A Graph-theoretic perspective on centrality

The concept of centrality is often invoked in social network analysis, and diverse indices have been proposed to measure it. This paper develops a unified framework for the measurement of centrality. All measures of centrality assess a node's involvement in the walk structure of a network. Measures vary along four key dimensions: type of nodal involvement assessed, type of walk considered, property of walk assessed, and choice of summary measure. If we cross-classify measures by type of nodal involvement (radial versus medial) and property of walk assessed (volume versus length), we obtain a four-fold polychotomization with one cell empty which mirrors Freeman's 1979 categorization. At a more substantive level, measures of centrality summarize a node's involvement in or contribution to the cohesiveness of the network. Radial measures in particular are reductions of pair-wise proximities/cohesion to attributes of nodes or actors. The usefulness and interpretability of radial measures depend on the fit of the cohesion matrix to the one-dimensional model. In network terms, a network that is fit by a one-dimensional model has a core-periphery structure in which all nodes revolve more or less closely around a single core. This in turn implies that the network does not contain distinct cohesive subgroups. Thus, centrality is shown to be intimately connected with the cohesive subgroup structure of a network.     

On summary measures of binarized dominance data

Data on outcomes of dominance contests in groups of animals are often binarized (the original matrix of counts transformed into a matrix of ones and zeros indicating, for each pair, which animal won more contests). Various measures attempt to summarize the structure of the binarized data. We discuss uncertainty in such summary measures, and suggest ways to account for this uncertainty. We consider the summary measure both for an observed finite sample and for the unobserved underlying probability structure. We illustrate the general ideas with one particular summary measure, Appleby's K, and one data set, Appleby's red deer data.     

Children's subjective well-being in Africa: A comparative analysis across three countries

Recent trends in child well-being research have shown a substantial advancement in studies investigating children's subjective well-being (SWB). This advancement has raised questions concerning the measurement of SWB and the extent to which various measures can be compared across countries and diverse cultures. With a dearth of empirical data on cross-cultural comparisons, the validation of existing measures and cross-cultural comparisons and adaptations, have been identified as a critical course of action. The current study contributes to this process – it aims to report on children's SWB in three African countries (Algeria, Ethiopia, and South Africa), using two multiple item measures of SWB (the context-free Students' Life Satisfaction Scale and the domain-specific Personal Well-Being Index-School Children). Within this process the study further aims to test the structural validity of these measures and to ascertain its cross-country comparability. Data from the second wave of the Children's Worlds survey were used; and includes a randomly selected sample of 3394 children between the ages of 11–12 from Algeria (Provinces of El Bayedh, Oran, and Tlemcen), Ethiopia and South Africa (Western Cape Province). Located within the goodness of fit theoretical framework, confirmatory factor analysis and Structural Equation Modelling were used to test the overall fit structure, while multi-group confirmatory factor analysis was used to test measurement invariance. The results show appropriate fit structure for the individual models, with metric and scalar factor invariance tenable across the three countries for the Students' Life Satisfaction Scale and partial scalar invariance obtained for four items on the Personal Well-Being Index-School Children. The Algerian sample scored significantly higher than Ethiopia and South Africa on both SWB measures. Appropriate fit structure was obtained for the combined model and for the structural model, indicating adequate convergent validity with the single item Overall Life Satisfaction. Metric and partial scalar invariance was tenable for the structural model, suggesting cross-country comparability for correlations, regressions and means. The overall findings suggest that the two measures are appropriate for use with children from the three countries and that meaningful comparisons can be made between the three countries.     

Prevention validation and accounting platform: a framework for establishing accountability and performance measures of substance abuse prevention programs

