What's the Point of Understanding?

What is human understanding and why should we care about it? I propose a method of philosophical investigation called ‘function-first epistemology’ and use this method to investigate the nature and value of understanding-why. I argue that the concept of understanding-why serves the practical function of identifying good explainers, which is an important role in the general economy of our concepts. This hypothesis sheds light on a variety of issues in the epistemology of understanding including the role of explanation, the relationship between understanding-why and knowledge, and the value of understanding-why. I conclude that understanding-why is valuable and yet knowledge plays more important roles in our epistemic life

General Theory of Topological Explanations and Explanatory Asymmetry

In this paper, I present a general theory of topological explanations, and illustrate its fruitfulness by showing how it accounts for explanatory asymmetry. My argument is developed in three steps. In the first step, I show what it is for some topological property A to explain some physical or dynamical property B. Based on that, I derive three key criteria of successful topological explanations: a criterion concerning the facticity of topological explanations, i.e. what makes it true of a particular system; a criterion for describing counterfactual dependencies in two explanatory modes, i.e. the vertical and the horizontal; and, finally, a third perspectival one that tells us when to use the vertical and when to use the horizontal mode. In the second step, I show how this general theory of topological explanations accounts for explanatory asymmetry in both the vertical and horizontal explanatory modes. Finally, in the third step, I argue that this theory is universally applicable across biological sciences, which helps to unify essential concepts of biological networks

What Can Be Learned from Computer Modeling? Comparing Expository and Modeling Approaches to Teaching Dynamic Systems Behavior

Computer modeling has been widely promoted as a means to attain higher order learning outcomes. Substantiating these benefits, however, has been problematic due to a lack of proper assessment tools. In this study, we compared computer modeling with expository instruction, using a tailored assessment designed to reveal the benefits of either mode of instruction. The assessment addresses proficiency in declarative knowledge, application, construction, and evaluation. The subscales differentiate between simple and complex structure. The learning task concerns the dynamics of global warming. We found that, for complex tasks, the modeling group outperformed the expository group on declarative knowledge and on evaluating complex models and data. No differences were found with regard to the application of knowledge or the creation of models. These results confirmed that modeling and direct instruction lead to qualitatively different learning outcomes, and that these two modes of instruction cannot be compared on a single “effectiveness measure”

The Hubble Hypothesis and the Developmentalist's Dilemma

Developmental psychopathology stands poised at the close of the 20th century on the horns of a major scientific dilemma. The essence of this dilemma lies in the contrast between its heuristically rich open system concepts on the one hand, and the closed system paradigm it adopted from mainstream psychology for investigating those models on the other. Many of the research methods, assessment strategies, and data analytic models of psychology’s paradigm are predicated on closed system assumptions and explanatory models. Thus, they are fundamentally inadequate forstudying humans, who are unparalleled among open systems in their wide ranging capacities for equifinal and multifinal functioning. Developmental psychopathology faces two challenges in successfully negotiating the developmentalist’s dilemma. The first lies in recognizing how the current paradigm encourages research practices that are antithetical to developmental principles, yet continue to flourish. I argue that the developmentalist’s dilemma is sustained by long standing, mutually enabling weaknesses in the paradigm’s discovery methods and scientific standards. These interdependent weaknesses function like a distorted lens on the research process by variously sustaining the illusion of theoretical progress, obscuring the need for fundamental reforms, and both constraining and misguiding reform efforts. An understanding of how these influences arise and take their toll provides a foundation and rationale for engaging the second challenge. The essence of this challenge will be finding ways to resolve the developmentalist’s dilemma outside the constraints of the existing paradigm by developing indigenous research strategies, methods, and standards with fidelity to the complexity of developmental phenomena

Counterfactuals of Ontological Dependence

A great deal has been written about 'would' counterfactuals of causal dependence. Comparatively little has been said regarding 'would' counterfactuals of ontological dependence. The standard Lewis-Stalnaker semantics is inadequate for handling such counterfactuals. That's because some of these counterfactuals are counterpossibles, and the standard Lewis-Stalnaker semantics trivializes for counterpossibles. Fortunately, there is a straightforward extension of the Lewis-Stalnaker semantics available that handles counterpossibles: simply take Lewis's closeness relation that orders possible worlds and unleash it across impossible worlds. To apply the extended semantics, an account of the closeness relation for counterpossibles is needed. In this paper I offer a strategy for evaluating 'would' counterfactuals of ontological dependence that understands closeness between worlds in terms of the metaphysical concept of grounding

Mental Structures

An ongoing philosophical discussion concerns how various types of mental states fall within broad representational genera—for example, whether perceptual states are “iconic” or “sentential,” “analog” or “digital,” and so on. Here, I examine the grounds for making much more specific claims about how mental states are structured from constituent parts. For example, the state I am in when I perceive the shape of a mountain ridge may have as constituent parts my representations of the shapes of each peak and saddle of the ridge. More specific structural claims of this sort are a guide to how mental states fall within broader representational kinds. Moreover, these claims have significant implications of their own about semantic, functional, and epistemic features of our mental lives. But what are the conditions on a mental state's having one type of constituent structure rather than another? Drawing on explanatory strategies in vision science, I argue that, other things being equal, the constituent structure of a mental state determines what I call its distributional properties—namely, how mental states of that type can, cannot, or must co‐occur with other mental states in a given system. Distributional properties depend critically on and are informative about the underlying structures of mental states, they abstract in important ways from aspects of how mental states are processed, and they can yield significant insights into the variegation of psychological capacities

Learning from the Past: Trends in Executive Compensation over the Twentieth Century

In recent years, a large academic debate has tried to explain the rapid rise in CEO pay experienced over the past three decades. In this article, I review the main proposed theories, which span views of compensation as the result of a competitive labor market for executivesto theories based on excess of managerial power. Some of these hypotheses have foundsupport in cross-sectional evidence, but it has proven more difficult to determine which factors have caused the observed changes in pay over time. An alternative strategy is to evaluate the fit of plausible explanations out of sample by contrasting them with the evolution in executive pay and the market for managers during earlier time periods. A case study of General Electric suggests that evidence for earlier decades can speak to the recent trends and reveals the limitations of current explanations to address the long-run data.executive compensation, managerial incentives, corporate governance, market for managers

Folk intuitions of Actual Causation: A Two-Pronged Debunking Explanation

How do we determine whether some candidate causal factor is an actual cause of some particular outcome? Many philosophers have wanted a view of actual causation which fits with folk intuitions of actual causation and those who wish to depart from folk intuitions of actual causation are often charged with the task of providing a plausible account of just how and where the folk have gone wrong. In this paper, I provide a range of empirical evidence aimed at showing just how and where the folk go wrong in determining whether an actual causal relation obtains. The evidence suggests that folk intuitions of actual causation are generated by two epistemically defective processes. I situate the empirical evidence within a background discussion of debunking, arguing for a two-pronged debunking explanation of folk intuitions of actual causation. I conclude that those who wish to depart from folk intuitions of actual causation should not be compelled to square their account of actual causation with the verdicts of the folk. In the dispute over actual causation, folk intuitions deserve to be rejected

Inference, Explanation, and Asymmetry

Explanation is asymmetric: if A explains B, then B does not explain A. Tradition- ally, the asymmetry of explanation was thought to favor causal accounts of explanation over their rivals, such as those that take explanations to be inferences. In this paper, we develop a new inferential approach to explanation that outperforms causal approaches in accounting for the asymmetry of explanation