Russell on Negative Judgement

Topoi - This paper concerns Bertrand Russell’s changing views on negative judgement. ‘Negative judgement’ is considered in the context of three theories of judgement that Russell...     

Choice Behaviour in a Computer-Aided Multiattribute Decision Task

Choice behaviour in an interactive multiple-criteria decision-making environment was examined experimentally. The main purpose was to investigate whether subjects are more comfortable in processing criterion/attribute information simultaneously (in parallel) or sequentially. As a research instrument, three different interactive software systems were used on a microcomputer by management students at the Helsinki School of Economics and Business Administration and the Institute of National Economy in Moscow to solve essentially the same problem of buying/leasing a home tailored to the respective decision environments. The experiments also provided us with a possibility to learn useful lessons about how human subjects make computer-supported choices. The results of the experiments are discussed. Furthermore, questions for future research are suggested. © 1997 John Wiley & Sons, Ltd.     

Working memory in very-low-birthweight children at the age of 11 years

The aim of this study is to investigate the working memory (WM) of very-low-birthweight (VLBW, ≤ 1500 g) children at the age of 11 years using Baddeley’s WM model. A regional cohort of 95 VLBW children was assessed for the domains of the WM model (central executive [CE], visuospatial sketchpad [VS], and phonological loop [PL]) using subtests from the Working Memory Test Battery for Children (WMTB-C) and the Wechsler Intelligence Scale for Children – Fourth Edition (WISC-IV). VLBW children were categorized into three groups according to their degree of brain pathology (normal, minor, or major) in neonatal brain magnetic resonance imaging at the term age, and the WM performance was compared between groups to test norms. The structure of the WM model was studied by analyzing correlations among domains. Even VLBW children with normal cognitive development (general ability index ≥ 85) performed worse compared to the test norms (M = 100, SD = 15) on CE (M = 87.64, SD = 20.54, p < .001) and VS (M = 91.65, SD = 11.03, p < .001), but their performance on PL was above the norm (M = 110.79, SD = 13.79, p < .001). VLBW children with major brain pathology performed significantly worse on VS and PL compared to the other groups. The correlations among the WM domains of the VLBW children differ from earlier findings in normative populations. To conclude, the WM of the VLBW children in the study differ—especially in the CE and VS subtest scores—from the normative population irrespective of the degree of brain pathology and level of cognitive development.     

Frege’s <Emphasis Type="Italic">Begriffsschrift</Emphasis> as a <Emphasis Type="Italic">lingua characteristica</Emphasis>

In this paper I suggest an answer to the question of what Frege means when he says that his logical system, the Begriffsschrift, is like the language Leibniz sketched, a lingua characteristica, and not merely a logical calculus. According to the nineteenth century studies, Leibniz’s lingua characteristica was supposed to be a language with which the truths of science and the constitution of its concepts could be accurately expressed. I argue that this is exactly what the Begriffsschrift is: it is a language, since, unlike calculi, its sentential expressions express truths, and it is a characteristic language, since the meaning of its complex expressions depend only on the meanings of their constituents and on the way they are put together. In fact it is in itself already a science composed in accordance with the Classical Model of Science. What makes the Begriffsschrift so special is that Frege is able to accomplish these goals with using only grammatical or syncategorematic terms and so has a medium with which he can try to show analyticity of the theorems of arithmetic.     

An evolutionary approach to support decision making with linear decision models

In this paper we consider decision problems that can be described as linear decision models. These models have been traditionally solved using linear programming, fuzzy linear programming, multiple-objective linear programming or ‘what-if’ analysis. Using these approaches, one encounters a number of difficulties. We propose an ‘evolutionary approach’ to overcome these difficulties. In the proposed approach the decision maker does not have to precisely specify the model (i.e. the objective functions, the RHS values, etc.) at the beginning of the solution procedure. In fact, the model evolves as the solution procedure proceeds.