Starting from the sixties of the past century theory change has become a main concern of philosophy of science. Two of the best known formal accounts of theory change are the post-Popperian theories of verisimilitude (PPV for short) and the AGM theory of belief change (AGM for short). In this paper, we will investigate the conceptual relations between PPV and AGM and, in particular, we will ask whether the AGM rules for theory change are effective means for approaching the truth, (...) i.e., for achieving the cognitive aim of science pointed out by PPV. First, the key ideas of PPV and AGM and their application to a particular kind of propositional theories - the so called "conjunctive propositions" - will be illustrated. Afterwards, we will prove that, as far as conjunctive propositions are concerned, AGM belief change is an effective tool for approaching the truth. (shrink)

In what follows, I will give examples of the sorts of step that can be taken towards spelling out the intuition that, after all, good models might be true. Along the way, I provide an outline of my account of models as ontologically and pragmatically constrained representations. And I emphasize the importance of examining models as functionally composed systems in which different components play different roles and only some components serve as relevant truth bearers. This disputes the standard approach that (...) proceeds by simply counting true and false elements in models in their entirety and concludes that models are false since they contain so many false elements. I call my alternative the functional decomposition approach. (shrink)

Funding policies for science are usually directed at supporting technological innovations. The im-pact and success of such policies depend crucially on how science and technology are connected to each other. I propose an “interactive view” of the relationship between basic science and technol-ogy development which comprises the following four claims: First, technological change derives from science but only in part. The local models used in accounting for technologically relevant phenomena contain theoretical and non-theoretical elements alike. Second, existing technologies and rules (...) of experience constitute another major repository of technological inventions. Third, technology dynamics is only weakly coupled to progress in basic science but it is closely related to science. There is a dependence of technological change on a more fundamental understanding, to be sure, but it is of an indirect and long-term character. Fourth, progress in basic research is some-times the effect of technological change. Technological change sometimes brings about increased theoretical understanding. (shrink)

'Structural realism' is a buzzword in the scientific realism debate. Various positions with diverse motivations fall under this label. A much advertised distinction is between epistemic and ontological forms of structuralism. This paper scrutinizes the alleged dichotomy between these two 'alternatives', and criticises the considerations that have been taken to motivate the ontic variety over the epistemic. I will argue that ontological structural realism is not called for within the traditional realism debate.

Interpretation in science has gained little attention in the past because philosophers of science believed that interpretation belongs to the context of discovery or must be associated with meaning. But scientists often speak about interpretation when they report their findings. Elsewhere I have argue in favour of a pragmatic-rhetorical theory of explanation, and it is in light of this theory that I suggest we can understand interpretation in the natural sciences.

Statistical inference is often justified by long-run properties of the sampling distributions, such as the repeated sampling rationale. These are frequentist justifications of statistical inference. I argue, in line with existing philosophical literature, but against a widespread image in empirical science, that these justifications are flawed. Then I propose a novel interpretation of probability in statistics, the artefactual interpretation. I believe that this interpretation is able to bridge the gap between statistical probability calculations and rational decisions on the basis of (...) observed data. The artefactual interpretation is able to justify statistical inference without making any assumptions about probability in the material world. (shrink)

In this paper it is argued that the multiple realizability argument and Kripke's argument are based on schemas of identifications rather than identification. In fact, "heat = molecular motion" includes a term "molecular motion" that does not capture a natural kind, nor has a unique referent. If properly framed, this schema suits also for the type identity theory of mind. Some consequences of this point are evaluated.

situation in the sciences of man and show it to be fallacious. On the view to be 6 rejected, the sciences of man are undergoing the first serious attempt in history to 7 thoroughly naturalize their subject matter and thus to put an end to their separate sta- 8 tus. Progress has (on this view) been quite considerable in the disciplines in charge 9 of the individual, while in the social sciences the outcome of the process is moot: 10 the (...) naturalistic social sciences are still in their infancy, and whether they will even- 11 tually engulf or at least profoundly transform the field of social science is unclear. 12 The dichotomous conception pits two camps against one another. On the one hand, 13.. (shrink)

Graphical models are a powerful tool for causal model specification. Besides allowing for a hierarchical representation of variable interactions, they do not require any a priori specification of the functional dependence between variables. The construction of such graphs hence often relies on the mere testing of whether or not model variables are marginally or conditionally independent. The identification of causal relationships then solely requires some general assumptions on the relation between stochastic and causal independence, such as the Causal Markov Condition (...) and the Faithfulness Condition (Spirtes et al. 2000; Pearl 2000). However, a procedure would require further assumptions to hold. Namely those the independence tests themselves are based on. In continuous settings, Spirtes et al. (2000) suggest causal inference based on a very restrictive formulation of independence, that is, vanishing partial correlations. Such a measure does, however, limit the applicability of causal inference to linear systems. This constitutes a serious drawback especially for the social sciences where an a priori specification of the functional form proves difficult or at odds with linearity. In short: graphical models theoretically reduce specification uncertainty regarding functional dependence, but their implementation in practice deprives them of this virtue. In this paper we investigate how causal structures in continuous settings can be identified when both functional forms and probability distributions of the variables remain unspecified. We focus on tests exploiting the fact that if X and Y are conditionally independent given a set of variables Z, the two conditional densities f (X|Y, Z) and f (X|Z) must coincide. We start by estimating the conditional densities f(X|Y, Z) and f(X|Z) via nonparametric techniques (kernel methods). We proceed by testing if some metric expressing the distance between these very conditional densities is sufficiently close to zero. Out of several metrics available in the literature to express such distance we choose two, the Euclidean, and the Hellinger distance. We investigate in a Monte Carlo study how different tests involving either measure are able to detect statistical independence, conditioned on a small set of variables. One limitation may result from nonparametric density estimation being subject to the curse of dimensionality. As the number of variables increases, the estimated empirical density converges at a slower rate to its population value. To compensate this drawback we use a local bootstrap procedure which consists of resampling the data for each test. While local bootstrap strongly increases the computational time of the test, it succeeds in counterbalancing the curse of dimensionality. (shrink)

In this article I examine whether an influential theory of mechanisms proposed by Peter Machamer, Lindley Darden and Carl Craver can accommodate polygenic effects. This theory is both interesting and problematic, I will argue, because it ascribes a central role to activities. In it, activities are needed not only to constitute mechanisms but also to perform their causal role. These putative functions of activities become problematic in certain situations where several causes or elements of a mechanism contribute simultaneously, i.e. with (...) certain forms of polygenic causation. The problematic form of polygeny, polygeny 2, occurs when the polygenic contribution concerns one and the same property or aspect of the affected object. When the result of such causation is that nothing happens, the theory suggested by Machamer and his colleagues cannot be applied. More generally, it seems that, whenever polygeny 2 is involved, the Machamer approach leads to an impoverished conception of mechanism. (shrink)

According to the theory of meaning as justification, semantics is closely entangled with epistemology: knowing the meaning of an utterance amounts to knowing the justification one may offer for it. In this perspective, the theory of meaning is connected with the epistemic theory of justification, namely the theory that undergoes the more explicit attempts of naturalization. Is it possible to extend those attempts to the notion of meaning? There are many ways of naturalizing the notion of meaning, independently of its (...) links with the notion of justification. Our goal in this paper is to explore the possibility of naturalizing meaning using those very links. To this aim, we will evaluate in brief three main directions: a) the interaction between justification and discovery; b) Quine's naturalized epistemology; c) the naturalization of logic. (shrink)