On the causal approach to explanation, explaining a phenomenon is telling the actual causal story as to why it occurs. Science is full of idealizing explanations that deliberately falsify the relevant causal story. Therefore, either (a) the causal approach to explanation is mistaken, or (b) idealizing explanations, however convenient, are deeply flawed. Correct? I don’t think so. I show that on...

Past research has shown that educational media, such as a television series or interactive games, can promote significant learning. Today, however, it is quite common for producers to create several interconnected media, such as a television show and an associated web site, under the assumption that multiple platforms elicit greater learning than a single medium would. The research reported bel...

Group Support Systems (GSS) technology is still in the early stages of its diffusion process. There are several thousand GSS installations worldwide, and that number is growing, but GSS have not yet achieved a mass market. It may be that studying adoption and diffusion of GSS within a single organization could yield insights that would help speed the process elsewhere. This paper presents an 18...

Probabilistic reasoning has been powered by the formalization of causality theory through Bayesian causal models[1]. Even when its semantic is flexible enough to model complex problems, it has to deal with the problem of interoperability between models. In the research community the necessity of contexts for these models has been pointed out. We need means to represent the context on which the ...

Strategic alliances in the form of interorganizational networks continue to receive attention in both service and manufacturing industries as a potential form of competitive advantage. Health care organizations, in particular, have embraced partnerships and strategic alliances with much intensity, adopting the interorganizational network as the new business model for the health care industry. Y...

We explore an approach to reasoning about causes via argumentation. We consider a causal model for a physical system, and we look for arguments about facts. Some arguments are meant to provide explanations of facts whereas some challenge these explanations and so on. At the root of argumentation here, are causal links ({A1, · · · , An} causes B) and also ontological links (c1 is a c2). We intro...

Working within the decision-theoretic framework for causal inference, we study the properties of “sufficient covariates”, which support causal inference from observational data, and possibilities for their reduction. In particular we illustrate the rôle of a propensity variable by means of a simple model, and explain why such a reduction typically does not increase (and may reduce) estimation e...