Sex-role norms and gender-related attainment values: Their role in attributions of success and failure

Sex-role norms and gender-related attainment values are considered as possible mediators of gender differences in causal attributions for success and failure. Several revisions of attribution theory are suggested in order to extend the theory to include corollaries concerning sex-role norms. The concept of sex-role consistency is employed as a basis for understanding how sex-role norms affect causal attributions. In addition, gender-related attainment values are hypothesized to affect causal attributions via differential salience and functioning of outcomes. Finally, the analysis is applied to an additional area of achievement-related behavior, gender differences in reward allocation norm choice.     

Refining the theory of basic individual values

We propose a refined theory of basic individual values intended to provide greater heuristic and explanatory power than the original theory of 10 values (Schwartz, 1992). The refined theory more accurately expresses the central assumption of the original theory that research has largely ignored: Values form a circular motivational continuum. The theory defines and orders 19 values on the continuum based on their compatible and conflicting motivations, expression of self-protection versus growth, and personal versus social focus. We assess the theory with a new instrument in 15 samples from 10 countries (N = 6,059). Confirmatory factor and multidimensional scaling analyses support discrimination of the 19 values, confirming the refined theory. Multidimensional scaling analyses largely support the predicted motivational order of the values. Analyses of predictive validity demonstrate that the refined values theory provides greater and more precise insight into the value underpinnings of beliefs. Each value correlates uniquely with external variables.     

Gender differences in the Big Five personality development: A longitudinal investigation from late adolescence to emerging adulthood

The present study aims to investigate gender differences in the mean-level change of the Big Five from late adolescence to emerging adulthood. We analyzed longitudinal self-report data from 192 males and 211 females, using multigroup Latent Growth Modeling. Gender differences were found in the shape of the trajectory, as well as in the mean and in the variance of the growth curve parameters (i.e. the initial level and the rate of change). At time 1 (Age 16), females scored significantly higher on measures of Agreeableness, Conscientiousness, and Openness. Males, in contrast, scored higher than females on a measure of Emotional stability. In both males and females, Conscientiousness and Openness increased linearly from age 16 to age 20, whereas Energy/Extraversion remained stable. Emotional stability slightly increased in males and remained stable in females. Agreeableness increased linearly in males and showed a quadratic trend in females, first increasing and then declining over time. Finally, females showed higher interindividual variability than males on the trajectories of Conscientiousness and Emotional stability.     

The Five Factor Model in personnel selection: Measurement equivalence between applicant and non-applicant groups

This study investigates the measurement equivalence of a Five Factor measure of personality between applicant and non-applicant samples. The Big Five Questionnaire-2 was administered in two samples: A group of volunteers (n = 903), who completed the test for research purposes, and a group applying for jobs, who completed the test during hiring procedures (n = 401). Multiple-group confirmatory factor analysis on item composites was conducted to test for the equivalence of factor covariance and mean structures of twenty facets of the Five Factors. Item-level analyses were carried out through analysis of variance to further examine the issue of measurement invariance. Findings suggested that personality facets have the same measurement unit across applicants and non-applicants, while a lack of equivalence was found in the origin of the scales. Similar results were found at the item-level. Implications for personality assessment are advanced and discussed.     

Influence of numerical magnitudes on the free choice of an object position

The link between numerical magnitude and mechanisms of spatial orienting has been underlined in an increasing number of studies. Similarly, the relationship between numerical magnitude and grasping actions has started to be investigated. The present study focuses on the influence of numerical magnitude processing in the free choice of the position of an object. Participants were presented with a digit (1-9 without 5) and were required to decide whether it was smaller or larger than 5. Then, they had to grasp a small cube and change its position before vocally responding "higher" or "lower". Results showed that in the initial phase of the grasp movement, the grip aperture was modulated by the numerical magnitude. Moreover, participants shifted the position of the cube more leftward with smaller digits compared with larger ones, and they tended to position the object closer to themselves with smaller digits compared with larger ones. These results extend the previous findings indicating that the processing of magnitude is tightly related to the mechanisms of spatial orienting that subserve action execution.     

Space coding for sensorimotor transformations can emerge through unsupervised learning

The posterior parietal cortex (PPC) is fundamental for sensorimotor transformations because it combines multiple sensory inputs and posture signals into different spatial reference frames that drive motor programming. Here, we present a computational model mimicking the sensorimotor transformations occurring in the PPC. A recurrent neural network with one layer of hidden neurons (restricted Boltzmann machine) learned a stochastic generative model of the sensory data without supervision. After the unsupervised learning phase, the activity of the hidden neurons was used to compute a motor program (a population code on a bidimensional map) through a simple linear projection and delta rule learning. The average motor error, calculated as the difference between the expected and the computed output, was less than 3°. Importantly, analyses of the hidden neurons revealed gain-modulated visual receptive fields, thereby showing that space coding for sensorimotor transformations similar to that observed in the PPC can emerge through unsupervised learning. These results suggest that gain modulation is an efficient coding strategy to integrate visual and postural information toward the generation of motor commands.