Christian J. Feldbacher-Escamilla

Schurz (Synthese 164:201–234, 2008) proposed a justification of creative abduction on the basis of the Reichenbachian principle of the common cause. In this paper we take up the idea of combining creative abduction with causal principles and model instances of successful creative abduction within a Bayes net framework. We identify necessary conditions for such inferences and investigate their unificatory power. We also sketch several interesting applications of modeling creative abduction Bayesian style. In particular, we discuss use-novel predictions, confirmation, and the problem of underdetermination in the context of abductive inferences.

Rudolf Carnap was one of the earliest proponents of logical positivism/empiricism to explicitly discuss reductionism in relation to mental phenomena from a philosophy of science perspective. In order to address early criticism, Carnap’s account underwent several modifications. An important feature of the ‘mental-to-physical’ reduction endorsed by the later Carnap is that of empirical confirmability. According to this feature, a reduction can only succeed if it carries with it the possibility to confirm or undermine mental claims on the basis of physical claims. Although other modifications of Carnap’s reductionistic account have already been linked to the modern philosophy of mind debate (von Kutschera Erkenntnis 35:305–323, 1991), the role of empirical confirmability in this context remains unexplored terrain. In this paper, we tackle this question and identify relevant modifications in the philosophy of mind with respect to physicalism. We suggest that if one shifts from the metaphysical notion of supervenience to an epistemic derivative of it, one can closely relate supervenience physicalism to Carnap’s account of empirical confirmability. We will show how this both illuminates Carnap’s reductionist program from a philosophy of mind perspective and highlights how the philosophy of mind debate can benefit from Carnap’s account of reduction.

Cultural evolutionary psychology (CEP) accounts for the cultural evolution of cognition. It is based on evolutionary psychology and cultural evolutionary theory and aims at a synthetic attempt which is achieved by what we want to call ‘generalization by recursion’. We argue in this paper that the evolutionary psychology program as a whole could greatly benefit from CEP’s generalization. As we will show, there is one theoretical element in particular, that CEP relevantly generalizes in contrast to its predecessors. It comes from cultural evolutionary theory and has been referred to as the ‘dual inheritance argument’. CEP’s novelty consists in showing that not only cognitive products (‘grist’) but also cognitive mechanisms (‘mills’) are subject to cultural evolution and provides lots of empirical evidence for this claim. This account is ‘recursive’, because CEP’s generalization of the dual inheritance argument theoretically employs a recursive feedback-loop between cultural learning and cultural evolution. We also argue that this account might be considered to supersede unificatory and reductionistic efforts of its competitors, because it is stronger than purely structural or analogical unification while at the same time it is not too strong in order to fall prey to implausible reductionism.

There is a plurality of formal constraints for aggregating probabilities of a group of individuals. Different constraints characterise different families of aggregation rules. In this paper, we focus on the families of linear and geometric opinion pooling rules which consist in linear, respectively, geometric weighted averaging of the individuals’ probabilities. For these families, it is debated which weights exactly are to be chosen. By applying the results of the theory of meta-induction, we want to provide a general rationale, namely, optimality, for choosing the weights in a success-based way by scoring rules. A major argument put forward against weighting by scoring is that these weights heavily depend on the chosen scoring rule. However, as we will show, the main condition for the optimality of meta-inductive weights is so general that it holds under most standard scoring rules, more precisely under all scoring rules that are based on a convex loss function. Therefore, whereas the exact choice of a scoring rule for weighted probability aggregation might depend on the respective purpose of such an aggregation, the epistemic rationale behind such a choice is generally valid.

We discuss two influential views of unification: mutual information unification (MIU) and common origin unification (COU). We propose a simple probabilistic measure for COU and compare it with Myrvold’s (2003, 2017) probabilistic measure for MIU. We then explore how well these two measures perform in simple causal settings. After highlighting several deficiencies, we propose causal constraints for both measures. A comparison with explanatory power shows that the causal version of COU is one step ahead in simple causal settings. However, slightly increasing the complexity of the underlying causal structure shows that both measures can easily disagree with explanatory power. The upshot of this is that even sophisticated causally constrained measures for unification ultimately fail to track explanatory relevance. This shows that unification and explanation are not as closely related as many philosophers thought.

Ever since proposals for generalizing the theory of natural evolution have been put forward, the aims and ambitions of both proponents and critics have differed widely. Some consider such proposals as merely metaphors, some as analogies, some aim at a real generalization and unification, and some have even proposed to work out full reductions. In this paper it is argued that these different forms of generalizing the theory of evolution can be systematically re-framed as different approaches for transferring justification from the natural to the cultural realm, and that their differences are basically a matter of degree. With the help of such a classification it should become clearer what to expect, but also what not to expect from the different approaches.

