Erik Weber

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.

We argue that two well-known examples (strawberry distribution and Konigsberg bridges) generally considered genuine cases of distinctively _mathematical_ explanation can also be understood as cases of distinctively _generic_ explanation. The latter answer resemblance questions (e.g., why did neither person A nor B manage to cross all bridges) by appealing to ‘generic task laws’ instead of mathematical necessity (as is done in distinctively mathematical explanations). We submit that distinctively generic explanations derive their explanatory force from their role in ontological unification. Additionally, we argue that distinctively generic explanations are better seen as standardly mathematical instead of distinctively mathematical. Finally, we compare and contrast our proposal with the work of Christopher Pincock on abstract explanations in science and the views of Michael Strevens on abstract causal event explanations.

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 the past 25 years, many philosophers have endorsed the view that the practical value of causal knowledge lies in the fact that manipulation of causes is a good way to bring about a desired change in the effect. This view is intuitively very plausible. For instance, we can predict a storm on the basis of a barometer reading, but we cannot avoid the storm by manipulating the state of the barometer (barometer status and storm are effects of a common cause, viz. atmospheric conditions). In Section 1 we present textual evidence which shows that this view is very popular. In Section 2 we show that this standard view is too restrictive: the practical value of causal knowledge is wider. In Section 3 we introduce the distinction between ‘manipulative policy’ and ‘selective policy’ as a theoretical framework to account for this wider practical value.

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 examinethe 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 explanationis 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.

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 scope of this paper can be clarified by means of a well-known phenomenon that is usually called ‘industrial melanism’: the fact that the melanic form of the peppered moth became dominant in industrial areas in England in the second half of the nineteenth century. Such changes in relative phenotype frequencies are important explananda for population biologists. Apart from trying to explain such changes over time, population biologists also often try to explain differences between populations, e.g. why yellow shell colour is dominant in certain colonies of land snails and almost absent in other colonies. The causal explanations that are given to address such explananda are the objects of analysis in this paper. Our primary aim is to explicate their structure: we want to capture the typical ingredients of causal explanations in population biology, and their organisation. Based on this explication, we discuss how natural selection fits into recent mechanical philosophy of science, and engage in the debate on the nature of evolutionary theory.

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.

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.

The periodic table is one of the best-known systems of classification in science. Because of the information it contains, it raises explanation-seeking questions. Quantum mechanical models of the behaviour of electrons may be seen as providing explanations in response to these questions. In this paper we first address the question ‘Do quantum mechanical models of atoms provide legitimate explanations?’ Because our answer is positive, our next question is ‘Are the explanations provided by quantum mechanical models of atoms mechanistic explanations?’. This question is motivated by the fact that in many scientific disciplines, mechanistic explanations are abundant. Because our answer to the second question is negative, our last question is ‘What kind of explanation do quantum mechanical models of atom provide?’ By addressing these questions, we shed light on the nature of an important type of chemical explanation.