A Multidimensional Dynamic Measure of Child Disadvantage: A Methodological Tool for Policymakers

This paper demonstrates the applicability of an innovative approach towards examining child disadvantage, using a holistic, dynamic measure that not only accounts for multiple sources of disadvantage but also for the recurrence and persistence of disadvantage throughout a child’s life. We analyse child disadvantage using two longitudinal surveys of the Australian child population, one of which is specific to Indigenous children, who experience notably higher rates of disadvantage. Among Australian children, we detect that poor body weight and bullying—representative of the broad dimensions of health and emotional wellbeing—should be of significant concern to policymakers. Among Indigenous children, housing conditions, schooling and exposure to risky behaviours stand out as areas of concern. By identifying the dimensions in which rates of child disadvantage are most severe, this methodological approach can help steer targeted policy actions.     

The Effect of Cultural Capital on High School Dropout: An Investigation in the Italian Provinces

This article studies at a detailed geographical level the relation between cultural capital and high school dropout. Bronfenbrenner’s systemic theory and Heckman’s perspective on cognitive/non-cognitive skills are considered as theoretical framework. We analyzed data from 103 Italian provinces employing Covariance Structure Analysis and spatial indices of autocorrelation. We found a consistent protective effect of cultural capital on dropout, independently of economic performance, in Central and Southern provinces, but not in Northern provinces. Spatial analyses showed very heterogeneous patterns of autocorrelation for dropout (especially across Southern provinces) even between neighboring areas, in spite of a more compact clustering when considering cultural and economic indicators. These results indicate that living in an environment with animated cultural life might enhance students’ non-cognitive skills, thus fostering their involvement in formative activities and the development of their human capital.     

A Measure of Trust: The Italian Regional Divide in a Latent Class Approach

Social differences within countries may partly explain the lack of economic convergence and the persistence of regional disparities. The case of Italy is emblematic: economic gap between North and South remains at high levels with large differences in social capital and in trust. In this paper, we use the micro data from the ISTAT “Aspects of Daily Life” Survey to build a measure of “trust in others” and a measure of “trust in institutions” through a latent class model to attribute a trust score to the Italian households and the Italian regions and, in this way, to add elements of knowledge useful to policies. Our measures confirm a persistent territorial divide although the regional mapping appears more complex than the classical North–South partition. At last, a discussion on the household typology shows that the territorial gaps of trust persist even among households with similar socio-economic characteristics.     

Data for the Sustainable Development Goals: Metrics for Evaluating Civil Registration and Vital Statistics Systems Data Relevance and Production Capacity,Illustrations with Nigeria

Three issues impinging on the potential use of Civil Registration and Vital Statistics (CRVS) data for the Sustainable Development Goals (SDGs) are analysed in the paper. These include CRVS data relevance, content and data production capacity of CRVS systems. The paper adopts a ‘data type’ approach to relevance and capacity and proposes two metrics based on a graded qualitative evaluation (GQE) methodology. One is a data-relevance metric for evaluating the relevance of CRVS data types to the SDGs. The second is a National Statistical Systems (NSS) data type production capacity metric used for evaluating the data production capacity of CRVS systems. CRVS data instrument analysis and the CRVS data production capacity are exemplified with the Nigerian CRVS system. Relevance assessment results suggest that CRVS systems can provide data relevant to 25% of the SDGs. However the SDG data contribution of CRVS depends on the ‘data type’ capacity of National CRVS systems. As the capacity assessment shows, the Nigerian CRVS system has ‘nominal’ capacity to produce all CRVS data types (fertility, mortality, migration, nuptiality and socio-economic) and ‘active’ and ‘latent’ capacities to provide data for some 21 SDG targets. However, it currently lacks ‘effective’ capacity to produce any of the data types for the SDGs. The paper has implications for goal setting and prioritization in evolving strategies to enhance the development of CRVS/NSS systems’ data capacities, especially in developing countries.     

