This essay explores Kaila's interpretation of the special theory of relativity. Although the relevance of his work to logical empiricism is well-known, not much has been written on what Kaila calls the ‘Einstein-Minkowski invariance theory’. Kaila's interpretation focuses on two salient features. First, he emphasizes the importance of the invariance of the spacetime interval. The general point about spacetime invariance has been known at least since Minkowski, yet Kaila applies his overall tripartite theory of invariances to space, time and spacetime (...) in an original way. Second, Kaila provides a non-conventionalist argument for the isotropic speed of electromagnetic signals. The standard Einstein synchrony is not a mere convention but a part of a larger empirical theory. According to Kaila's holistic principle of testability, which stands in contrast to the theses of translatability and verification, different items in the theory cannot be sharply divided into conventional and empirical. Kaila's invariantism/non-conventionalism about relativity reflects an interesting case in the gradual transition from positivism to realism within the philosophy of science. (shrink)

The paper starts with the distinction between conjunction-of-parts accounts and disjunction-of-possibilities accounts to truthlikeness. In Sect. 3, three distinctions between kinds of truthlikeness measures are introduced: comparative versus numeric t-measures, t-measures for qualitative versus quantitative theories, and t-measures for deterministic versus probabilistic truth. These three kinds of truthlikeness are explicated and developed within a version of conjunctive part accounts based on content elements. The focus lies on measures of probabilistic truthlikeness, that are divided into t-measures for statistical probabilities and single (...) case probabilities. The logical notion of probabilistic truthlikeness can be treated as a subcase of deterministic truthlikeness for quantitative theories. In contrast, the epistemic notion of probabilistic truthlikeness creates genuinely new problems, especially for hypotheses about single case probabilities that are evaluated not by comparison to observed frequencies, but by comparison to the truth values of single event statements. By the method of meta-induction, competing theories about single case probabilities can be aggregated into a combined theory with optimal predictive success and epistemic truthlikeness. (shrink)

Abductive reasoning involves finding the missing premise of an “unsaturated” deductive inference, thereby selecting a possible _explanans_ for a conclusion based on a set of previously accepted premises. In this paper, we explore abductive reasoning from a structural proof-theory perspective. We present a hybrid sequent calculus for classical propositional logic that uses sequents and antisequents to define a procedure for identifying the set of analytic hypotheses that a rational agent would be expected to select as _explanans_ when presented with an (...) abductive problem. Specifically, we show that this set may not include the deductively minimal hypothesis due to the presence of redundant information. We also establish that the set of all analytic hypotheses exhausts all possible solutions to the given problem. Finally, we propose a deductive criterion for differentiating between the best _explanans_ candidates and other hypotheses. (shrink)

The idea that sentences can be closer or further apart in meaning is highly intuitive. Not only that, it is also a pillar of logic, semantic theory and the philosophy of science, and follows from other commitments about similarity. The present paper proposes a novel way of comparing the ‘distance’ between two pairs of propositions. We define ‘\ is closer in meaning to \ than \ is to \’ and thereby give a precise account of comparative propositional similarity facts. Notably, (...) our definition eschews metric assumptions, which are unrealistic in most applications of interest. (shrink)

Olav Benjamin Vassend proposes two solutions to the “interpretive problem” of assigning nonzero probabilities to hypotheses that are known to be false. He argues that the verisimilitude interpretation and the counterfactual interpretation are equivalent. While Vassend’s intuition about these two solutions is basically correct, the technical details of his treatment need elaboration and correction. Appropriate tools for combining verisimilitude and Bayesian probabilities can be found in my Truthlikeness.

The scientific realism debate in philosophy of science raises some intriguing methodological issues. Scientific realism posits a link between a scientific theory's observational and referential success. This opens the possibility of testing the thesis empirically, by searching for evidence of such a link in the record of theories put forward in the history of science. Many realist philosophers working today propose case study methodology as a way of carrying out such a test. This article argues that a qualitative method such (...) as case study methodology is not adequate for this purpose, for two reasons: to test scientific realism is to pose an effects‐of‐causes question, and observational and referential success are quantities that theories possess to a greater or lesser degree. The article concludes that an empirical test of scientific realism requires a quantitative method. (shrink)

Truthlikeness is a property of a theory or a proposition that represents its closeness to the truth. We start by summarizing Niiniluoto’s proposal of truthlikeness for deterministic laws, which defines truthlikeness as a function of accuracy, and García-Lapeña’s expanded version, which defines truthlikeness for DL as a function of two factors, accuracy and nomicity. Then, we move to develop an appropriate definition of truthlikeness for probabilistic laws based on Niiniluoto’s suggestion to use the Kullback–Leibler divergence to define the distance between (...) a probability law X\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$X$$\end{document} and the true probability law T\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$T$$\end{document}. We argue that the Kullback–Leibler divergence seems to be the best of the available probability distances to measure accuracy between PL. However, as in the case of DL, we argue that accuracy represents a necessary but not sufficient condition, as two PL may be equally accurate and still one may imply more true or truthlike consequences, behaviours or true facts about the system than the other. The final proposal defines truthlikeness for PL as a function of two factors, p-accuracy and p-nomicity, in intimate connexion with García-Lapeña’s proposal for DL. (shrink)

Truthlikeness is a property of a theory or a proposition that represents its closeness to the truth. According to Niiniluoto, truthlikeness for quantitative deterministic laws can be defined by the Minkowski metric. I present some counterexamples to the definition and argue that it fails because it considers truthlikeness for quantitative deterministic laws to be just a function of accuracy, but an accurate law can be wrong about the actual ‘structure’ or ‘behaviour’ of the system it intends to describe. I develop (...) a modification of Niiniluoto’s proposal that defines truthlikeness for quantitative deterministic laws according to two parameters: accuracy and nomicity. The presented proposal solves the counterexamples and defines a new way of understanding scientific progress. (shrink)

There is a large literature exploring how accuracy constrains rational degrees of belief. This paper turns to the unexplored question of how accuracy constrains knowledge. We begin by introducing a simple hypothesis: increases in the accuracy of an agent’s evidence never lead to decreases in what the agent knows. We explore various precise formulations of this principle, consider arguments in its favour, and explain how it interacts with different conceptions of evidence and accuracy. As we show, the principle has some (...) noteworthy consequences for the wider theory of knowledge. First, it implies that an agent cannot be justified in believing a set of mutually inconsistent claims. Second, it implies the existence of a kind of epistemic blindspot: it is not possible to know that one’s evidence is misleading. (shrink)

Organizational research constitutes a differentiated, complex and fragmented field with multiple contradicting and incommensurable theories that make fundamentally different claims about the social and organizational reality. In contrast to natural sciences, the progress in this field can’t be attributed to the principle of truthlikeness where theories compete against each other and only best theories survive and prove they are closer to the truth and thus demonstrate scientific knowledge accumulation. We defend the structural realist view on the nature of organizational theories (...) in order to demonstrate that despite the multiplicity of isolated and competing explanations of organization-environment relations these theories are still logically compatible and mutually consistent which, in turn, assures theoretical progress in the field. Although postulating different and incompatible ontologies, three most successful organization-environments theories, namely, contingency theory, new institutionalism and population ecology share the same explanations of the relations between organizations and environments at the structural level. Without this principle one would say that what occurs in the field of organization theory is a change rather than a progress. (shrink)