Spouse “Together Time”: Quality Time Within the Household

During the last decade more and more time-use data were gathered on a household level in stead of on an individual level. The time-use information of all members of the household provides much more insight in research fields that until now largely used data gathered at the individual level. One of these research fields is the study of quality of life, based on the (quality) time partners within a household spend together which in turn is often linked to studying the associations between the amount of time spent together and relationship satisfaction. The amount of face-to-face spousal interaction is considered to be critically important for marital quality and is assumed to be violated within dual-earner couples, especially those with women working long hours. In this contribution we analyze the time-use of couples in the Belgian Time Use Surveys of 1999 and 2005. We identify which activities couples do together and which they do apart, and what household characteristics predict couples’ together time. Working times in general seem the most decisive factor influencing the amount of together time. The increased labor market participation of women, on the other hand, seems not to be so much a threat for the time a couple spends together.     

纳米技术与隐私:有关全景敞视监狱外的持续监视

我们认为,隐形标签、传感器和射频识别芯片等形式的纳米技术将在两个方面引发不同于过去几十年中传统意义上的隐私问题。一是它们将不再仅仅围绕监视集中和权力集中的理念,如全景敞视监狱的隐喻含义,而是要关注分散层面上的持续观察;二是对隐私的关注可能不仅仅涉及对信息流动的制约,同时也涉及到相关材料和纳米制品,如芯片及标签的设计。我们首先建构了一个框架用以概述当前有关隐私问题的辩论情况,进而提出我们的基本观点。     

The DYNAMO-HIA Model: An Efficient Implementation of a Risk Factor/Chronic Disease Markov Model for Use in Health Impact Assessment (HIA)

In Health Impact Assessment (HIA), or priority-setting for health policy, effects of risk factors (exposures) on health need to be modeled, such as with a Markov model, in which exposure influences mortality and disease incidence rates. Because many risk factors are related to a variety of chronic diseases, these Markov models potentially contain a large number of states (risk factor and disease combinations), providing a challenge both technically (keeping down execution time and memory use) and practically (estimating the model parameters and retaining transparency). To meet this challenge, we propose an approach that combines micro-simulation of the exposure information with macro-simulation of the diseases and survival. This approach allows users to simulate exposure in detail while avoiding the need for large simulated populations because of the relative rareness of chronic disease events. Further efficiency is gained by splitting the disease state space into smaller spaces, each of which contains a cluster of diseases that is independent of the other clusters. The challenge of feasible input data requirements is met by including parameter calculation routines, which use marginal population data to estimate the transitions between states. As an illustration, we present the recently developed model DYNAMO-HIA (DYNAMIC MODEL for Health Impact Assessment) that implements this approach.     

Learning to respect

In this article, "learning to respect" is considered both as a condition for the creation of a safe learning environment and as a condition for "learning to live together" in a democratic society. Learning to respect is not a subject like mathematics or history. As far as the school is concerned, pupils learn to respect through experiences with interactions within the classroom and the school. This paper explores some of the consequences for school policy and teachers' skills.