Distributive Justice Evaluations in Two Cultural Contexts: A Comparison of U.S. and South Korean Teachers

The justice literature suggests, but has nottested, a positive relationship between met expectationsabout multiple workplace rewards and distributivejustice evaluations (the individual's assessment of whether s/he has been treated fairly). Datafrom samples of teachers in South Korea (N = 649) andthe U.S. (N = 810) are used to examine thisrelationship. In addition, U.S.-South Korea culturalvalue differences in individualism, seniority, and hierarchicalauthority are the basis for hypothesizing that certainreward-specific met expectations will be linkeddifferently to justice evaluations across the twosocieties. As hypothesized for both societies, the moreone's expectations about job-related rewards are met,the greater the perception of just treatment. Also ashypothesized, several societal differences based on cultural differences are found. Metexpectations about autonomy are more important inexplaining justice evaluations in the U.S., whereas metexpectations about advancement opportunities are moreimportant in South Korea.     

灾害中残疾人的媒介使用与信息沟通需求——以汶川地震为例

在灾害情况下,残疾人群所面临的沟通困境要远远高于正常人群,甚至连最基本的信息需求都无法得到保障。从2008年汶川地震中残疾人群媒介使用的特征和信息沟通需求来看,对这部分弱势群体的保护需要在法律和政策上给予更多的支持:改善信息发布和传递的渠道,使用新的技术手段,培养残疾人使用媒介的良好习惯。     

浅谈“神似”理论在唐诗英译中的重要作用——以《送友人》的两个英译版本为例

诗歌是一种独特的艺术表现形式,拥有优美的形式和丰富的内容,唐诗也不例外。英译唐诗时,应以再现诗作精神内容风貌为主,即以达到“神似”为翻译第一目标,才能更好地保持唐诗的原貌。本文选择李白《送友人》的两个英译本,分析了“神似”理论在唐诗英译中的重要作用。     

中美大学社团现状与管理模式比较——以河北工程大学与北卡罗来纳州立大学为例

[摘 要]通过对比河北工程大学和北卡州立大学学生社团的发展现状和管理模式,包括学生社团数目、组成及社团的审批、管理、经费、活动、资源等各个方面,对高校学生社团的发展和管理提出了几点建议。     

Embedding latent class regression and latent class distal outcome models into cluster-weighted latent class analysis: a detailed simulation experiment

Usually in latent class (LC) analysis, external predictors are taken to be cluster conditional probability predictors (LC models with external predictors), and/or score conditional probability predictors (LC regression models). In such cases, their distribution is not of interest. Class-specific distribution is of interest in the distal outcome model, when the distribution of the external variables is assumed to depend on LC membership. In this paper, we consider a more general formulation, that embeds both the LC regression and the distal outcome models, as is typically done in cluster-weighted modelling. This allows us to investigate (1) whether the distribution of the external variables differs across classes, (2) whether there are significant direct effects of the external variables on the indicators, by modelling jointly the relationship between the external and the latent variables. We show the advantages of the proposed modelling approach through a set of artificial examples, an extensive simulation study and an empirical application about psychological contracts among employees and employers in Belgium and the Netherlands.     

Adjusted empirical likelihood models with estimating equations for accelerated life tests

This article proposes an adjusted empirical likelihood estimation (AMELE) method to model and analyze accelerated life testing data. This approach flexibly and rigorously incorporates distribution assumptions and regression structures by estimating equations within a semiparametric estimation framework. An efficient method is provided to compute the empirical likelihood estimates, and asymptotic properties are studied. Real-life examples and numerical studies demonstrate the advantage of the proposed methodology.     

Adaptive cluster sampling with a data driven stopping rule

The adaptive cluster sampling (ACS) is a suitable sampling design for rare and clustered populations. In environmental and ecological applications, biological populations are generally animals or plants with highly patchy spatial distribution. However, ACS would be a less efficient design when the study population is not rare with low aggregation since the final sample size could be easily out of control. In this paper, a new variant of ACS is proposed in order to improve the performance (in term of precision and cost) of ACS versus simple random sampling (SRS). The idea is to detect the optimal sample size by means of a data-driven stopping rule in order to determine when to stop the adaptive procedure. By introducing a stopping rule the theoretical basis of ACS are not respected and the behaviour of the ordinary estimators used in ACS is explored by using Monte Carlo simulations. Results show that the proposed variant of ACS allows to control the effective sample size and to prevent from excessive efficiency loss typical of ACS when the population is less clustered than anticipated. The proposed strategy may be recommended especially when no prior information about the population structure is available as it does not require a prior knowledge of the degree of rarity and clustering of the population of interest.     

Recall searching with and without recall

We revisit the sequential search problem by Hey (J Econ Behav Organ 8:137–144, 1987). In a 2 \(\times \) 2 factorial design, varying fixed and random cost treatments with and without recall, we address open research questions that were originally stated by Hey (1987). Our results provide clear evidence for Hey’s (1987) conjecture that recall negatively affects performance in sequential search. With experience, however, search behavior with and without recall converges toward the optimal reservation rule. We further find that the utilization of optimal reservation rules is independent from the stochastic nature of the search cost.