Online research in philosophy

This paper proposes a solution to David Miller's Minnesotan-Arizonan demonstration of the language dependence of truthlikeness (Miller 1974), along with Miller's first-order demonstration of the same (Miller 1978). It is assumed, with Peter Urbach, that the implication of these demonstrations is that the very notion of truthlikeness is intrinsically language dependent and thus non-objective. As such, truthlikeness cannot supply a basis for an objective account of scientific progress. I argue that, while Miller is correct in arguing that the number of true atomic sentences of a false theory is language dependent, the number of known sentences (under certain straightforward assumptions) is conserved by translation; degree of knowledge, unlike truthlikeness, is thus a linguistically invariant notion. It is concluded that the objectivity of scientific progress must be grounded on the fact (noted in Cohen 1980) that knowledge, not mere truth, is the aim of science.

In a famous critique, Goodman dismissed similarity as a slippery and both philosophically and scientifically useless notion. We revisit his critique in the light of important recent work on similarity in psychology and cognitive science. Specifically, we use Tversky’s influential set-theoretic account of similarity as well as Gärdenfors’s more recent resuscitation of the geometrical account to show that, while Goodman’s critique contained valuable insights, it does not warrant a dismissal of similarity.

In a famous critique, Goodman dismissed similarity as a slippery and both philosophically and scientifically useless notion. We revisit his critique in the light of important recent work on similarity in psychology and cognitive science. Specifically, we use Tversky’s influential set-theoretic account of similarity as well as Gärdenfors’s more recent resuscitation of the geometrical account to show that, while Goodman’s critique contained valuable insights, it does not warrant a dismissal of similarity.

A qualitative theory of truthlikeness, based on a family of quantitative measures, is developed for hypotheses that are concerned with the values of a finite number of real-valued quantities. Representing hypotheses by subsets of n, I first show that a straightforward application of the basic ideas of the similarity approach to truthlikeness does not work out for hypotheses with zero n-dimensional Lebesgue measure. However, it is easy to give a counterpart for the average measure preferred by Pavel Tichý and Graham Oddie in terms of Hausdorff measures. The task of finding analogies of the min-sum-measure preferred by Ilkka Niiniluoto is more interesting. I present and discuss analogies of two different types for this measure.

A holistic account of the meaning of theoretical terms leads scientific realism into serious troubles. Alternative methods of reference fixing are needed by a realist who wishes to show how reference invariance is possible in spite of meaning variance. This paper argues that the similarity theory of truthlikeness and approximate truth, developed by logicians since the mid 1970s, helps to make precise the idea of charitable theoretical reference. Comparisons to the recent proposals by Kitcher and Psillos are given. This argument helps to undermine the scepticist meta-induction about theories, and thereby to reevaluate Laudan's alleged confutation of scientific realism.

The most elaborate recent accounts of truthlikeness (verisimilitude) apply this notion primarily to generalizations in first-order languages with qualitative predicates. This paper outlines a new approach to the definition of truthlikeness for quantitative statements, including singular statements (point estimation), interval statements (interval estimation), and quantitative laws. In the case of laws, the basic issue is reduced to the topological problem of measuring the distance between two real-valued functions. The solution of this problem makes it possible to define also the notion of approximate truth for quantitative laws.

The purpose of this paper is to look at some existing methods of semantic information quantification and suggest some alternatives. It begins with an outline of Bar-Hillel and Carnap’s theory of semantic information before going on to look at Floridi’s theory of strongly semantic information. The latter then serves to initiate an in-depth investigation into the idea of utilising the notion of truthlikeness to quantify semantic information. Firstly, a couple of approaches to measure truthlikeness are drawn from the literature and explored, with a focus on their applicability to semantic information quantification. Secondly, a similar but new approach to measure truthlikeness/information is presented and some supplementary points are made.

The modern history of verisimilitude can be divided into three periods. The first began in 1960, when Karl Popper proposed his qualitative definition of what it is for one theory to be more truthlike than another theory, and lasted until 1974, when David Miller and Pavel Trich published their refutation of Popper's definition. The second period started immediately with the attempt to explicate truthlikeness by means of relations of similarity or resemblance between states of affairs (or their linguistic representations); the work within this similarity approach was summarized in the books of Graham Oddie [1986] and Ilkka Niiniluoto [1987]. During the subsequent third period, studies in verisimilitude have been actively continued, and interesting results and applications have been achieved, but not many dramatic novelties. While it is now obsolete to claim that truthlikeness with reasonable properties cannot be defined at all, there is still a lot of controversy about the best and least arbitrary approach to doing this.

This paper studies the interplay between two notions which are important for the project of defending scientific realism: abduction and truthlikeness. The main focus is the generalization of abduction to cases where the conclusion states that the best theory is truthlike or approximately true. After reconstructing the recent proposals of Theo Kuipers within the framework of monadic predicate logic, I apply my own notion of truthlikeness. It turns out that a theory with higher truthlikeness does not always have greater empirical success than its less truthlike rivals. It is further shown that the notion of expected truthlikeness provides a fallible link from the approximate explanatory success of a theory to its truthlikeness. This treatment can be applied also in cases where even the best potential theory is an idealization that is known to be false.

J. P. Z. Bonilla's methodological approach to truthlikeness is evaluated critically. On a more general level, various senses in which the theory of truthlikeness could be seen as a theory concerned with methodology are distinguished, and it is argued that providing speical sciences with methodological tools is unrealistic as an aim of the theory of verisimilitude. Rather, when developing this theory, one should rest contnet with the more modest aim of conceptual analysis, or of providing explications for the relational concept of being closer to the truth. In addition, some remarks will be made on the difficulties which the similarity approach to truthlikeness has in realizing this aim and which are caused by the important role that Hintikka's constituents have in it.