Intuitive theories of group types and relational principles

Three studies investigated perceivers’ beliefs about the principles by which different kinds of social groups govern interactions among group members. In Study 1, participants rated a sample of 20 groups on a set of group properties, including measures of relational principles used within groups. Results showed that people believe that interactions in different types of groups are governed by different blends of relational principles unique for each type of group. Study 2 experimentally demonstrated that perceivers could use minimal group property characteristics of different types of groups (i.e., extent of group member interaction, group size, duration, and permeability) to make inferences about the relational principles used in different types of groups. Study 3 demonstrated that relational style information influences people’s judgments of a group’s entitativity and collective responsibility.     

Some implications of a relational principle of reinforcement

A formal statement of a relational principle of reinforcement is developed that makes contact with analyses of choice, interresponse-time distributions, and stimulus control. Some implications for current theoretical and empirical work in the various areas are examined.     

An algorithm for clustering relational data with applications to social network analysis and comparison with multidimensional scaling

A method of hierarchical clustering for relational data is presented, which begins by forming a new square matrix of product-moment correlations between the columns (or rows) of the original data (represented as an n × m matrix). Iterative application of this simple procedure will in general converge to a matrix that may be permuted into the blocked form [_?1¹₁^?1]. This convergence property may be used as the basis of an algorithm (CONCOR) for hierarchical clustering. The CONCOR procedure is applied to several illustrative sets of social network data and is found to give results that are highly compatible with analyses and interpretations of the same data using the blockmodel approach of White (White, Boorman & Breiger, 1976). The results using CONCOR are then compared with results obtained using alternative methods of clustering and scaling (MDSCAL, INDSCAL, HICLUS, ADCLUS) on the same data sets.     

Some extensions of Johnson's hierarchical clustering algorithms

Considerable attention has been given in the psychological literature to techniques of data reduction that partition a set of objects into optimally homogeneous groups. This paper is an attempt to extend the hierarchical partitioning algorithms proposed by Johnson and to emphasize a general connection between these clustering procedures and the mathematical theory of lattices. A goodness-of-fit statistic is first proposed that is invariant under monotone increasing transformations of the basic similarity matrix. This statistic is then applied to three illustrative hierarchical clusterings: two obtained by the Johnson algorithms and one obtained by an algorithm that produces the same chain under hypermonotone increasing transformations of the similarity measures.     

Some applications of graph theory to clustering

This paper attempts to review and expand upon the relationship between graph theory and the clustering of a set of objects. Several graphtheoretic criteria are proposed for use within a general clustering paradigm as a means of developing procedures in between the extremes of complete-link and single-link hierarchical partitioning; these same ideas are then extended to include the more general problem of constructing subsets of objects with overlap. Finally, a number of related topics are surveyed within the general context of reinterpreting and justifying methods of clustering either through standard concepts in graph theory or their simple extensions.     

Clustering with relational constraint

The paper deals with clustering problems where grouping is constrained by a symmetric and reflexive relation. For solving clustering problems with relational constraints two methods are adapted: the standard hierarchical clustering procedure based on the Lance and Williams formula, and local optimization procedure, CLUDIA. To illustrate these procedures, clusterings of the European countries are given based on the developmental indicators where the relation is determined by the geographical neighbourhoods of countries.Extended version of the paper presented at the European meeting of the Psychometric Society, Groningen, June, 19–21, 1980.This work was supported in part by the Boris Kidri Fund, Yugoslavia.     

Bayesian analogy with relational transformations

How can humans acquire relational representations that enable analogical inference and other forms of high-level reasoning? Using comparative relations as a model domain, we explore the possibility that bottom-up learning mechanisms applied to objects coded as feature vectors can yield representations of relations sufficient to solve analogy problems. We introduce Bayesian analogy with relational transformations (BART) and apply the model to the task of learning first-order comparative relations (e.g., larger, smaller, fiercer, meeker) from a set of animal pairs. Inputs are coded by vectors of continuous-valued features, based either on human magnitude ratings, normed feature ratings (De Deyne et al., 2008), or outputs of the topics model (Griffiths, Steyvers, & Tenenbaum, 2007). Bootstrapping from empirical priors, the model is able to induce first-order relations represented as probabilistic weight distributions, even when given positive examples only. These learned representations allow classification of novel instantiations of the relations and yield a symbolic distance effect of the sort obtained with both humans and other primates. BART then transforms its learned weight distributions by importance-guided mapping, thereby placing distinct dimensions into correspondence. These transformed representations allow BART to reliably solve 4-term analogies (e.g., larger:smaller::fiercer:meeker), a type of reasoning that is arguably specific to humans. Our results provide a proof-of-concept that structured analogies can be solved with representations induced from unstructured feature vectors by mechanisms that operate in a largely bottom-up fashion. We discuss potential implications for algorithmic and neural models of relational thinking, as well as for the evolution of abstract thought.     