The field of substance abuse prevention has neither an overarching conceptual framework nor a set of shared terminologies for establishing the accountability and performance outcome measures of substance abuse prevention services rendered. Hence, there is a wide gap between what we currently have as data on one hand and information that are required to meet the performance goals and accountability measures set by the Government Performance and Results Act of 1993 on the other. The task before us is: How can we establish the accountability and performance measures of substance abuse prevention programs and transform the field of prevention into prevention science? The intent of this volume is to serve that purpose and accelerate the processes of this transformation by identifying the requisite components of the transformation (i.e., theory, methodology, convention on terms, and data) and by introducing an open forum called, Prevention Validation and Accounting (PREVA) Platform. The entire PREVA Platform (for short, the Platform) is designed as an analytic framework, which is formulated by a collectivity of common concepts, terminologies, accounting units, protocols for counting the units, data elements, and operationalizations of various constructs, and other summary measures intended to bring about an efficient and effective measurement of process input, program capacity, process output, performance outcome, and societal impact of substance abuse prevention programs. The measurement units and summary data elements are designed to be measured across time and across jurisdictions, i.e., from local to regional to state to national levels. In the Platform, the process input is captured by two dimensions of time and capital. Time is conceptualized in terms of service delivery time and time spent for research and development. Capital is measured by the monies expended for the delivery of program activities during a fiscal or reporting period. Program capacity is captured by fourteen measurement units, tapping into the dimensions of staff resources and community assets. Staff resources are, in turn, operationalized in terms of staff size, staff certification status, staff turnover rate, and the accreditation status of a provider agency. Community assets are operationalized by the number of community centers accessible to the funded agency, number of formalized teams or antidrug coalitions active in the catchment area, and other social/human services providers with whom the prevention agency has formalized networks. The totality of process output from all sources of program activities is reduced to eighteen classes of measures. These are operationalized by thirty-three summary measures. Some of these include: total count of events facilitated; total number of clients served; average number of clients served per event; clients served by single and multiple program sessions; classification of target population in terms of the severity of risk as defined by the Institute of Medicine; age groups and race/ethnicity of clients served; number of program participants retained by recurring programs; number of clients who have completed the program; penetration rates to the target population; client attrition rates; average referral rates per provider per time interval; referral success rates; and so on. All process output measures specified in the Platform are derived from two broad classes of events classified as either products or services. The collectivity of these measures is expected to present a cost-effective, parsimonious, yet comprehensive picture of the entire spectrum of the process output, i.e., "what came out of the program as program activities". For the measurement of performance outcomes, two types of data are incorporated into the Platform: outcome data from individuals and the behavior (or performance) of social indicators from aggregated data bases. Individual data are used to evaluate the outcome of substance abuse programs     

Intergenerational mobility and racial inequality: The case for a more holistic approach

Intergenerational social mobility studies have largely explored the relationship between one aspect of parent background (e.g., education, income, occupational status, wealth, or neighborhood context) and the corresponding aspect of that parent's child once they reach adulthood. Studies examining these various measures have provided differing conclusions about the extent that social origins constrain attainment in the U.S. In contrast, the persistence of racial inequality in intergenerational mobility is one consistent finding. For instance, across various measures, research demonstrates Black individuals are more likely than White individuals to experience downward mobility, and less likely to exceed the socioeconomic standings of their parents. In this article, we argue that a more holistic measure of both origin and destination, one that combines the above-mentioned indicators, is necessary to advance our understanding of the extent that origin constrains future attainment. We summarize lessons gleaned from one-dimensional estimates, and from other approaches that either combine some dimensions of socioeconomic background or attempt to capture a more holistic background in other ways. We then make a recommendation for methodological interventions to accomplish this more holistic approach and conclude with research and policy implications.     

Gender inequality in the one percent: A look under the hood of high incomes in Germany

Gender differences in economic outcomes are important topics in social science research. However, the study of gender differences among economic elites—“the top one percent”—has received surprisingly little attention, likely also due to a lack of empirical data. This paper investigates gender differences in individual and household income among the top one percent of individual monthly net incomes and top two percent of net household incomes using data from the German Microcensus from 2006 to 2016 covering more than 3.3 million individuals. I find that women account for only around 14% of the one percent in individual incomes. Additionally, regarding the household level, women's incomes are sufficient to achieve two percent status in fewer than 10% of all households. Both numbers did hardly change over the decade from 2006 to 2016. Furthermore, women's pathways to belonging to a high-income household are far more dependent on their partner's education and employment status than men's. Overall, the findings thus show dramatic gender differences among the German economic elite that do not narrow over time.     

