Erik Weber

This paper deals with the "functions of intentional explanations" of actions (IEAs), i.e., explanations that refer to intentional states (beliefs, desires, etc.) of the agent. IEAs can have different formats. We consider these different formats to be instruments that enable the explainer to capture different kinds of information. We pick out two specific formats, i.e. "contrastive" and "descriptive", which will enable us to discuss the functions of IEAs. In many cases the explanation is contrastive, i.e. it makes use of one or more contrasts between real intentional states and ideal intentional states (ideal from the point of view of the explainer). In many other cases IEAs have a descriptive (covering-law) format. The aim of this paper is to analyze the functions the two kinds of explanations can have. We will show that certain functions are better served by one rather than the other format. This leads to pluralism with respect to formats. We argue that both formats are necessary and that their functions are complementary.

In this chapter we assess the explanatory utility of ascriptions of technical functions by considering two explanation-seeking contexts that often figure in the philosophical literature on functions (and explanations). Applied to the technical domain, these are: (i) why was artifact x produced?, and (ii) why does artifact x not have the expected capacity to ϕ? We argue that function ascriptions are explanatorily irrelevant for the first explanation-seeking question, and are explanatorily relevant for the second one. We argue these points in terms of the desideratum that explanations should only list difference making factors.

There are several theses in political science that are usually explicitly called ‘laws’. Other theses are generally thought of as laws, but often without being explicitly labelled as such. Still other claims are well-supported and arguably interesting, while no one would be tempted to call them laws. This situation raises philosophical questions: which theses deserve to be called laws and which not? And how should we decide about this? In this paper we develop and motivate a strategy for thinking about laws in political science which integrates two core concepts: spatio-temporal stability and social mechanisms. The proposed strategy is a set of guidelines that political scientists can use to reflect on and argue about specific cases within their discipline, not a clear-cut demarcation criterion. We defend and motivate this strategy and apply it to two cases (one with respect to state repression, one about parliamentary elections). After we have developed and motivated our strategy for political science, we show that our proposal is relevant for other disciplines in the social sciences. We explain how our views fit into critical realism and embed them in the debate on laws in general philosophy of science and in the philosophy of the social sciences.

This paper is a reaction to ‘Styles of Thought on the Continental Drift Debate’ by Pablo Pellegrini, published in this journal. The author argues that rationalist accounts of the continental drift debate fail because they overlook important issues. In this discussion we distinguish various forms of rationalism. Then we present a sophisticated rationalist account of the continental drift debate and argue that it is satisfactory because it explains all the central developments in that debate. Finally, we point to a problematic tension in Pellegrini’s paper and unravel an underlying ambiguity.

In this paper we identify six theses that constitute core results of philosophical investigation into the nature of mechanisms, and of the role that the search for and identification of mechanisms play in the sciences. These theses represent the fruits of the body of research that is now often called New Mechanism. We concisely present the main arguments for these theses. In the literature, these arguments are scattered and often implicit. Our analysis can guide future research in many ways: it provides critics of New Mechanism with clear targets, it can reduce misunderstandings, it can clarify differences of opinion among New Mechanists and it helps to define a research agenda for New Mechanists.

In this essay the authors explore the nature of efficient causal explanation in Newton’s "Principia and The Opticks". It is argued that: (1) In the dynamical explanations of the Principia, Newton treats the phenomena under study as cases of Hall’s second kind of atypical causation. The underlying concept of causation is therefore a purely interventionist one. (2) In the descriptions of his optical experiments, Newton treats the phenomena under study as cases of Hall’s typical causation. The underlying concept of causation is therefore a mixed interventionist/mechanicist one.

Evidence-based management (EBMgt) is a relatively recent approach to management, developed by Denise Rousseau in a series of articles and in a book that she co-authored with Eric Barends (Barends & Rousseau 2018). It is based on the idea that good-quality management decisions require both critical thinking and use of the best available evidence. In this paper we want to contribute to the scholarship on evidence-based management by showing how its central concept – evidence – can and should be defined more strictly. Barends and Rousseau define evidence as a two-place relation between information and a claim that is at stake. Starting from insights from the methodology of the social sciences we argue that evidence is a three-place relation between a method, information and a claim. We offer a guiding principle for adequately characterising what counts as evidence (the inclusion of a procedural component which describes how the information should be collected and reported) and apply it to Barends and Rousseau’s concepts of (i) evidence from practitioners, (ii) evidence from the organization and (iii) evidence from stakeholders. We think that by treating evidence as a three-place relation we can develop an improved account (which we call EBMgt+) of what evidence-based management can and should be.

The International Agency for Research on Cancer (IARC) is an organization which seeks to identify the causes of human cancer. Per agent, such as betel quid or Human Papillomaviruses, they review the available evidence deriving from epidemiological studies, animal experiments and information about mechanisms (and other data). The evidence of the different groups is combined such that an overall assessment of the carcinogenicity of the agent in question is obtained. In this paper, we critically review the IARC’s carcinogenicity evaluations. First we show that serious objections can be raised against their criteria and procedures – more specifically regarding the role of mechanistic knowledge in establishing causal claims. Our arguments are based on the problem of confounders, of the assessment of the temporal stability of carcinogenic relations, and of the extrapolation from animal experiments. Then we address a very important question, viz. how we should treat the carcinogenicity evaluations that were based on the current procedures. After showing that this question is important, we argue that an overall dismissal of the current evaluations would be too radical. Instead, we argue in favour of a stepwise re-evaluation of the current findings.

A worldview has six components. We concentrate on the first two: the descriptive world model and the explanatory world model. In the first half of the paper we make some general remarks on the methodology of world construction. In the second part, we discuss inconsistencies in world models. Adding new fragments to our world model can lead to inconsistencies. Three strategies are distinguished: (i) a partial return to instrumentalism, (ii) paraconsistency, and (iii) the adaptive option. The latter option is elaborated by means of several historical examples and by means of the EPR paradox.

In this article we criticize two recent articles that examine the relation between explanation and unification. Halonen and Hintikka (1999), on the one hand, claim that no unification is explanation. Schurz (1999), on the other hand, claims that all explanation is unification. We give counterexamples to both claims. We propose a pluralistic approach to the problem: explanation sometimes consists in unification, but in other cases different kinds of explanation (e.g., causal explanation) are required; and none of these kinds is more fundamental

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.

Some social scientists and philosophers (e.g., James Coleman and Jon Elster) claim that all social facts are best explained by means of a micro-explanation. They defend a micro-reductionism in the social sciences: to explain is to provide a mechanism on the individual level. The first aim of this paper is to challenge this view and defend the view that it has to be substituted for an explanatory pluralism with two components: (1) structural explanations of P-, O- and T-contrasts between social facts are more efficient than the competing micro-explanations; and (2) whether a plain social fact (as opposed to a contrast) is best explained in a micro-explanation or a structural explanation depends on the explanatory interest. The second aim of the paper is to show how this explanatory pluralism is compatible with ontological individualism. This paper is motivated by our conviction that explanatory pluralism as defended by Frank Jackson and Philip Pettit is on the right track, but must be further elaborated. We want to supplement their contribution, by (1) introducing the difference between explanations of facts and explanations of contrasts; (2) giving examples from the social sciences, instead of mainly from the natural sciences or common sense knowledge; and (3) emphasizing the pragmatic relevance of explanations on different levels –social, psychological, biological, etc. – which is insufficiently done by Jackson and Pettit.