Working with the relational unconscious: an integration of intrapsychic and relational analysis

From its inception, psychoanalysis has tended to idealize the curative value of insight while devaluing the mutative significance of the analytic relationship. This paper argues that applying the construct of the "relational unconscious" in clinical practice offers a possible resolution of this "mind-relationship" rift. From this perspective, transference and countertransference provoke a continual intersubjective/interpersonal enactment of a co-created infantile drama emanating from the internal worlds of analyst and analysand in which a vital form of parental and/or self loving is at stake. Case vignettes demonstrate how to apply the relational unconscious in clinical practice.     

Syntactic analysis in sentence comprehension: Effects of dependency types and grammatical constraints

This paper presents three experiments on the parsing of Italian wh-questions that manipulate the wh-type (whovs. which-N)and the whextraction site (main clause, dependent clause with or without complementizer). The aim of these manipulations is to see whether the parser is sensitive to the type of dependencies being processed and whether the processing effects can be explained by a unique processing principle, the minimal chain principle (MCP; De Vincenzi, 1991). The results show that the parser, following the MCP, prefers structures with fewer and less complex chains. In particular: (1) There is a processing advantage for the wh-subject extractions, the structures with less complex chains; (2) there is a processing dissociation between the whoand which questions; (3) the parser respects the principle that governs the well-formedness of the empty categories (ECP).     

Some types of conditioned inhibitors carry collateral excitatory associations

Two experiments using summation tests in conditioned suppression with rats examined whether conditioned inhibitors generated by five different conditioning procedures have an associative structure which includes collateral excitatory associations. The existence of collateral conditioned excitation was inferred from an increase in the amount of manifest conditioned inhibition after a conditioned inhibitory stimulus (CS-) extinction treatment. The five CS-s evaluated were differential, explicitly unpaired, conditional, backward, and trace. With abbreviated conditioning (Experiment 1), the differential and explicitly unpaired CS-s exhibited conditioned inhibitory properties; the conditional, backward, and trace CS-s did not. Repeated extinction presentations of the CS- in the absence of the unconditioned stimulus unmasked conditioned inhibition to the conditional, backward, and trace CS-s revealing moderate degrees of conditioned inhibition for all five CS-s. After more extensive conditioning (Experiment 2), the explicitly unpaired and conditional CS-s were strongly inhibitory and the differential and trace CS-s were moderately inhibitory. The backward CS- was not inhibitory. Repeated presentations of the CS- in extinction unmasked conditioned inhibition to trace and backward CS-s. All five CS-s were now nearly equally inhibitory. That the measured inhibitory power of backward, trace, and conditional (after few trials) CS-s can be modulated by a CS- extinction treatment suggests that they have similar associative structures and carry, in addition to inhibitory associations, collateral excitatory associations that mask the expression of conditioned inhibition.     

Some types of error in a choice response task

Errors from a serial response task involving single-finger responses to alphabetic stimuli are analysed and discussed in relation to findings which have been reported from tasks with more compatible stimulus-response relationships. Errors are divided into three distinguishable subsets and in each case found to have longer latencies than correct responses. Those which result from mirroring the required response about the centre of the hand are found to resist elimination during practice and their frequency seems to depend on the type of code used. In all cases error correction times are faster than the times to make a correct response but mirror errors and errors involving a finger adjacent to the correct response are corrected faster than other errors. The findings are discussed in relation to the theory of choice reaction time and error correction.     

An examination of the effect of six types of error perturbation on fifteen clustering algorithms

An evaluation of several clustering methods was conducted. Artificial clusters which exhibited the properties of internal cohesion and external isolation were constructed. The true cluster structure was subsequently hidden by six types of error-perturbation. The results indicated that the hierarchical methods were differentially sensitive to the type of error perturbation. In addition, generally poor recovery performance was obtained when random seed points were used to start theK-means algorithms. However, two alternative starting procedures for the nonhierarchical methods produced greatly enhanced cluster recovery and were found to be robust with respect to all of the types of error examined.     

