The Logic of Pragmatic Truth

The mathematical concept of pragmatic truth, first introduced in Mikenberg, da Costa and Chuaqui (1986), has received in the last few years several applications in logic and the philosophy of science. In this paper, we study the logic of pragmatic truth, and show that there are important connections between this logic, modal logic and, in particular, Jaskowski's discussive logic. In order to do so, two systems are put forward so that the notions of pragmatic validity and pragmatic truth can be accommodated. One of the main results of this paper is that the logic of pragmatic truth is paraconsistent. The philosophical import of this result, which justifies the application of pragmatic truth to inconsistent settings, is also discussed.     

Factor analysis and AIC

The information criterion AIC was introduced to extend the method of maximum likelihood to the multimodel situation. It was obtained by relating the successful experience of the order determination of an autoregressive model to the determination of the number of factors in the maximum likelihood factor analysis. The use of the AIC criterion in the factor analysis is particularly interesting when it is viewed as the choice of a Bayesian model. This observation shows that the area of application of AIC can be much wider than the conventional i.i.d. type models on which the original derivation of the criterion was based. The observation of the Bayesian structure of the factor analysis model leads us to the handling of the problem of improper solution by introducing a natural prior distribution of factor loadings.The author would like to express his thanks to Jim Ramsay, Yoshio Takane, Donald Ramirez and Hamparsum Bozdogan for helpful comments on the original version of the paper. Thanks are also due to Emiko Arahata for her help in computing.     

Mode distinctions in knowing: The view from perception. Comments on Rönnberg (1990)

Information available for perception has been shown to be specific, to have validity extending over time, and to be meaningful. Thus, cognition cannot be distinguished as that which exclusively provides adaptive coherence of action and reliance on constraints. Transitions between perception and memory/cognition, as two qualitatively distinct modes of knowing, must instead be expected to occur for purposes of ensuring optimal utilization of information relative to its temporal validity and usefulness.     

Differential ordering of objects and attributes

By reference to nominated attributes, a genus, being a population of objects of one specified kind, may be partitioned into species, being subpopulations of different kinds. A prototype is an object representative of its species within the genus. Using this framework, the paper describes how objects can be relatively differentiated with respect to attributes, and how attributes can be relatively differentiating with respect to objects. Methods and rationale for such differential ordering of objects and attributes are presented by example, formal development, and application.For a genus comprisingn species of object there is a subsetP ofn distinct prototypes. With respect tom nominated attributes, each object in has anm-element characterization. Together these determine ann ×m objects × attributes matrix, the rows of which are the characterizations of the prototypical objects. Over then species in , an associated relative frequency vector gives the distribution of objects (and of their characterizations). The matrix and vector associate the objects in with points in a metric space (P, ); and it is with respect to various sums of distances in this attribute space that one can differentially order objects and attributes.The definition of the distance function is generalized across kinds of difference, types of characterization, scale-types of measurement, Minkowskiindex 1, and any form of distribution of objects over species. Explanatory and taxonomic applications in psychology and other fields are discussed, with focus on classification, identification, recognition, and search. The Braille code and the identification of its characters provide illustration.An anticipation and some preliminary indications were given in Sutcliffe and Bristow (1966), Sutcliffe (1972, 1973), and Nowakowska (1975). Subsequently the ideas have been extended and their applications realized in a computer program which, in its development, has so far gone through many minor and three major revisions to its present form in Sutcliffe (1985). The foregoing provided the foundation for the empirical applications and for the presentation in this paper of the ideas in their general form. the research has been supported by funds from the University of Sydney Research Grant and from the Australian Research Grants Scheme. In the working out and exposition of the ideas I have very much benefited from constructive critical comment given by C. R. Latimer, J. B. Michell, G. Oliphant, and E. Seneta, and from the professional programming skills of Michael Wilson and David Shillito. I am grateful for the invitation and the facilities for writing extended during 1983 by Georges Noizet, Laboratoire de Psychologie Expérimentale, Université René Descartes, Paris V, and by Samuel Messick, Vice President for Research, E.T.S. Princeton, N.J. Finally, I acknowledge the improvements in presentation of this paper which have arisen from the editor's and reviewers' comments.     

The role of collateral information about examinees in item parameter estimation

Standard procedures for estimating item parameters in item response theory (IRT) ignore collateral information that may be available about examinees, such as their standing on demographic and educational variables. This paper describes circumstances under which collateral information about examineesmay be used to make inferences about item parameters more precise, and circumstances under which itmust be used to obtain correct inferences.This work was supported by Contract No. N00014-85-K-0683, project designation NR 150-539, from the Cognitive Science Program, Cognitive and Neural Sciences Division, Office of Naval Research. Reproduction in whole or in part is permitted for any purpose of the United States Government. We are indebted to Tim Davey, Eugene Johnson, and three anonymous referees for their comments on earlier versions of the paper.     

行为决策中的描述–经验差距:信息加工角度的解释

选项信息获取过程会影响决策,描述–经验差距简称D-E差距,是指个体进行决策时根据概括性描述信息得到的结果与依据序列体验信息的经验得到的结果之间的差异。文章以认知因素在决策范式演进过程中的角色为线索,梳理了D-E差距的提出及最新的研究发现。参考决策认知过程框架从信息加工角度探讨D-E差距影响因素,从整体上解释D-E差距的原因。未来需要从全面对比两种决策范式,改进经验决策研究方法等角度进行深入探讨。     

On-court position and handedness in visual anticipation of stroke direction in tennis

ObjectivesIn racket sports, players integrate information picked up from their opponent's kinematics and contextual cues like on-court position into shot outcome anticipation. In view of suggested difficulties with anticipating left-handed opponents' action intentions, here we examined whether an opponent's handedness interacts with position-dependency in visual anticipation.Design and methodFollowing a 2 (Group) x 2 (Handedness) x 2 (Position) x 3 (Temporal Occlusion) factorial design, 20 tennis players and 20 non-players predicted directional outcome of temporally manipulated point-light animations of identical left- and right-handed forehand groundstrokes performed near vs. far from the court's midline.ResultsTennis players' response selection was mostly affected by an opponent's on-court position, particularly at an early stage of a hitting movement. Opponents' handedness affected response selection similarly in both groups (i.e., bias towards down-the-line predictions against left-handed strokes occluded at racket-ball-contact), but it did not interact with on-court position.ConclusionsFindings highlight that on-court position, and opponents' handedness to some extent as well, appears relevant for skilled visual anticipation in tennis.     

Testing for Granger Causality in the Frequency Domain: A Phase Resampling Method

This article introduces phase resampling, an existing but rarely used surrogate data method for making statistical inferences of Granger causality in frequency domain time series analysis. Granger causality testing is essential for establishing causal relations among variables in multivariate dynamic processes. However, testing for Granger causality in the frequency domain is challenging due to the nonlinear relation between frequency domain measures (e.g., partial directed coherence, generalized partial directed coherence) and time domain data. Through a simulation study, we demonstrate that phase resampling is a general and robust method for making statistical inferences even with short time series. With Gaussian data, phase resampling yields satisfactory type I and type II error rates in all but one condition we examine: when a small effect size is combined with an insufficient number of data points. Violations of normality lead to slightly higher error rates but are mostly within acceptable ranges. We illustrate the utility of phase resampling with two empirical examples involving multivariate electroencephalography (EEG) and skin conductance data.