST PUBLICATION YEAR | 2025 |
| H-INDEX | 4 |
Rules to Infinity: The Normative Role of Mathematics in Scientific Explanation
One central aim of science is to provide explanations of natural phenomena. What role(s) does mathematics play in achieving this aim? How does mathematics contribute to the explanatory power of science? Rules to Infinity defends the thesis, common though perhaps inchoate among many members of the Vienna Circle, that mathematics contributes to the explanatory power of science by expressing conceptual rules, rules which allow the transformation of …
Constitutive relevance & mutual manipulability revisited
The Narrow Ontic Counterfactual Account of Distinctively Mathematical Explanation
An account of distinctively mathematical explanation (DME) should satisfy three desiderata: it should account for the modal import of some DMEs; it should distinguish uses of mathematics in explanation that are distinctively mathematical from those that are not (Baron [2016]); and it should also account for the directionality of DMEs (Craver and Povich [2017]). Baron’s ([forthcoming]) deductive-mathematical account, because it is modelled on the …
Model-based cognitive neuroscience: Multifield mechanistic integration in practice
Autonomist accounts of cognitive science suggest that cognitive model building and theory construction (can or should) proceed independently of findings in neuroscience. Common functionalist justifications of autonomy rely on there being relatively few constraints between neural structure and cognitive function. In contrast, an integrative mechanistic perspective stresses the mutual constraining of structure and function. In this article, I show …
Because without Cause: Non-Causal Explanations in Science and Mathematics
The consensus in the philosophy of science, at least since the 1980s, has been that Hempel's covering law model fails largely because it ignores the central role of causation in scientific explanation. Most subsequent work on scientific explanation has focused on understanding how causal (Salmon 1984; Woodward 2003; Strevens 2008) and mechanistic (Craver 2007) explanations work. Some have even asserted, perhaps in incautious moments, that all sci…
Minimal Models and the Generalized Ontic Conception of Scientific Explanation
Batterman and Rice ([2014]) argue that minimal models possess explanatory power that cannot be captured by what they call ‘common features’ approaches to explanation. Minimal models are explanatory, according to Batterman and Rice, not in virtue of accurately representing relevant features, but in virtue of answering three questions that provide a ‘story about why large classes of features are irrelevant to the explanandum phenomenon’ ([2014], p.…
The directionality of distinctively mathematical explanations
Mechanisms and Model-Based Functional Magnetic Resonance Imaging
Mechanistic explanations satisfy widely held norms of explanation: the ability to manipulate and answer counterfactual questions about the explanandum phenomenon. A currently debated issue is whether any nonmechanistic explanations can satisfy these explanatory norms. Weiskopf argues that the models of object recognition and categorization, JIM, SUSTAIN, and ALCOVE, are not mechanistic yet satisfy these norms of explanation. In this article I arg…
The directionality of distinctively mathematical explanations
Constitutive relevance & mutual manipulability revisited
Minimal Models and the Generalized Ontic Conception of Scientific Explanation
Batterman and Rice ([2014]) argue that minimal models possess explanatory power that cannot be captured by what they call ‘common features’ approaches to explanation. Minimal models are explanatory, according to Batterman and Rice, not in virtue of accurately representing relevant features, but in virtue of answering three questions that provide a ‘story about why large classes of features are irrelevant to the explanandum phenomenon’ ([2014], p.…
The Narrow Ontic Counterfactual Account of Distinctively Mathematical Explanation
An account of distinctively mathematical explanation (DME) should satisfy three desiderata: it should account for the modal import of some DMEs; it should distinguish uses of mathematics in explanation that are distinctively mathematical from those that are not (Baron [2016]); and it should also account for the directionality of DMEs (Craver and Povich [2017]). Baron’s ([forthcoming]) deductive-mathematical account, because it is modelled on the …
Mechanisms and Model-Based Functional Magnetic Resonance Imaging
