THE AIMS OF TYPOLOGIES AND A TYPOLOGY OF METHODS

Typologies like Ian Barbour's have been widely used—and critiqued—in religion-and-science. Several alternatives have been proposed by, for example, John Haught, Willem Drees, Mikael Stenmark, and Shoaib Ahmed Malik. However, there has been a surprising deficit in discussion of what we wish typologies to do in religion and science in the first place. In this article, I provide a general analysis of typologies in religion-and-science by (1) providing a classification of existing typologies as conclusion- or concept-oriented; (2) showing that typologies are used, or expected to be used, as first-order categorizations of how religion and science are related and as second-order classifications of scholars/scholarly works; (3) discussing several aims which we might want typologies to achieve in their second-order usage; and (4) presenting a new kind of typology focused on the methods used by scholars which achieves those aims in a unique way.     

Proof-Theoretic Modal PA-Completeness II: The Syntactic Countermodel

This paper is the second part of the syntactic demonstration of the Arithmetical Completeness of the modal system G, the first part of which is presented in [9]. Given a sequent S so that ⊢_GL-LIN S, ⊬_G S, and given its characteristic formula H = char(S), which expresses the non G-provability of S, we construct a canonical proof-tree T of ~ H in GL-LIN, the height of which is the distance d(S, G) of S from G. T is the syntactic countermodel of S with respect to Gand is a tool of general interest in Provability Logic, that allows some classification in the set of the arithmetical interpretations. This revised version was published online in June 2006 with corrections to the Cover Date.     

The classification of neuropsychological deficit

The study involves classification of neuropsychiatric patients on the basis of neuropsychological and intelligence test performance. One hundred twenty-five hospitalized male neuropsychiatric patients with various diagnoses were administered the Halstead-Reitan and Luria-Nebraska neuropsychological test batteries, as well as the Wechsler Adult Intelligence Scale. A cluster analysis was performed for each of those three procedures utilizing Ward's method. It was found in all cases that clusters were determined on the basis of level rather than pattern of performance. Relationships were found between cluster membership and age, education, and presence or absence of structural brain damage but were not found for diagnoses of schizophrenia or alcoholism. Schizophrenic and alcoholic patients were found in all clusters in the case of all three test procedures. Differences in clustering among the three test procedures were noted, with the WAIS being relatively more sensitive to educational differences while the Halstead-Reitan was more sensitive to age differences. The clinical utility of classifying patients on the basis of neuropsychological and cognitive test performance was discussed.Acknowledgement is made to the Veterans Administration for support of this research.     

Two-group classification in latent trait theory: Scores with monotone likelihood ratio

This paper deals with two-group classification when a unidimensional latent trait,, is appropriate for explaining the data,X. It is shown that ifX has monotone likelihood ratio then optimal allocation rules can be based on its magnitude when allocation must be made to one of two groups related to. These groups may relate to probabilistically via a non-decreasing functionp(), or may be defined by all subjects above or below a selected value on.In the case where the data arise from dichotomous items, then only the assumption that the items have nondecreasing item characteristic functions is enough to ensure that the unweighted sum of responses (the number-right score or raw score) possesses this fundamental monotone likelihood ratio property.     

DSM-IV Literature reviews: Rationale,process, and limitations

DSM-IV will benefit from the extensive research and interest in diagnosis generated in large part by DSM-III. The development of DSM-IV is proceeding through three stages of empirical documentation, including literature reviews, analysis of unpublished data sets, and field trials. This paper discusses the rationale, process, and limitations of the literature reviews. The purpose of the literature reviews is to provide and to document a comprehensive review of the clinical and empirical literature to facilitate objective and empirically based decisions. The review process is guided by the explicit and systematic methods developed within meta-analysis. Limitations of the reviews are also discussed.The opinions expressed in this paper are those of the authors and do not necessarily represent the position of the American Psychiatric Association and its Task Force on DSM-IV.     

Negotiating criteria and setting limits: The case of aids

The classification of clinical problems, such as AIDS, requires choices. Choices are made on epistemic (i.e., knowledge-based) and non-epistemic (i.e., action-based) grounds. That is, the ways in which we classify clinical problems, such as AIDS, involve a balancing of different understandings of clinical reality and of clinical values among participants of the clinical community. On this view, the interplay between epistemic and non-epistemic interests occurs within the embrace of particular clinical contexts.The ways in which we classify AIDS is the topic of this paper. We consider the extent to which we construct clinical reality; we examine a suggested classification of AIDS; and we conclude suggesting that the choice regarding how to classify AIDS is the result of negotiation among participants in the clinical community.     

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.     

Invariance Properties for General Diagnostic Classification Models

In item response theory (IRT), the invariance property states that item parameter estimates are independent of the examinee sample, and examinee ability estimates are independent of the test items. While this property has long been established and understood by the measurement community for IRT models, the same cannot be said for diagnostic classification models (DCMs). DCMs are a newer class of psychometric models that are designed to classify examinees according to levels of categorical latent traits. We examined the invariance property for general DCMs using the log-linear cognitive diagnosis model (LCDM) framework. We conducted a simulation study to examine the degree to which theoretical invariance of LCDM classifications and item parameter estimates can be observed under various sample and test characteristics. Results illustrated that LCDM classifications and item parameter estimates show clear invariance when adequate model data fit is present. To demonstrate the implications of this important property, we conducted additional analyses to show that using pre-calibrated tests to classify examinees provided consistent classifications across calibration samples with varying mastery profile distributions and across tests with varying difficulties.     

Human age classification using facial skin aging features and artificial neural network

In this paper a novel method based on facial skin aging features and Artificial Neural Network (ANN) is proposed to classify the human face images into four age groups. The facial skin aging features are extracted by using Local Gabor Binary Pattern Histogram (LGBPH) and wrinkle analysis. The ANN classifier is designed by using two layer feedforward backpropagation neural networks. The proposed age classification framework is trained and tested with face images from PAL face database and shown considerable improvement in the age classification accuracy up to 94.17% and 93.75% for male and female respectively.