Sources of health insurance and characteristics of the uninsured: analysis of the March 1999 Current Population Survey

This Issue Brief provides summary data on the insured and uninsured populations in the nation and in each state. It discusses the characteristics most closely related to an individual's health insurance status. Based on EBRI estimates from the March 1999 Current Population Survey (CPS), it represents 1998 data--the most recent data available. In 1998, 194.7 million nonelderly Americans--81.6 percent--had some form of health insurance. More than 64 percent had it through an employment-based health plan; 6.5 percent purchased it on their own; and 14.3 percent were covered by a public program, mostly through Medicaid (10.4 percent). In 1998, 18.4 percent of the nonelderly population was uninsured (43.9 million people), compared with 14.8 percent in 1987. The percentage of uninsured Americans has generally been increasing since at least 1987, although the percentage uninsured in 1998 was not statistically different from the percentage uninsured in 1997 (18.3 percent). The increase in the uninsured prior to 1993 can be attributed to the erosion of employment-based health insurance. However, since 1993, the percentage of nonelderly Americans covered by an employment-based health plan has increased from 63.5 percent to 64.9 percent. The decline in public sources of health insurance would mostly explain the recent increase in the uninsured. For example, between 1994 and 1998 the percentage of nonelderly Americans covered by CHAMPUS/CHAMPVA declined from 3.8 percent to 2.9 percent, in large part due to downsizing in the military. Similarly, between 1993 and 1998, the percentage of nonelderly Americans covered by Medicaid declined from 12.7 percent to 10.4 percent as people left welfare. The increase in employment-based coverage since 1994 was due mainly to a higher likelihood that children were covered by an employment-based health plan. Between 1994 and 1998, the percentage of children covered by an employment-based health plan increased from 58.1 percent to 60.2 percent. For adults, it increased less than one percentage point, from 66.1 percent to 66.9 percent. Adults started to realize gains in employment-based health insurance between 1997 and 1998. Between 1994 and 1997, the percentage of working adults with employment-based health insurance coverage held steady at roughly 72.3 percent. During this period, health care cost inflation was essentially nonexistent. However, between 1997 and 1998, the percentage of working adults with employment-based health insurance increased from 72.2 percent to 72.8 percent, despite the apparent return of health care cost inflation in 1998. It is likely that the changing composition of the labor force accounted for some of the increase in employment-based coverage.     

Well‐being among adolescent boys

Most studies on mental health in the adult population have found a significant relationship between mental health and social class. No study has thoroughly examined this relationship in the adolescent population. This article, based on the Bachman, O'Malley, and Johnston “Youth in Transition” data set, tests the social class/mental state relationship among adolescents. Three separate measures—well‐being, psychiatric symptoms, and depression—are used to indicate mental state. Social class is based on a composite measure of socioeconomic level that exists within the “Youth in Transition” data set. Surprisingly, no relationship was found. These results persisted even when more traditional measures of social class based on parents’ education and the Duncan ranking of the fathers’ occupations were substituted for socioeconomic level. An alternative explanation supporting social stress is discussed in light of Thornberry's developmental hypothesis.     

THE EFFECTS OF EDUCATION ON FERTILITY: EVIDENCE FROM TAIWAN

This study investigates the impact of women's education on fertility. For identification, we use the 1968 compulsory education law change in Taiwan, which generated a regression discontinuity design (RDD) setting. We use the whole population of women from the 1980 and 2010 Population Censuses. Results of our RDD estimation using the exact date of birth suggest that the law change was effective in boosting women's education, but it did not have any impact on fertility. This is in stark contrast to most previous studies using only the birth year as the running variable or using it to construct instruments, which find that women's education depresses fertility. This study demonstrates that using a discrete running variable in RDD may generate a false discontinuity for an otherwise continuous regression function. (JEL J13, C21, I2)     

Assessing the Effects of the Physical,Psychological, and Social Dimensions of Health on the Use of Health Services*

In this paper we examine two major assumptions inherent in the literature relating health status to the use of health services: (1) that each of the three dimensions of health (i.e., the physical, the psychological, and the social) has an equal impact on the use of health services; and (2) that the effects of these three dimensions of health are manifest in an additive rather than in an interactive fashion. To test these assumptions, multiple regression analyses are performed using a modified version of the generic model of access to medical care in order to predict eight different types of health services utilization. The results compel us to accept the additivity assumption, while rejecting the equality assumption. Moreover, contrary to Mechanic's assertion, psychological health was found to have the least impact of any of the three dimensions of health on the use of health services. We then discuss two possible explanations (i.e., differences in the populations studied and the measurement of the independent variables) that might account for the disparity between Mechanic's and our own findings. Although further study is needed before any firm conclusions may be drawn, the evidence suggests that Mechanic's findings may be specific to the HMO populations that he sampled.     

