Going the Extra Mile? How Street‐level Bureaucrats Deal with the Integration of Immigrants

Dutch immigration and integration policies are being interpreted and implemented by local street‐level bureaucrats. We carried out 28 semi‐structured interviews with integration coaches, integration teachers and client managers in order to understand the dilemmas they face, and to explain their subsequent behaviour. The results show that although organizational characteristics such as the bureaucratic burden made street‐level bureaucrats reluctant to enlarge their discretionary space at the expense of policy rules, their willingness to help clients often transcends these boundaries under a combination of three conditions: high client motivation, extreme personal distress of the client, and negative assessment of existing policies and policy instruments (both in terms of fairness and practicality). Furthermore, street‐level bureaucrats were found to be constantly reinterpreting and revising their roles.     

Effects of Regional Labour Markets on Migration Flows,by Education Level

European economies display large variations in unemployment rates across regions as well as between education groups. Insufficient labour mobility is widely believed to contribute to higher regional disparities and overall unemployment, but few studies have compared mobility responses of different education groups to regional shocks. This paper employs administrative registers covering the entire Norwegian population to compute annual time series from 1994 to 2004 of migration flows and regional labour market conditions by education level for 90 travel‐to‐work areas. We find that regional disparities in unemployment rates are decreasing in education level, whereas the response of migration flows to regional unemployment shocks is increasing in education level. The results suggest that low regional mobility of low‐educated workers may contribute to higher regional disparities and higher overall unemployment among the low educated.     

Modelling the evolution of a bipartite network—Peer referral in interlocking directorates

A central part of relational ties between social actors is constituted by shared affiliations and events. The action of joint participation reinforces personal ties between social actors as well as mutually shared values and norms that in turn perpetuate the patterns of social action that define groups. Therefore the study of bipartite networks is central to social science. Furthermore, the dynamics of these processes suggests that bipartite networks should not be considered static structures but rather be studied over time. In order to model the evolution of bipartite networks empirically we introduce a class of models and a Bayesian inference scheme that extends previous stochastic actor-oriented models for unimodal graphs. Contemporary research on interlocking directorates provides an area of research in which it seems reasonable to apply the model. Specifically, we address the question of how tie formation, i.e. director recruitment, contributes to the structural properties of the interlocking directorate network. For boards of directors on the Stockholm stock exchange we propose that a prolific mechanism in tie formation is that of peer referral. The results indicate that such a mechanism is present, generating multiple interlocks between boards.     

Differences in mortality by marital status in Finland from 1976 to 2000: analyses of changes in marital-status distributions, socio-demographic and household composition, and cause of death

Being currently not married is more common today than 25 years ago. Over this period relative differences in mortality by marital status have increased in several countries, mainly as a result of a sharp decline in mortality among the married. Using Finnish census data linked with death certificates, we show that these increases are not explained by the non-married population becoming more marginalized in socio-economic status or household composition. However, the increases in marital-status differences in mortality from accidental, violent, and alcohol-related causes of death in the 30-64 age group indicate that changes in the health-related behaviour of the non-married population may play a role. The public-health burden associated with not being married has also grown. At the end of the 1990s about 15 per cent of all deaths above the age of 30 would not have occurred if the non-married population had had the same age-specific mortality rates as the married population.     

Bayesian scale space analysis of temporal changes in satellite images

We consider the detection of land cover changes using pairs of Landsat ETM+ satellite images. The images consist of eight spectral bands and to simplify the multidimensional change detection task, the image pair is first transformed to a one-dimensional image. When the transformation is non-linear, the true change in the images may be masked by complex noise. For example, when changes in the Normalized Difference Vegetation Index is considered, the variance of noise may not be constant over the image and methods based on image thresholding can be ineffective. To facilitate detection of change in such situations, we propose an approach that uses Bayesian statistical modeling and simulation-based inference. In order to detect both large and small scale changes, our method uses a scale space approach that employs multi-level smoothing. We demonstrate the technique using artificial test images and two pairs of real Landsat ETM+satellite images.