‘He's got his father's bias’: Parental influence on weight bias in young children

Our aim was to explore the role of parents in the transmission of stereotypical body size attitudes and awareness of weight loss strategies to preschool children. Participants were 279 3‐year‐old children and their parents, who provided data at baseline and 1 year later. Parents completed self‐report body size attitude and dieting measures. Child weight bias and awareness of weight loss strategies were assessed through interview. Over time, negative associations with large bodies and awareness of weight loss strategies increased. Fathers’ attitudes prospectively predicted boys’ weight bias and awareness of weight loss strategies. Among girls, parental attitudes were less predictive. Findings confirm the importance of fathers in the development of boys’ body attitudes and inform prevention programmes.     

The Embodied Penman: Effector‐Specific Motor–Language Integration During Handwriting

Several studies have illuminated how processing manual action verbs (MaVs) affects the programming or execution of concurrent hand movements. Here, to circumvent key confounds in extant designs, we conducted the first assessment of motor–language integration during handwriting—a task in which linguistic and motoric processes are co‐substantiated. Participants copied MaVs, non‐manual action verbs, and non‐action verbs as we collected measures of motor programming and motor execution. Programming latencies were similar across conditions, but execution was faster for MaVs than for the other categories, regardless of whether word meanings were accessed implicitly or explicitly. In line with the Hand‐Action‐Network Dynamic Language Embodiment (HANDLE) model, such findings suggest that effector‐congruent verbs can prime manual movements even during highly automatized tasks in which motoric and verbal processes are naturally intertwined. Our paradigm opens new avenues for fine‐grained explorations of embodied language processes.     

Two ways of learning associations

How people learn chunks or associations between adjacent items in sequences was modelled. Two previously successful models of how people learn artificial grammars were contrasted: the CCN, a network version of the competitive chunker of Servan‐Schreiber and Anderson [J. Exp. Psychol.: Learn. Mem. Cogn. 16 (1990) 592], which produces local and compositionally‐structured chunk representations acquired incrementally; and the simple recurrent network (SRN) of Elman [Cogn. Sci. 14 (1990) 179], which acquires distributed representations through error correction. The models' susceptibility to two types of interference was determined: prediction conflicts, in which a given letter can predict two other letters that appear next with an unequal frequency; and retroactive interference, in which the prediction made by a letter changes in the second half of training. The predictions of the models were determined by exploring parameter space and seeing howdensely different regions of the space of possible experimental outcomes were populated by model outcomes. For both types of interference, human data fell squarely in regions characteristic of CCN performance but not characteristic of SRN performance.     

Developing an efficient clinical information system for a comprehensive psychiatric institute: I. Principles,design, and organization

The principles, design considerations, and components of a clinical information system intended to support and enhance the patient care, educational, and research missions of a comprehensive psychiatric institute are presented. Major characteristics of the system are its emphases on efficiency, simplicity, and intensive user involvement throughout the development of the system.     

LISP: An introduction and some great programs

Some of the advantages of LISP and some of its unsavory reputation are discussed. Some LISP programs in a variety of areas (chemistry, medicine, question answering, natural language, mathematics, airline tariffs, etc.) are briefly described.     

A representation theorem for languages with generalized quantifiers through back-and-forth methods

We obtain in this paper a representation of the formulae of extensions ofL by generalized quantifiers through functors between categories of first-order structures and partial isomorphisms. The main tool in the proofs is the back-and-forth technique. As a corollary we obtain the Caicedo's version of Fraïssés theorem characterizing elementary equivalence for such languages. We also discuss informally some geometrical interpretations of our results.