黑夜意识和女性的(自我)毁灭--评现代中国的黑暗理论

文章对黑暗/夜的概念在中国语境中的演绎进行了调查:首先对黑暗(darkness)和黑夜(night)在中国传统文化中的使用加以评说,然后讨论其在现当代中国文学中的使用,最后着重讨论女作家翟永明(1955-)和她将女性精神理解为“黑夜意识”(nocturnalconsciousness)的观点。文章认为人们只有从夜里才能看到黑暗,从黑暗中才能见到光明。     

Means‐End Behavior in Young Infants: The Interplay of Action Perception and Action Production

In 2 experiments, the interplay of action perception and action production was investigated in 6‐month‐old infants. In Experiment 1, infants received 2 versions of a means‐end task in counterbalanced order. In the action perception version, a preferential looking paradigm in which infants were shown an actor performing means‐end behavior with an expected and an unexpected outcome was used. In the action production version, infants had to pull a cloth to receive a toy. In Experiment 2, infants' ability to perform the action production task with a cloth was compared to their ability to perform the action production task with a less flexible board. Finally, Experiment 3 was designed to control for alternative low‐level explanations of the differences in the looking times toward the final states presented in Experiment 1 by only presenting the final states of the action perception task without showing the initial action sequence. Results obtained in Experiment 1 showed that in the action perception task, infants discriminated between the expected and the unexpected outcome. This perceptual ability was independent of their actual competence in executing means‐ end behavior in the action production task. Experiment 2 showed no difference in 6‐month‐olds' performance in the action production task depending on the properties of the support under the toy. Similarly, in Experiment 3, no differences in looking times between the 2 final states were found. The findings are discussed in light of theories on the development of action perception and action production.     

Cross-National Measurement Invariance of the Teacher and Classmate Support Scale

The cross-national measurement invariance of the teacher and classmate support scale was assessed in a study of 23202 Grade 8 and 10 students from Austria, Canada, England, Lithuania, Norway, Poland, and Slovenia, participating in the Health Behaviour in School-aged Children (HBSC) 2001/2002 study. A multi-group means and covariance analysis supported configural and metric invariance across countries, but not full scalar equivalence. The composite reliability was adequate and highly consistent across countries. In all seven countries, teacher support showed stronger associations with school satisfaction than did classmate support, with the results being highly consistent across countries. The results indicate that the teacher and classmate support scale may be used in cross-cultural studies that focus on relationships between teacher and classmate support and other constructs. However, the lack of scalar equivalence indicates that direct comparison of the levels support across countries might not be warranted.     

Ascent-based Monte Carlo expectation– maximization

Summary.  The expectation–maximization (EM) algorithm is a popular tool for maximizing likelihood functions in the presence of missing data. Unfortunately, EM often requires the evaluation of analytically intractable and high dimensional integrals. The Monte Carlo EM (MCEM) algorithm is the natural extension of EM that employs Monte Carlo methods to estimate the relevant integrals. Typically, a very large Monte Carlo sample size is required to estimate these integrals within an acceptable tolerance when the algorithm is near convergence. Even if this sample size were known at the onset of implementation of MCEM, its use throughout all iterations is wasteful, especially when accurate starting values are not available. We propose a data-driven strategy for controlling Monte Carlo resources in MCEM. The algorithm proposed improves on similar existing methods by recovering EM's ascent (i.e. likelihood increasing) property with high probability, being more robust to the effect of user-defined inputs and handling classical Monte Carlo and Markov chain Monte Carlo methods within a common framework. Because of the first of these properties we refer to the algorithm as 'ascent-based MCEM'. We apply ascent-based MCEM to a variety of examples, including one where it is used to accelerate the convergence of deterministic EM dramatically.     

Entwicklung zur Handlungskompetenz durch Supervision in der Automobilindustrie

Development of competence by supervision in automotive industryAs a result of problems with the implementation of teamwork in the production processes a car manufacturing company decided to install training activities for the technical management. The author who participated in this training program, describes in which way a psychodrama oriented supervision was implemented as a specific learning process.