Characterizations of Negative Definability in Modal Logic

Negative definability ([18]) is an alternative way of defining classes of Kripke frames via a modal language, one that enables us, for instance, to define the class of irreflexive frames. Besides a list of closure conditions for negatively definable classes, the paper contains two main theorems. First, a characterization is given of negatively definable classes of (rooted) finite transitive Kripke frames and of such classes defined using both traditional (positive) and negative definitions. Second, we characterize the negatively definable classes of rooted general frames.     

An abac for the sample range

An abac is computed which gives the probability that at leastq% of the whole population will be included in the range of a random sample of given size. Applications are suggested for testing homogeneity of a sampling from a given population.     

Does trait coping exist? A momentary assessment approach to the evaluation of traits.

This study investigated the extent to which momentary reports of coping are a traitlike phenomenon and the validity of a questionnaire assessment of coping style. Participants (N = 96) completed the questionnaire, then monitored stressful events and coping activities for 2 days using a hand-held computer that administered a brief assessment every 40 min. Momentary reports exhibited a sizable traitlike component: Individual differences accounted for 42% of the variance for 2 coping items and 15-30% of the variance for 15 items. The questionnaire assessment of coping style was a poor predictor of average momentary coping; the coping style measure and the aggregated momentary measure of trait coping shared 23% of their variance for religion and 0-12% for the 16 other coping measures. Self-report assessments of trait coping are poor measures of the trait component of momentary coping and very poor predictors of coping in specific situations.     

Personality described by adjectives: The generalizability of the Big Five to the Italian lexical context

Two studies have been performed in the frame of the Big Five model to describe personality. In the first study, the most useful adjectives for describing personality have been selected, trying to adopt a procedure as objective and empirically driven as possible. The resulting pool of adjectives (n = 492) has been administered to a sample of 274 subjects to verify the emergence of the Big Five in the Italian context. In the second study the pool of original adjectives has been reduced to 260 adjectives selecting the most representative terms (with regard to the factorial structure that has emerged). This pool of 260 adjectives has been administered to a sample of 862 subjects, together with the NEO-PI and the BFQ to facilitate the interpretation of the resulting factorial structure. Results showed the emergence of an Italian Big Five factorial structure that resembles the ‘canonical’ Big Five, although some of the factors, viz. Agreeableness and Emotional Stability, emerged as ‘blended’ dimensions.     

Familiar/interactive raters are not always best: The influence of sampling schedules and class of behavior

Retrospective rating scales are widely used for formal assessment of typical performance. Raters who are the most familiar/interactive with ratees are routinely recommended to maximize the quality of ratings. This caveat to use the most familiar/interactive raters fails to distinguish sampling parameters of the observations on which ratings are based that may be important to assessing different classes of behavior. We hypothesized that systematic observational schedules would be of greater importance to ratings of public events than familiarity/interaction, per se, while the caveat would hold for ratings of private events. We used the Psychotic Inpatient Profile (PIP), which provides separate factor scores for ratings of public and private events, to examine these hypotheses in a quasi-experimental study with adult inpatients of mental hospitals. A large multiinstitutional data set provided retrospective PIP ratings by two types of raters. The most familiar/interactive local clinical staff for each client completed the PIP after observing on an ad lib schedule, along with ongoing job duties. Unfamiliar, noninteractive raters completed the PIP for each client after observing on a systematic time-sampling schedule for purposes of coding an entirely different instrument. Data were selected so that each of 189 clients received PIP scores from four raters, reflecting functioning during the same time period based on day-shift observations by one rater of each type and evening-shift observations by one rater of each type. Analyses of variance, consistency/discriminability of ratings, and prediction of social-action outcomes all supported the hypotheses. We discuss alternative strategies that are better for assessing typical performance in most circumstances. We also provide recommendations for improving the adequacy of observations for those circumstances in which the standardized retrospective rating scale could be a cost-effective assessment strategy.This study was the basis of a master's thesis at the University of Houston by the senior author under the direction of the junior authors. Richard M. Rozelle served on the examination committee. This study was partially supported by grants to Gordon L. Paul from the National Institute of Mental Health, Public Health Service (MH-15353; MH-25464); the Illinois Department of Mental Health and Developmental Disabilities; the Joyce Foundation; the MacArthur Foundation; the Owsley Foundation; the Cullen Foundation; and the Center for Public Policy of the University of Houston.     

The attribution of aggression and grief to body movements: The effect of sex-stereotypes

Forty-two adult subjects, 21 male and 21 female, were asked to rate 16 distinct movement expressions as to their expressiveness of aggression and grief. Each movement expressed anger or grief at one of four levels of diagnosticity. Of each movement two performances were selected, one by a male, the other by a female encoder. With higher levels of diagnosticity, higher ratings were given. The male encoder was rated higher in aggression than the female with movements at a high or moderate level of aggression, and lower than the female with movements at the lowest levels of diagnosticity. The female encoder was rated higher in grief than the male at all levels of diagnosticity.     

Exploring the peer status prototypes: A large-scale latent profile analysis on high-school students from four European countries

Peer status – the regard other group members have of an individual – is fundamental for youth development. Different research traditions developed independent theoretical frameworks conceiving the dimensions underlying social status, and this led to identifying a variety of peer status prototypes. In this work, we explored whether a classification based on the four dimensions of popularity, aggression, dislike, and victimization could integrate the scattered peer status profiles found in the different traditions. A latent profile analysis on 16,224 European students identified the peer status prototypes of popular, bullies, disliked, victims, and average students. Both the peer- and self-reported correlates supported that the five profiles accounted for the large variety of the students' profiles in the literature. These findings suggest that the adoption of a multidimensional approach supported by advanced statistical procedures could identify students' peer status profiles more effectively, replacing classifications based on cutoffs, and leading to a unified students' classification.     

Social Media and Language Processing: How Facebook and Twitter Provide the Best Frequency Estimates for Studying Word Recognition

Corpus‐based word frequencies are one of the most important predictors in language processing tasks. Frequencies based on conversational corpora (such as movie subtitles) are shown to better capture the variance in lexical decision tasks compared to traditional corpora. In this study, we show that frequencies computed from social media are currently the best frequency‐based estimators of lexical decision reaction times (up to 3.6% increase in explained variance). The results are robust (observed for Twitter‐ and Facebook‐based frequencies on American English and British English datasets) and are still substantial when we control for corpus size.