Online research in philosophy

The paper has two aims. First, to show that we need social mechanisms to establish the policy relevance of causal claims, even if it is possible to build a good argument for those claims without knowledge of mechanisms. Second, to show that although social scientists can, in principle, do without social mechanisms when they argue for causal claims, in reality scientific practice contexts where they do not need mechanisms are very rare. Key Words: social mechanisms • causal inference • social policy.

Two kinds of causal inference rules which are widely used by social scientists are investigated. Two conceptions of causation also widely used are explicated -- the INUS and probabilistic conceptions of causation. It is shown that the causal inference rules which link correlation, a kind of partial correlation, and a conception of causation are invalid. It is concluded a new methodology is required for causal inference.

During the past decade, social mechanisms and mechanism-based ex- planations have received considerable attention in the social sciences as well as in the philosophy of science. This article critically reviews the most important philosophical and social science contributions to the mechanism approach. The first part discusses the idea of mechanism- based explanation from the point of view of philosophy of science and relates it to causation and to the covering-law account of explanation. The second part focuses on how the idea of mechanisms has been used in the social sciences. The final part discusses recent developments in analytical sociology, covering the nature of sociological explananda, the role of theory of action in mechanism-based explanations, Merton’s idea of middle-range theory, and the role of agent-based simulations in the development of mechanism-based explanations.

A recent movement in the social sciences and philosophy of the social sciences focuses on mechanisms as a central analytical unit. Starting from a pluralist perspective on the aims of the social sciences, I argue that there are a number of important aims to which knowledge about mechanisms—whatever their virtues relative to other aims—contributes very little at best and that investigating mechanisms is therefore a methodological strategy with fairly limited applicability. Key Words: social science • mechanisms • explanation • critical realism • methodology.

mechanism" is frequently encountered in the social science literature, but there is considerable confusion about the exact meaning of the term. The article begins by addressing the main conceptual issues. Use of this term is the hallmark of an approach that is critical of the explanatory deficits of correlational analysis and of the covering-law model, advocating instead the causal reconstruction of the processes that account for given macro-phenomena. The term "social mechanisms" should be used to refer to recurrent processes generating a specific kind of outcome. Explanation of social macro-phenomena by mechanisms typically involves causal regression to lower-level elements, as stipulated by methodological individualism. While there exist a good many mechanism models to explain emergent effects of collective behavior, we lack a similarly systematic treatment of generative mechanisms in which institutions and specific kinds of structural configurations play the decisive role. Key Words: causal regression • correlational analysis • emergent effects • micro-macro processes • social mechanisms • structural determinants.

This paper discusses various problems of explanations by mechanisms. Two positions are distinguished: the narrow position claims that only explanations by mechanisms are acceptable. It is argued that this position leads to an infinite regress because the discovery of a mechanism must entail the search for other mechanisms etc. Another paradoxical consequence of this postulate is that every successful explanation by mechanisms is unsatisfactory because it generates new ``black box'' explanations. The second – liberal – position that is advanced in this paper regards, besides explanations by mechanisms, also the discovery of bivariate correlations as a first step of an explanation by mechanisms as meaningful. It is further argued that there is no contradiction between causal analysis and the explanation by mechanisms. Instead, explanations by mechanisms always presuppose the analysis of causal structures (but not vice versa). The final point is that an explanation by mechanisms is not inconsistent with the Hempel-Oppenheim scheme of explanation.

Why do people get sick? I argue that a disease explanation is best thought of as causal network instantiation, where a causal network describes the interrelations among multiple factors, and instantiation consists of observational or hypothetical assignment of factors to the patient whose disease is being explained. This paper first discusses inference from correlation to causation, integrating recent psychological discussions of causal reasoning with epidemiological approaches to understanding disease causation, particularly concerning ulcers and lung cancer. It then shows how causal mechanisms represented by causal networks can contribute to reasoning involving correlation and causation. The understanding of causation and causal mechanisms provides the basis for a presentation of the causal network instantiation model of medical explanation.

This chapter explores the idea that causal inference is warranted if and only if the mechanism underlying the inferred causal association is identified. This mechanistic stance is discernible in the epidemiological literature, and in the strategies adopted by epidemiologists seeking to establish causal hypotheses. But the exact opposite methodology is also discernible, the black box stance, which asserts that epidemiologists can and should make causal inferences on the basis of their evidence, without worrying about the mechanisms that might underlie their hypotheses. I argue that the mechanistic stance is indeed a bad methodology for causal inference. However, I detach and defend a mechanistic interpretation of causal generalisations in epidemiology as existence claims about underlying mechanisms.

In this discussion note I clarify the motivation behind my original paper "Social Mechanisms, Causal Inference and the Policy Relevance of Social Science." I argue that one of the tasks of philosophers of social science is to draw attention to methodological problems that are often forgotten or overlooked. Then I show that my original paper does not make the mistake or fallacy that Daniel Steel suggests in his comment on it. Key Words: social mechanisms • causal inference • social policy.

This reply to Erik Weber’s commentary agrees that mechanisms are important for causal inference in social science, but argues that Weber makes the mistake that was the main focus of my original essay: inferring that since a problem cannot be solved without mechanisms, it can be solved with them. As it stands, this inference is invalid since the problem might be unsolvable with or without mechanisms. Any claim about the usefulness of mechanisms for some purpose requires an adequate account of how mechanisms can actually fulfill that function, which Weber has not provided with regard to the issues he discusses.