Mechanistic explanations satisfy widely held norms of explanation: the ability to manipulate and answer counterfactual questions about the explanandum phenomenon. A currently debated issue is whether any nonmechanistic explanations can satisfy these explanatory norms. Weiskopf argues that the models of object recognition and categorization, JIM, SUSTAIN, and ALCOVE, are not mechanistic yet satisfy these norms of explanation. In this article I arg…
Because without Cause: Non-Causal Explanations in Science and Mathematics
The consensus in the philosophy of science, at least since the 1980s, has been that Hempel's covering law model fails largely because it ignores the central role of causation in scientific explanation. Most subsequent work on scientific explanation has focused on understanding how causal (Salmon 1984; Woodward 2003; Strevens 2008) and mechanistic (Craver 2007) explanations work. Some have even asserted, perhaps in incautious moments, that all sci…
Mechanisms and Model-Based Functional Magnetic Resonance Imaging
Mechanistic explanations satisfy widely held norms of explanation: the ability to manipulate and answer counterfactual questions about the explanandum phenomenon. A currently debated issue is whether any nonmechanistic explanations can satisfy these explanatory norms. Weiskopf argues that the models of object recognition and categorization, JIM, SUSTAIN, and ALCOVE, are not mechanistic yet satisfy these norms of explanation. In this article I arg…
The directionality of distinctively mathematical explanations
Because without Cause: Non-Causal Explanations in Science and Mathematics
The consensus in the philosophy of science, at least since the 1980s, has been that Hempel's covering law model fails largely because it ignores the central role of causation in scientific explanation. Most subsequent work on scientific explanation has focused on understanding how causal (Salmon 1984; Woodward 2003; Strevens 2008) and mechanistic (Craver 2007) explanations work. Some have even asserted, perhaps in incautious moments, that all sci…
Minimal Models and the Generalized Ontic Conception of Scientific Explanation
Batterman and Rice ([2014]) argue that minimal models possess explanatory power that cannot be captured by what they call ‘common features’ approaches to explanation. Minimal models are explanatory, according to Batterman and Rice, not in virtue of accurately representing relevant features, but in virtue of answering three questions that provide a ‘story about why large classes of features are irrelevant to the explanandum phenomenon’ ([2014], p.…
Model-based cognitive neuroscience: Multifield mechanistic integration in practice
Autonomist accounts of cognitive science suggest that cognitive model building and theory construction (can or should) proceed independently of findings in neuroscience. Common functionalist justifications of autonomy rely on there being relatively few constraints between neural structure and cognitive function. In contrast, an integrative mechanistic perspective stresses the mutual constraining of structure and function. In this article, I show …
Constitutive relevance & mutual manipulability revisited
The Narrow Ontic Counterfactual Account of Distinctively Mathematical Explanation
An account of distinctively mathematical explanation (DME) should satisfy three desiderata: it should account for the modal import of some DMEs; it should distinguish uses of mathematics in explanation that are distinctively mathematical from those that are not (Baron [2016]); and it should also account for the directionality of DMEs (Craver and Povich [2017]). Baron’s ([forthcoming]) deductive-mathematical account, because it is modelled on the …
Rules to Infinity: The Normative Role of Mathematics in Scientific Explanation
One central aim of science is to provide explanations of natural phenomena. What role(s) does mathematics play in achieving this aim? How does mathematics contribute to the explanatory power of science? Rules to Infinity defends the thesis, common though perhaps inchoate among many members of the Vienna Circle, that mathematics contributes to the explanatory power of science by expressing conceptual rules, rules which allow the transformation of …
Epistemology (8 works) · Philosophy (8 works) · Philosophy and History of Science (8 works) · Biomedical Text Mining and Ontologies (6 works) · Causation (4 works) · Mathematics (4 works) · Computer Science (3 works) · Ontic (3 works) · Philosophy of science (3 works) · Artificial Intelligence (2 works)