The SOPhiA conferences are intended to give young predoctoral philosophers the possibility to actively attend a professional conference, to tackle current, as well as classical, philosophical problems, and to discuss their own approaches with promising students from many dierent countries as well as with wellestablished experts. We are firmly convinced that this is a natural and necessary step for promoting the next generation of analytic philosophers and thus, strengthening analytic philosophy in general. Because we believe that the methods of analytic philosophy can be fruitfully applied to all areas of philosophy, the SOPhiA conferences do not have a thematic focus; this is also reflected by the fact that the talks given at SOPhiA 2011 covered all areas of philosophy.

In this paper it is argued that there are relevant similarities of Aristotle's account of definition and Carnap's account of explication. To show this, first, Aristotle's conditions of adequacy for definitions are provided and an outline of the main critique put forward against Aristotle's account of definition is given. Subsequently, Carnap's conditions of adequacy for explications are presented and discussed. It is shown that Aristotle's conditions of extensional correctness can be interpreted against the backdrop of Carnap's condition of similarity once one skips Aristotelian essentialism and takes in a Carnapian and more pragmatic stance. Finally, it is argued that, in general, a complementary rational reconstruction of both approaches allows for resolving problems of interpretational underdetermination.

Generalized Darwinism models cultural development as an evolutionary process, where traits evolve through variation, selection, and inheritance. Inheritance describes either a discrete unit’s transmission or a mixing of traits. In this article, we compare classical models of cultural evolution and generalized population dynamics with respect to blending inheritance. We identify problems of these models and introduce our model, which combines relevant features of both. Blending is implemented as success-based social learning, which can be shown to be an optimal strategy.

There are several proposals to resolve the problem of epistemic peer disagreement which concentrate on the question of how to incorporate evidence of such a disagreement. The main positions in this field are the equal weight view, the steadfast view, and the total evidence view. In this paper we present a new argument in favour of the equal weight view. As we will show, this view results from a general approach of forming epistemic attitudes in an optimal way. By this, the argument for equal weighting can be massively strengthened from reasoning via epistemic indifference to reasoning from optimality.

Schurz (Synthese 164:201–234, 2008) proposed a justification of creative abduction on the basis of the Reichenbachian principle of the common cause. In this paper we take up the idea of combining creative abduction with causal principles and model instances of successful creative abduction within a Bayes net framework. We identify necessary conditions for such inferences and investigate their unificatory power. We also sketch several interesting applications of modeling creative abduction Bayesian style. In particular, we discuss use-novel predictions, confirmation, and the problem of underdetermination in the context of abductive inferences.

The Newtonian research program consists of the core axioms of the Principia Mathematica, a sequence of force laws and auxiliary hypotheses, and a set of methodological rules. The latter underwent several changes and so it is sometimes claimed that, historically seen, Newton and the Newtonians added methodological rules post constructione in order to further support their research agenda. An argument of Duhem, Feyerabend, and Lakatos aims to provide a theoretical reason why Newton could not have come up with his theory of the Principia in accordance with his own methodology: Since Newton’s starting point, Kepler’s laws, contradict the law of universal gravitation, he could not have applied the so-called method of analysis and synthesis. In this paper, this argument is examined with reference to the Principia’s several editions. Newton’s method is characterized, and necessary general background assumptions of the argument are made explicit. Finally, the argument is criticized based on a contemporary philosophy of science point of view.

Certain hypotheses cannot be directly confirmed for theoretical, practical, or moral reasons. For some of these hypotheses, however, there might be a workaround: confirmation based on analogical reasoning. In this paper we take up Dardashti, Hartmann, Thébault, and Winsberg’s (in press) idea of analyzing confirmation based on analogical inference Baysian style. We identify three types of confirmation by analogy and show that Dardashti et al.’s approach can cover two of them. We then highlight possible problems with their model as a general approach to analogical inference and argue that these problems can be avoided by supplementing Bayesian update with Jeffrey conditionalization.

Mereology, the theory of parts and wholes, is sometimes used as a framework for categorisation because it is regarded as ontologically innocent in the sense that the mereological fusion of some entities is nothing over and above the entities. In this paper it is argued that an adequate answer to the question of whether the thesis of the ontological innocence of mereology holds relies crucially on the underlying theory of reference. It is then shown that upholding the thesis comes at high costs, viz. at the cost of a quite strong logical background theory or at paradoxical ways of predicating and counting.