Evaluating student achievement with a relational database

Commercial database programs such as dBase and Paradox, although developed originally for business applications, are versatile and powerful tools that can be used for an academic purpose such as evaluating student performance. They can be used to write and store test questions, assemble and print classroom or on-line laboratory tests, and calculate grades, test statistics, and so forth. Databases are flexible, unlike textbook “ancillary” test bank programs that are inextricably bound to the strictly linear format and brief shelf life of specific textbook editions. A prototypical relational database program is described, with which an instructor can produce tests based on generic terms adapted from Boneau’s (1990) study of psychological literacy, as well as on behavioral learning objectives adapted from Bloom’s (1956) taxonomy of educational objectives. As a relational database, the program integrates terms, objectives, questions, tests, and test scores, and avoids unnecessary data duplication and waste of computer storage space.     

Classifying types of concept and conceptual structure: Some taxonomies

Abstract

The study of concepts can advance further by clarifying the meanings of basic terms such as “prototype” and by constructing a large-scale primary taxonomy of concept types. This paper presents the latter, based on concept structure, two secondary concept taxonomies and one of conceptual structures. The primary taxonomy organises much data and several previous taxonomies into a single framework. It suggests that many concept types exist, and that type determines how a concept is learned, is used and how it develops. As well as enumerating and interrelating some major types, the taxonomy predicts that many individuals' concepts will consist of mixes of information types. The present study suggests that the field will progress faster by ceasing to look for the single way anything is done. A better strategy is to enumerate concept types, ways each can be learned and developmental patterns, and then see what variables affect these and how common each is.     

Increasing relational memory in childhood with unitization strategies

Young children often experience relational memory failures, which are thought to result from immaturity of the recollection processes presumed to be required for these tasks. However, research in adults has suggested that relational memory tasks can be accomplished using familiarity, a process thought to be mature by the end of early childhood. The goal of the present study was to determine whether relational memory performance could be improved in childhood by teaching young children memory strategies that have been shown to increase the contribution of familiarity in adults (i.e., unitization). Groups of 6- and 8-year-old children were taught to use visualization strategies that either unitized or did not unitize pictures and colored borders. Estimates of familiarity and recollection were extracted by fitting receiver operator characteristic curves (Yonelinas, Journal of Experimental Psychology: Learning, Memory, and Cognition 20, 1341–1354, 1994, Yonelinas, Memory & Cognition 25, 747–763, 1997) based on dual-process models of recognition. Bayesian analysis revealed that strategies involving unitization improved memory performance and increased the contribution of familiarity in both age groups.     

Investigation and its discontents: Some constraints on progress in psychological research

This article examines a number of prominent trends in the conduct of psychological research and considers how they may limit progress in our field. Failure to appreciate important differences in temperament among researchers, as well as differences in the particular talents researchers bring to their work, has prevented the development in psychology of a vigorous tradition of fruitful theoretical inquiry. Misplaced emphasis on quantitative “productivity,” a problem for all disciplines, is shown to have particularly unfortunate results in psychology. Problems associated with the distorting effects of seeking grant support are shown to interact with the first two difficulties. Finally, the distorting effects of certain kinds of experimental studies are discussed, together with their implications for progress in this field.     

Deductive temporal reasoning with constraints

When modelling realistic systems, physical constraints on the resources available are often required. For example, we might say that at most N processes can access a particular resource at any moment, exactly M participants are needed for an agreement, or an agent can be in exactly one mode at any moment. Such situations are concisely modelled where literals are constrained such that at most N, or exactly M, can hold at any moment in time. In this paper we consider a logic which is a combination of standard propositional linear time temporal logic with cardinality constraints restricting the numbers of literals that can be satisfied at any moment in time. We present the logic and show how to represent a number of case studies using this logic. We propose a tableau-like algorithm for checking the satisfiability of formulae in this logic, provide details of a prototype implementation and present experimental results using the prover.     

Establishing a relational field that fosters learning processes: Some tentative propositions derived from trainee experiences

In this article, we look at the recent introduction of more relational-oriented learning principles and how they translate into practice by documenting the experiences of both trainees and instructors. It became clear that actors held different opinions and viewpoints on learning objectives and process ingredients for achieving these objectives. This divergence in opinions resulted in an “impoverished” learning trajectory. We suggest that remedying this situation implies introducing reflexivity regarding learning processes or, stated otherwise, addressing “meta-cognitions” that participants inevitably bring to the process as they affect the way in which people engage in the relational field that encompasses the learning trajectory. Despite some recent arguments in favour of a distinction between cognitive and meta-cognitive mediation, we argue for a similar approach with respect to both types of mediation. We end this article by suggesting that designing learning trajectories with this dual concern in mind might open the road to “learning to learn”.