Rural homelessness: its effect on healthcare access,healthcare outcomes,mobility, and perspectives of novel technologies

Rural homelessness is an undeniable public health issue that is understudied in the research literature. The purpose of this study was to determine the sociodemographics, physical and mental health status, barriers to access to care, and perspectives on potential technological advances of homeless individuals. A structured 45–90?min interview was utilized to gather demographic, physical health, mental health, mobility, and technology use data from a sample of 75 homeless individuals within three shelters in three micropolitan Nebraska cities. Individuals in this region were more likely to be white, unmarried, and mobile who have various physical and mental health disorders. Adherence to treatment of mental health disorders ranged from 43–60 percent. This population had increased employment, access to healthcare services, and use of technology than predicted. Leaders from all over the country can use these data to help improve state and local efforts to better cater to this vulnerable population's needs.     

Reference distributions and inequality measurement

We investigate a general problem of comparing pairs of distributions which includes approaches to inequality measurement, the evaluation of “unfair” income inequality, evaluation of inequality relative to norm incomes, and goodness of fit. We show how to represent the generic problem simply using (1) a class of divergence measures derived from a parsimonious set of axioms and (2) alternative types of “reference distributions.” The problems of appropriate statistical implementation are discussed and empirical illustrations of the technique are provided using a variety of reference distributions.     

Young people's time use and maternal employment in the UK1

This paper analyses the relationship between young people's time use and maternal employment in the United Kingdom (UK). Two dimensions of young people's time use are important for understanding the impact of maternal employment. The first of these is family context. This concerns the time young people are near their parents or not. The second relates to young people's activity patterns. Combining information from both dimensions is necessary to provide a comprehensive overview of the impact of maternal employment on young people's time use. The paper demonstrates that young people's time use is associated with maternal employment both in terms of activity patterns and family context. Young people with employed mothers spend more time alone with a father, and more time with neither parent. More specifically, young people with mothers employed fulltime (FT) spend significantly more time watching TV than those whose mothers are not employed, especially when they are not near any parents. There is a negative association between FT maternal employment and the time young people spend in achievement‐related activities, concentrated in time when alone with a mother. Unlike time in leisure activities or time watching TV, time in achievement‐related activities when in the presence of a father does not increase to compensate for the loss in time spent in achievement‐related activities when alone with a mother.     

Implications of ERISA for health benefits and the number of self-funded ERISA plans

This Issue Brief provides an overview of the issues relating to the Employee Retirement Income Security Act of 1974 (ERISA) and health benefit plans, the major case law relating to ERISA and health plans, and the implications of the preemption of state regulations for health plan sponsors and participants. It also presents the latest data on the number of health plan participants in self-funded ERISA plans. Finally, it presents a summary of current legislative proposals that would attempt to amend ERISA. Under the framework ERISA established for employee benefit plans, the regulation of employment-based health benefit plans has evolved into a two-tiered system in which both federal and state laws play important roles. The Supreme Court has interpreted ERISA's "savings" and "deemer" clauses to mean that insured plans are subject to regulations directly at the federal level and indirectly at the state level, while self-funded plans are regulated exclusively at the federal level. The ERISA statute and the courts' interpretations of the Act have created a sharp controversy over how employee health benefit plans are provided and administered, with state regulators and consumer advocates on one side of the debate and plan sponsors (e.g., employers and unions) on the other. State regulators and consumer advocates tend to favor more regulation, and in many instances greater regulation at the state level, which they argue would provide more protections for consumers. However, employers and unions (or any plan sponsors) think ERISA preemption is very important to their ability to provide innovative and cost-effective health benefits for their employees, and assert that ERISA's present structure should be preserved. The U.S. General Accounting Office (GAO) found that 44 million individuals (39 percent of those in ERISA plans) were enrolled in self-funded ERISA plans in 1993, up from 39 million (33 percent of those in ERISA plans) in 1989. The Employee Benefit Research Institute (EBRI), using the same methodology as GAO with 1995 data, estimated that 48 million individuals (39 percent of those in ERISA plans) were enrolled in self-funded ERISA plans in 1995. When policymakers look to amend ERISA, they should consider whether the change to ERISA will produce a higher level of quality for consumers than is being provided under the present system and will continue to do so in the future. Policymakers must also decide whether quality of care is better enhanced by health plans' greater exposure to liability or by market forces. If policymakers decide that increased exposure to liability is the route to go, will consumers be able to enjoy any potential improvement in quality or will more individuals end up uninsured because of increased costs and not be able to get any care regardless of the quality?     