Disasters,local organizations,and poverty in the USA, 1998 to 2015

Disaster research has drawn attention to how natural hazards transform local organizational dynamics and social inequalities. It has yet to examine how these processes unfold together over time. We begin to fill this gap with a county-level, longitudinal analysis that examines how property damages from natural hazards correlate not only with local shifts in poverty a year later but also counts of for-profit as well as bonding and bridging social capital organizations. Results show that poverty and all organizational types tend to increase with local hazard damages. They also show that poverty tends to increase most where the number of bonding social capital organizations is also increasing. This pattern suggests a Janus-faced dynamic in which bonding, or more inwardly focused, organizations that arise after disaster may end up inadvertently marginalizing those in more dire need.     

Fifty Years After the Social Indicators Movement: Has the Promise Been Fulfilled?

In spite of its currency both in academic research and political rhetoric, there are numerous attempts to define and conceptualize the social cohesion concept but there has been paid little attention to provide a rigorous and empirically tested definition. There are even fewer studies that address social cohesion in a framework of cross-cultural validation of the indicators testing the equivalence of the factorial structure across countries. Finally, as far as we know there is no study that attempt to provide an empirically tested multilevel definition of social cohesion specifying a Multilevel Structural Equation Model. This study aims to cover this gap. First, we provide a theoretical construct of social cohesion taking into account not only its multidimensionality but also its multilevel structure. In the second step, to test the validity of this theoretical construct, we perform a multilevel confirmatory factor analysis in order to verify if the conceptual structure suggested in first step holds. In addition, we test the cross-level structural equivalence and the measurement invariance of the model in order to verify if the same multilevel model of social cohesion holds across the 29 countries analysed. In the final step, we specify a second-order multilevel CFA model in order to identify the existence of a general factor that can be called “social cohesion” operating in society that accounts for the surface phenomena that we observe.     

Time in the Development of Indicators on Sustainable Wellbeing: A Local Experiment in Developing Alternative Indicators

This paper is a theoretical and methodological study on the topics of distribution of and competition between time spans dedicated to social activities in the development of sustainable well-being indicators. This article seeks to answer the following question: why and how should we take into account social time in the development of alternative indicators? To bring to light the complex relationship between well-being, sustainability and people’s relationship to time, this article draws on an experiment aimed at developing Regional Sustainable Well-being Indicators (Indicateurs de Bien-être Soutenable Territorialisés—IBEST), which took place in the Grenoble urban area. This experiment was based on two methodologies; the first one being a quantitative survey, and the second one being a series of qualitative interviews coupled with a participatory approach. One of the datasheet indicators developed following this methodological crossover is the activity times balancing indicator, which allows us to take into consideration the pressure affecting time spent on social activities (work, leisure, families and civic engagement).     

SNAP Benefits and Pregnancy-Related Emergency Room Visits

Pregnant women are likely to be sensitive to daily fluctuations in nutritional intake. To see if income constraints at the end of the month limit food consumption and trigger health problems, we examine how the date that benefits are issued for the Supplemental Nutrition Assistance Program (SNAP) changes the probability that a woman will go to the Emergency Room (ER) for pregnancy-related conditions using administrative data from SNAP and Medicaid from Missouri for 2010–2013. SNAP benefits in Missouri are distributed from the 1st through the 22nd day of the month based on the birth month and the first letter of the last name of the head of the household, making timing of SNAP issuance exogenous. We estimate probit models of the calendar month and SNAP benefit month on the probability of a pregnancy-related ER visit for women age 17–45, or the sample at risk of being pregnant. We also examine the relationship between SNAP benefit levels and ER visits. We found that women who received SNAP benefits in the second or third week of the calendar month were less likely to receive pregnancy-related care through the ER in the week following benefit receipt. Results suggest that SNAP benefits might be related to patterns of pregnancy-related medical care accessed through the ER. Since SNAP issuance date is within state control in the United States, states may want to consider the health effects of their choice.