MODERNIZATION OF THE CHINESE FAMILY BUSINESS

In order to study the modernization of the Chinese family business, the contrast between formal rationality and substantive rationality was used to characterize significant features of Western culture and Chinese culture respectively. A theoretical model of Chinese social behaviors as influenced by the substantive ethics of Confucianism was adopted to describe the organizational behaviors which were frequently observed in Chinese family business. Several empirical studies comparing organizational climates as perceived by employees working in foreign-invested business, private business with formal regulations, and family business were cited to support the argument that such Confucian virtues as loyalty to the organization, working hard, maintaining interpersonal harmony, etc., are most likely to be manifested in organizations where formal regulations of Western-style management were enforced.     

Differences in Multidimensional Poverty According to Householders’ Gender and Age in South Korea

This study examines multidimensional poverty according to householders’ gender and age in South Korea. Using the counting approach, multidimensional poverty was measured on six dimensions: money, health, housing, employment, social protection, and social relations. The results indicate that the monetary dimension does not cover other deprived dimensions. In terms of poverty rate, female-headed households are more deprived on all six dimensions. The headcount ratio and adjusted headcount ratio gradually decrease as the cutoff value of multidimensional poverty increases. The decreasing tendency is more moderate for female-headed households than for male-headed households, indicating that female-headed households face more weighted poverty dimensions. Our study found that the poverty dimension demonstrates different patterns according to householders’ age. For the older group, health is the second most contributing factor, and for the younger group housing and social protection contributed more to multidimensional poverty than for the older group.

     

Role of the working alliance in the treatment of delinquent boys in community-based programs

Examined the role of the working alliance in the treatment of delinquent boys in community-based residential programs, clarifying the relation between therapeutic process and behavioral change. Horvath and Greenberg's (1989) Working Alliance Inventory was used to assess the therapeutic alliance between youth and staff after 3 weeks in treatment and again after 3 months. Achenbach's (1991) Child Behavior Checklist (CBCL; Youth Self-Report [YSR] and Teacher Report Form [TRF]) and recidivism scores were used to assess treatment progress and outcome. Results indicated that a positive working alliance assessed after 3 months in treatment related to positive psychological changes and predicted lower rates of recidivism. Unexpectedly, a positive working alliance assessed early in treatment was associated with negative outcomes (increased internalizing and externalizing symptoms and higher rates of recidivism). This finding suggests that for some delinquent youth initially optimistic assessments may be prognostic of slow progress or treatment failure.     

Body-esteem in Swedish 10-year-old children

This study examined body-esteem in 10-yr.-old children. The study group comprised 960 schoolchildren, 515 girls and 445 boys (M age= 10.4, SD=0.5). Analysis showed that girls who were overweight had more negative body-esteem on all dimensions (weight, appearance, and attribution). The overweight boys had more negative perceptions on only two dimensions (weight and appearance). Twice as many girls perceived themselves as too fat (20%) as too skinny (10%). Of the girls who perceived themselves as fat, only 31% were overweight; similarly only 33% of the boys who perceived themselves as fat were overweight. The children's perception of their weight seemed as important as their actual weight and was associated with their body-esteem in the same way. Although few children had dieted (7% of the girls and 5% of the boys), the ones who had dieted had more negative body-esteem than children who had not dieted.     

Assessing the distinguishability of models and the informativeness of data

A difficulty in the development and testing of psychological models is that they are typically evaluated solely on their ability to fit experimental data, with little consideration given to their ability to fit other possible data patterns. By examining how well model A fits data generated by model B, and vice versa (a technique that we call landscaping), much safer inferences can be made about the meaning of a model's fit to data. We demonstrate the landscaping technique using four models of retention and 77 historical data sets, and show how the method can be used to: (1) evaluate the distinguishability of models, (2) evaluate the informativeness of data in distinguishing between models, and (3) suggest new ways to distinguish between models. The generality of the method is demonstrated in two other research areas (information integration and categorization), and its relationship to the important notion of model complexity is discussed.     

Flexibility versus generalizability in model selection

Which quantitative method should be used to choose among competing mathematical models of cognition? Massaro, Cohen, Campbell, and Rodriguez (2001) favor root mean squared deviation (RMSD), choosing the model that provides the best fit to the data. Their simulation results appear to legitimize its use for comparing two models of information integration because it performed just as well as Bayesian model selection (BMS), which had previously been shown by Myung and Pitt (1997) to be a superior alternative selection method because it considers a model's complexity in addition to its fit. In the present study, after contrasting the theoretical approaches to model selection espoused by Massaro et al. and Myung and Pitt, we discuss the cause of the inconsistencies by expanding on the simulations of Massaro et al. Findings demonstrate that the results from model recovery simulations can be misleading if they are not interpreted relative to the data on which they were evaluated, and that BMS is a more robust selection method.     

Influence of Social Perception and Social Monitoring on Structural Priming

Although structural priming has been considered to be an independent cognitive process, recent evidence suggests that structural priming is modulated by sociocognitive factors such as social perception; speakers are more likely to mimic the sentence structure of a socially desirable interlocutor than the structure of a less desirable interlocutor. This study aims to further address the role of sociocognitive factors in language use by investigating how individual differences in social perception and tendency to align with others (i.e., social monitoring) modulate same‐verb structural priming. In particular, we investigate how likely students are to repeat a sentence structure of a teacher depending on their perception of the teacher and their social monitoring tendency. Our results demonstrate that students’ tendency to imitate a sentence structure of the teacher is positively influenced by their perception of the teacher but negatively by social monitoring. We suggest that the effects may be accounted for in terms of their influence on attention and memory encoding.     

Functional Extended Redundancy Analysis

We propose a functional version of extended redundancy analysis that examines directional relationships among several sets of multivariate variables. As in extended redundancy analysis, the proposed method posits that a weighed composite of each set of exogenous variables influences a set of endogenous variables. It further considers endogenous and/or exogenous variables functional, varying over time, space, or other continua. Computationally, the method reduces to minimizing a penalized least-squares criterion through the adoption of a basis function expansion approach to approximating functions. We develop an alternating regularized least-squares algorithm to minimize this criterion. We apply the proposed method to real datasets to illustrate the empirical feasibility of the proposed method.