Sources of health insurance and characteristics of the uninsured: analysis of the March 1997 Current Population Survey

This Issue Brief provides summary data on the insured and uninsured populations in the nation and in each state. It discusses the characteristics most closely related to individuals' health insurance status. Based on EBRI analysis of the March 1997 Current Population Survey, it represents 1996 data--the most recent data available. In 1996, 82.3 percent of nonelderly (under age 65) Americans had private or public health insurance. Seventy-one percent had private insurance, 64 percent through an employment-based plan. Sixteen percent had public health insurance. The percentage of uninsured Americans has been increasing since at least 1987. In 1987, 14.8 percent of the nonelderly population was uninsured, compared with 17.7 percent in 1996. However, the erosion of employment-based health benefits cannot fully explain this increase since 1993. Instead, the decline in public sources of health insurance would partly explain it. It may be that, while the percentage of individuals with employment-based coverage is rising, individuals previously covered by Medicaid and CHAMPUS/CHAMPVA are not being fully absorbed into the employment-based health insurance market. Between 1995 and 1996, the percentage of nonelderly Americans without health insurance coverage increased from 17.4 percent to 17.7 percent. Further examination indicates that children completely accounted for this increase. In 1995, 13.8 percent of children and 19 percent of persons ages 18-64 were uninsured, compared with 14.8 percent of children and 18.9 percent of persons ages 18-64 in 1996. With the recent passage of legislation designed to reduce the number of uninsured children, the next focal point for health care reform could be early retirees and unemployed persons. President Clinton and some members of Congress have expressed an interest in improving access to and affordability of coverage for these groups. Currently, health care cost inflation is at its lowest point in years, but there are signals indicating that it is about to rise above current levels. The federal government's recent announcement that health insurance premiums will rise for federal employees an average of 8.5 percent in 1998 may portend higher future health care costs. Similarly, disappointing earnings announcements from several large insurers because of higher medical costs and lower-than-expected revenues may indicate that health insurance plans will increase premiums. Employment and income play a dominant role in determining an individual's likelihood of having health insurance. Age, gender, firm size, work hours, and industry are also important determinants; however, these variables are also closely linked to employment status and income. Some of the widest variations involve factors that are not always looked at in traditional demographic assessments, such as citizenship. However, variations by race, ethnicity, and citizenship are also closely linked to employment status and income.     

Fitting blockmodels to data

Whether the important conceptual advantages of blockmodelling can be practically utilized depends crucially upon the development of a satisfactory method for fitting blockmodes to data. Existing procedures suffer from several important limitations, principal among which is the lack of consensus on a measure of the goodness of fit of a blockmodel to the data it represents. In this paper I present a measure of goodness of fit, and an algorithm for finding blockmodels with maximal fit to data, that together render blockmodeling mathematically equivalent to regression analysis. To facilitate more detailed analyses, I also present measures of the degree to which individuals and their relations deviate from the overall pattern of the blockmodel of the sharpness with which each cluster is defined, and of the distances between clusters. The algorithm and measures are applied to data concerning international trade in the Western Hemisphere in two different decades.     

