Fundamental Dimensions of Social Judgment: Sociability and Morality as Distinct Characteristics of Social Warmth

The present dissertation focuses on the two basic dimensions of social judgment, i.e., warmth and competence. Previous research has shown that warmth and competence emerge as fundamental dimensions both at the interpersonal level and at the group level. Moreover, warmth judgments appear to be primary, reflecting the importance of first assessing others’ intentions before determining the other’s ability to carry out those intentions. Finally, it has been shown that warmth and competence judgments are predicted by perceived economic competition and status, respectively (for a review, see Cuddy, Fiske, & Glick, 2008). Building on this evidence, the present work intends to further explore the role of warmth and competence in social judgment, adopting a finer-grained level of analysis. Specifically, we consider warmth to be a dimension of evaluation that encompasses two distinct characteristics (i.e., sociability and morality) rather than as an undifferentiated dimension (see Leach, Ellemers, & Barreto, 2007). In a similar vein, both economic competition and symbolic competition are taken into account (see Stephan, Ybarra, & Morrison, 2009). In order to highlight the relevance of our empirical research, the first chapter reviews the literature in social psychology that has studied the warmth and competence dimensions. In the second chapter, across two studies, we examine the role of realistic and symbolic threats (akin economic and symbolic competition, respectively) in predicting the perception of sociability and morality of social groups. In study 1, we measure perceived realistic threat, symbolic threat, sociability, and morality with respect to 8 social groups. In study 2, we manipulate the level and type of threat of a fictitious group and measure perceived sociability and morality. The findings show that realistic threat and symbolic threat are differentially related to the sociability and morality components of warmth. Specifically, whereas realistic threat seems to be a stronger predictor of sociability than symbolic threat, symbolic threat emerges as better predictor of morality than realistic threat. Thus, extending prior research, we show that the types of threat are linked to different warmth stereotypes. In the third and the fourth chapter, we examine whether the sociability and morality components of warmth play distinct roles at different stages of group impression formation. More specifically, the third chapter focuses on the information-gathering process. Two studies experimentally investigate which traits are mostly selected when forming impressions about either ingroup or outgroup members. The results clearly show that perceivers are more interested in obtaining information about morality than about sociability when asked to form a global impression about others. The fourth chapter considers more properly the formulation of an evaluative impression. Thus, in the first study participants rate real groups on sociability, morality, and competence. In the second study, participants read an immigration scenario depicting an unfamiliar social group in terms of high (vs. low) morality, sociability, and competence. In both studies, participants are also asked to report their global impression of the group. The results show that global evaluations are better predicted by morality than by sociability and competence trait ascriptions. Taken together the third and the fourth chapters show that the dominance of warmth suggested by previous studies on impression formation might be better explained in terms of a greater effect of one of the two subcomponents (i.e., morality) over the other (i.e., sociability). In the general discussion, we discuss the relevance of our findings for intergroup relation and group perception, as well as for impression formation.

Physical models for numerical simulation of Si-based nanoscale FETs and sensors

To continuously improve the performance of metal-oxide-semiconductor field-effect-transistors (MOSFETs), innovative device architectures, gate stack engineering and mobility enhancement techniques are under investigation. In this framework, new physics-based models for Technology Computer-Aided-Design (TCAD) simulation tools are needed to accurately predict the performance of upcoming nanoscale devices and to provide guidelines for their optimization. In this thesis, advanced physically-based mobility models for ultrathin body (UTB) devices with either planar or vertical architectures such as single-gate silicon-on-insulator (SOI) field-effect transistors (FETs), double-gate FETs, FinFETs and silicon nanowire FETs, integrating strain technology and high-κ gate stacks are presented. The effective mobility of the two-dimensional electron/hole gas in a UTB FETs channel is calculated taking into account its tensorial nature and the quantization effects. All the scattering events relevant for thin silicon films and for high-κ dielectrics and metal gates have been addressed and modeled for UTB FETs on differently oriented substrates. The effects of mechanical stress on (100) and (110) silicon band structures have been modeled for a generic stress configuration. Performance will also derive from heterogeneity, coming from the increasing diversity of functions integrated on complementary metal-oxide-semiconductor (CMOS) platforms. For example, new architectural concepts are of interest not only to extend the FET scaling process, but also to develop innovative sensor applications. Benefiting from properties like large surface-to-volume ratio and extreme sensitivity to surface modifications, silicon-nanowire-based sensors are gaining special attention in research. In this thesis, a comprehensive analysis of the physical effects playing a role in the detection of gas molecules is carried out by TCAD simulations combined with interface characterization techniques. The complex interaction of charge transport in silicon nanowires of different dimensions with interface trap states and remote charges is addressed to correctly reproduce experimental results of recently fabricated gas nanosensors.