Big data is being implemented with success in the private sector and science. Yet the public sector seems to be falling behind, despite the potential value of big data for government. Government organizations do recognize the opportunities of big data but seem uncertain about whether they are ready for the introduction of big data, and if they are adequately equipped to use big data. This paper addresses those uncertainties. It presents an assessment framework for evaluating public organizations' big data readiness. Doing so demystifies the concept of big data, as it is expressed in terms of specific and measureable organizational characteristics. The framework was tested by applying it to organizations in the Dutch public sector. The results suggest that organizations may be technically capable of using big data, but they will not significantly gain from these activities if the applications do not fit their organizations and main statutory tasks. The framework proved helpful in pointing out areas where public sector organizations could improve, providing guidance on how government can become more big data ready in the future.

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University administrators and mental health clinicians have raised concerns about depression and anxiety among Ph.D. students, yet no study has systematically synthesized the available evidence in this area. After searching the literature for studies reporting on depression, anxiety, and/or suicidal ideation among Ph.D. students, we included 32 articles. Among 16 studies reporting the prevalence of clinically significant symptoms of depression across 23,469 Ph.D. students, the pooled estimate of the proportion of students with depression was 0.24 (95% confidence interval [CI], 0.18–0.31; I2 = 98.75%). In a meta-analysis of the nine studies reporting the prevalence of clinically significant symptoms of anxiety across 15,626 students, the estimated proportion of students with anxiety was 0.17 (95% CI, 0.12–0.23; I2 = 98.05%). We conclude that depression and anxiety are highly prevalent among Ph.D. students. Data limitations precluded our ability to obtain a pooled estimate of suicidal ideation prevalence. Programs that systematically monitor and promote the mental health of Ph.D. students are urgently needed.

Proximity influences collaboration. This makes proximity a logical starting point for management and policy intervention in order to stimulate collaboration. In this paper, we analyze three types of proximity, namely organizational, technological and geographical proximity. The role of these proximities in stimulating collaboration is estimated with the help of a sample of European nanotechnology publications. While organizational proximity is significant it is the least important of the three kinds of proximity. Geographical proximity is most significant in statistical terms and technological proximity has the highest magnitude of effect. Consequently, the latter lends itself most for management and policy intervention. 1 Abstract:Collaborations are particularly important for the development and deployment of technology. We analyze the influence of organizational, technological and geographical proximity on European nanotechnology collaborations with the help of a publication dataset and additional geographical information. While organizational proximity influences collaboration only indirectly geographical and technological proximity do so directly. Geographical proximity is most significant in statistical terms and technological proximity has the highest magnitude of effect. Consequently, the latter lends itself most for management and policy interventions, e.g. providing information on technological specialization of potential partners or on project management tools. JEL Classification:O33, O14, R12

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Foster care caseloads have nearly doubled over the last three decades. Parental methamphetamine (meth) use grew significantly during the same period. While child welfare workers and law enforcement claim that parental meth use contributes to foster care growth, the evidence for a causal effect has not been determined. This paper presents the first evidence of a causal effect of meth on foster care admissions using two exogenous supply‐side interventions in meth markets from the late 1990s for identification. First, we find that restrictions on meth precursor distribution caused meth use (proxied by white meth self‐referred treatment cases) to decline 4.1%. Second, using two‐stage least squares, we estimate a positive elasticity of foster care cases with respect to meth use of 1.54. We also estimate elasticities of 1.03 and 1.49 for cases of child neglect and parental abuse, respectively. These results suggest that child welfare policies should be designed specifically for the children of meth‐using parents. (JEL I12, J13, K42)

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