Unauthorized Status and Youth Development in the United States: Consensus Statement of the Society for Research on Adolescence

In the United States, 5.3 million children and adolescents are growing up either with unauthorized status or with at least one parent who has that status. Until recently, little in the way of research has informed federal, state, and local policy debates related to unauthorized status (e.g., border enforcement, deportation, and a pathway to citizenship) although these issues have important implications for youth development. This statement is a brief summary of the research evidence on multiple domains of development that may be affected by the child or parent's unauthorized status. We also describe the contextual and psychological mechanisms that may link this status to developmental outcomes. We summarize a range of policies and practices that could reduce the developmental harm to children, youth, and their families stemming from this status. Finally, we conclude with recommendations for policy, practice, and research that are based on the evidence reviewed.     

Sources of health insurance and characteristics of the uninsured: analysis of the March 1994 Current Population Survey

This Issue Brief provides summary data on the insured and uninsured populations in the nation and in each state and is based on EBRI analysis of the March 1994 supplement to the Current Population Survey (CPS). It discusses the way health protection has changed for the insured, how the states rank in health insurance protection, and the characteristics most closely related to whether or not an individual is likely to have health insurance protection. The March 1994 CPS represents 1993 data--the most recent data available. Forty-three percent of nonelderly respondents indicating they were noncitizens were uninsured in 1993, compared with 16.4 percent of citizens. Among all nonelderly uninsured, 15.1 percent were noncitizens. In six states a higher proportion of the total uninsured were noncitizens than in the nation as a whole. These states include California (37.8 percent), New York (26.6 percent), Florida (21.7 percent), New Jersey (20.8 percent), Illinois (19.9 percent), and Texas (17.8 percent). The CPS contained data regarding citizenship for the first time in its March 1994 survey and does not allow for the determination of legal status of noncitizens. Eighty-two percent of nonelderly Americans and 99 percent of elderly Americans (aged 65 and over)--or 215.7 million individuals--were covered by either public or private health insurance in 1993. In 1993, 18.1 percent of the nonelderly population--or 40.9 million people--were not covered by health insurance, up from 17.8 percent and 39.8 million in 1992. However, the margin of error in 1993 at the 95 percent confidence level is 0.4 percent and 765 thousand. Thus, the percentage of uninsured in 1993 ranged from 17.7 percent to 18.5 percent, and the number of uninsured ranged from 40.1 million to 41.7 million. Children accounted for the largest proportion of the increase in the number of uninsured between 1992 and 1993. Sixteen percent of all children--or 11.1 million children--were not covered by private health insurance and were either ineligible or did not receive publicly financed medical assistance in 1993, up from 15.1 percent and 10.2 million in 1992.     

A comprehensive health service evaluation and monitoring framework

ObjectiveTo develop a framework for evaluating and monitoring a primary health care service, integrating hospital and community services.MethodA targeted literature review of primary health service evaluation frameworks was performed to inform the development of the framework specifically for remote communities. Key principles underlying primary health care evaluation were determined and sentinel indicators developed to operationalise the evaluation framework. This framework was then validated with key stakeholders.ResultsThe framework includes Donabedian's three seminal domains of structure, process and outcomes to determine health service performance. These in turn are dependent on sustainability, quality of patient care and the determinants of health to provide a comprehensive health service evaluation framework. The principles underpinning primary health service evaluation were pertinent to health services in remote contexts. Sentinel indicators were developed to fit the demographic characteristics and health needs of the population. Consultation with key stakeholders confirmed that the evaluation framework was applicable.ConclusionData collected routinely by health services can be used to operationalise the proposed health service evaluation framework. Use of an evaluation framework which links policy and health service performance to health outcomes will assist health services to improve performance as part of a continuous quality improvement cycle.     

Resource-Based Crisis Management: The Important Role of the CEO's Reputation

This study provides empirical support for the positive power of a CEO's reputation as a strategic resource during and after a corporate crisis. Specifically, it demonstrates that a CEO's favorable reputation relieves many stakeholders' negative perceptions in a postcrisis situation. In addition, this study tests whether a particular type of CEO reputation will be more effective than another in dealing with different types of threats that a crisis poses to corporate reputation. This study introduces a resource-based approach to crisis that provides a wide, comprehensive set of strategies based on a variety of an organization's competitive resources.