11 research outputs found
Personality profiles of cultures: aggregate personality traits
Personality profiles of cultures can be operationalized as the mean trait levels of culture members. College students from 51 cultures rated an individual from their country whom they knew well (N = 12, 156). Aggregate scores on Revised NEO Personality Inventory scales generalized across age and gender groups, approximated the individual-level Five-Factor Model, and correlated with aggregate self-report personality scores and other culture-level variables. Results were not attributable to national differences in economic development or to acquiescence. Geographical differences in scale variances and mean levels were replicated, with Europeans and Americans generally scoring higher in Extraversion than Asians and Africans. Findings support the rough scalar equivalence of NEO-PI-R factors and facets across cultures, and suggest that aggregate personality profiles provide insight into cultural differences
Human Emotions: Theories and Processes. The Psychology of Emotion: Theories of Emotion in Perspective (4th edn). K. T. Strongman. Wiley, New York, 1996, 255 pp. Changing Moods, the Psychology of Mood and Mood Regulation. B. Parkinson, P. Totterell, R. B. Briner and S. Reynolds. Addison-Wesley-Longman, New York, 1996, 254 pp.
Replicable types and subtypes of personality: Spanish NEO-PI samples
Three major personality prototypes were derived on the basis of a Big Five instrument (NEO-PI) by means of replicated cluster analysis in two Spanish samples (a sample from the general population and a student sample). The replicability of the three prototypes within and their consistency between the two samples were evaluated. In addition, subtypes were analysed in a similar way. Finally, the relation between prototype assignment and level of education was examined in the sample from the general population. Within-study replicability was satisfactory only for the student sample. Comparison with the results for a similar instrument (NEO-PI-R) applied to a German sample showed satisfactory consistency only for the student sample. Discussion centres on the strong sample dependency of the results. Copyright # 2002 John Wiley & Sons, Ltd
Nature over nurture: temperament personality and lifespan
Temperaments are often regarded as biologically based psychological tendencies with intrinsic paths of development. It is argued that this definition applies to the personality traits of the five-factor model. Evidence for the endogenous nature of traits is summarized from studies of behavior genetics, parent¿child relations, personality structure, animal personality, and the longitudinal stability of individual differences. New evidence for intrinsic maturation is offered from analyses of NEO Five-Factor Inventory scores for men and women age 14 and over in German, British, Spanish, Czech, and Turkish samples (N = 5,085). These data support strong conceptual links to child temperament despite modest empirical associations. The intrinsic maturation of personality is complemented by the culturally conditioned development of characteristic adaptations that express personality; interventions in human development are best addressed to these. (PsycINFO Database Record (c) 2010 APA, all rights reserved
National character does not reflect mean personality trait levels in 49 cultures
Most people hold beliefs about psychological characteristics typical of members of their own and others' cultures. These perceptions of national character may be generalizations from personal experience, or stereotypes with or without a “ kernel of truth." We obtained national character ratings from 49 cultures and compared them to average personality scores of culture members as assessed by observer ratings and self-reports. National character ratings appeared to be reliable and valid measures, but they did not converge with assessed personality traits. Perceptions of national character thus appear to be unfounded stereotypes that may serve the function of maintaining a national identity
Universal features of personality traits from the observer’ s perspective: data from 50 cultures
To test hypotheses about the universality of personality traits, college students in 50 cultures identified an adult or college-age man or woman whom they knew well and rated the 11, 985 targets using the third-person version of the Revised NEO Personality Inventory. Factor analyses within cultures showed that the normative American self-report structure was clearly replicated in most cultures, and was recognizable in all. Sex differences replicated earlier self-report results, with the most pronounced differences in Western cultures. Cross-sectional age differences for three factors followed the pattern identified in self-reports, with moderate rates of change during college age and very slow changes after age 40. With a few exceptions, these data support the hypothesis that features of personality traits are common to all human groups
Multi-year linkage and association mapping confirm the high number of genomic regions involved in oilseed rape quantitative resistance to blackleg
Beyond the imitation game: Quantifying and extrapolating the capabilities of language models
Language models demonstrate both quantitative improvement and new qualitative capabilities with increasing scale. Despite their potentially transformative impact, these new capabilities are as yet poorly characterized. In order to inform future research, prepare for disruptive new model capabilities, and ameliorate socially harmful effects, it is vital that we understand the present and near-future capabilities and limitations of language models. To address this challenge, we introduce the Beyond the Imitation Game benchmark (BIG-bench). BIG-bench currently consists of 204 tasks, contributed by 442 authors across 132 institutions. Task topics are diverse, drawing problems from linguistics, childhood development, math, common-sense reasoning, biology, physics, social bias, software development, and beyond. BIG-bench focuses on tasks that are believed to be beyond the capabilities of current language models. We evaluate the behavior of OpenAI's GPT models, Google-internal dense transformer architectures, and Switch-style sparse transformers on BIG-bench, across model sizes spanning millions to hundreds of billions of parameters. In addition, a team of human expert raters performed all tasks in order to provide a strong baseline. Findings include: model performance and calibration both improve with scale, but are poor in absolute terms (and when compared with rater performance); performance is remarkably similar across model classes, though with benefits from sparsity; tasks that improve gradually and predictably commonly involve a large knowledge or memorization component, whereas tasks that exhibit "breakthrough" behavior at a critical scale often involve multiple steps or components, or brittle metrics; social bias typically increases with scale in settings with ambiguous context, but this can be improved with prompting