Christian J. Feldbacher-Escamilla

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.

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.

In the debate of epistemic peer disagreement the equal-weight view suggests to split the difference between one's own and one's peer's opinions. An argument in favour of this view---which is prominently held by Adam Elga---is that by such a difference-splitting one may make some use of a so-called wise-crowd effect. In this paper it is argued that such a view faces two main problems: First, the problem that the standards for making use of a wise-crowd effect are quite low. And second, the problem that following the equal-weight view decreases such effects and by this the argument's own basis is defeated. We therefore come to the conclusion that an argument for the equal-weight view with the help of wise-crowd effects as provided more or less explicitly by Elga does not succeed.

The standard approach to solve prediction tasks is to apply inductive methods such as, e.g., the straight rule. Such methods are proven to be access-optimal in specific prediction settings, but not in all. Within the optimality-approach of meta-induction, success-based weighted prediction methods are proven to be access-optimal in all possible continuous prediction settings. However, meta-induction fails to be access-optimal in so-called demonic discrete prediction environments where the predicted value is inversely correlated with the true outcome. In this paper the problem of discrete prediction environments is addressed by embedding them into a synchronised prediction setting. In such a setting the task consists in providing a discrete and a continuous prediction. It is shown that synchronisation constraints exclude the possibility of demonic environments.

Sometimes the cognitive part of the human mind is modelled in a simplified way by degrees of belief. E.g., in philosophy of science and in formal epistemology agents are often identified by their credences in a set of claims. This line of dealing with the individual mind is currently expanded to groups by attempts of finding adequate ways of pooling individual degrees of belief into an overall group credence or, more abstractly speaking, into a collective mind. In this paper, we model religious people’s minds as such a collective mind. Religious people are therein identified with a set of degrees of beliefs containing religious and secular credences. E.g., within a religious context a person may be sure that some statement is true, whereas the same person lacks non-religious support for such a credence and hence may doubt the truth of that statement within a secular context. We will also present two results on the adequacy of this model.

One challenge of societies in the 21st century is the conflict of norms between different cultures. In Ancient Greece, too, such conflicts arose, and great thinkers offered great solutions. In this contribution we will argue for the following: - Ancient ethical theories were not only individual ethical theories but also social ethical theories (II). - The ancient methods of scientific examinations are useful not only in classical sciences but also in ethics (III). - Accepting the result of (III) yields highly interesting theoretical results about conflicts of norms between different cultures (IV).