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The past half-century has seen enormous changes in the demographic makeup of Latin America and the Caribbean (LAC). In the 1950s, LAC had a small population of about 160 million people, less than today's population of Brazil. Two-thirds of Latin Americans lived in rural areas. Families were large and women had one of the highest fertility rates in the world, low levels of education, and few opportunities for work outside the household. Investments in health and education reached only a small fraction of the children, many of whom died before reaching age five. Since then, the size of the LAC population has tripled and the mostly rural population has been transformed into a largely urban population. There have been steep reductions in child mortality, and investments in health and education have increased, today reaching a majority of children. Fertility has been more than halved and the opportunities for women in education and for work outside the household have improved significantly. Life expectancy has grown by 22 years. Less obvious to the casual observer, but of significance for policy makers, a population with a large fraction of dependent children has evolved into a population with fewer dependents and a very large proportion of working-age adults. This overview seeks to introduce the reader to three groups of issues related to population aging in LAC. First is a group of issues related to the support of the aging and poverty in the life cycle. Second is the question of the health transition. Third is an understanding of the fiscal pressures that are likely to accompany population aging and to disentangle the role of demography from the role of policy in that process.

Aim/Purpose: The purpose of this article is to present clear definitions of the population structures essential to research, to provide examples of how these structures are described within research, and to propose a basic structure that novice researchers may use to ensure a clearly and completely defined population of interest and sample from which they will collect data. Background: Novice researchers, especially doctoral students, experience challenges when describing and distinguishing between populations and samples. Clearly defining and describing research structural elements, to include populations and the sample, provides needed scaffolding to doctoral students. Methodology: The systematic review of 65 empirical research articles and research texts provided peer-reviewed support for presenting consistent population- and sample-related definitions and exemplars. Contribution: This article provides clear definitions of the population structures essential to research, with examples of how these structures, beginning with the unit of analysis, are described within research. With this defined, we examine the population subsets and what characterizes them. The proposed writing structure provides doctoral students a model for developing the relevant population and sample descriptions in their dissertations and other research. Findings: The article describes that although many definitions and uses are relatively consistent within the literature, there are epistemological differences between research designs that do not allow for a one-size-fits-all definition for all terms. We provide methods for defining populations and the sample, selecting a sample from the population, and the arguments for and against each of the methods. Recommendations for Practitioners: Social science research faculty seek structured ways in which to present key research elements to doctoral students and to provide a model by which they may write the dissertation. The article offers contemporary examples from the peer-reviewed literature to support these aims. Recommendation for Researchers: Novice researchers may wish to use the recommended framework within this article when developing the relevant section of the dissertation. Doing so provides an itemized checklist of writing descriptions, ensuring a more complete and comprehensive description of the study population and sample. Impact on Society: The scientific method provides a consistent methodological approach to researching and presenting research. By reemphasizing the definitions and applications of populations and samples in research, and by providing a writing structure that doctoral students may model in their own writing, the article supports doctoral students’ growth and development in using the scientific method. Future Research: Future researchers may wish to further advance novice researcher knowledge in developing models to guide dissertation writing. Future studies may focus on other essential areas of research, including studies about recruitment methods and attrition strategies, data collection procedures, and overall research alignment. Additionally, future researchers may wish to consider evaluating doctoral student foundational knowledge about populations and samples as part of the research process.

This article reports on the results of an intervention to promote the reintegration of Yezidi children and youth in the Kurdistan Region of Iraq, who had been in ISIS captivity or were displaced by ISIS, by increasing their cognitive complexity through experiential learning. The article explores the challenges faced by this demographic, including trauma and exclusion. It looks at the impact of a group-based curriculum designed to increase cognitive complexity (measured by integrative complexity), and discusses how the intervention addressed socio-cognitive needs in order to support reintegration. The intervention was piloted with young people associated with ISIS and those displaced by ISIS. Participants were thirty-three Yezidi males. Ages of participants ranged from 12-26 (Mean age = 17.77; SD = 3.69). Pre and posttest results show significant gain in IC in the overall sample (Cohen’s d = 1.76, 95% CI [-1.86, -2.35]). Both cohorts showed significant gain, with a slightly higher gain among the cohort of internally displaced persons. Participants gained important skills such as increased empathy and emotional regulation. Implications for additional uses of this approach are discussed.

This article uses the theory of Red Queen competition to predict patterns in the founding of nationally active interest groups in the USA. The theory of Red Queen competition holds that competition among groups in a population is history-dependent such that each organization’s competitiveness is a function of its historical experience. The theory predicts that: (1) a population relatively full of recently experienced incumbent organizations is extremely uninviting for newcomers; and (2) a population relatively devoid of recently experienced competitors (and thusly full of incumbents whose competitive experiences are either minimal or concentrated in the distant past) is relatively inviting for newcomers. We test these predictions against data from two group populations. Ultimately, we find strong support for the theory of Red Queen competition and its substantive predictions.

The extraction of natural resources in the mining regions causes environmental pollution, changes the landscape, and reduces biodiversity, and leads to conflicts between the local population and the mining enterprises. The paper aims to design a methodological tool for eliminating social tensions in the mining regions during field development and exploitation. The goal can be achieved by creating compensation projects that take into account the priorities assessed by the stakeholders: the population, the regional authorities and the mining enterprise. As the compensation projects strive to solve social and environmental problems in the mining regions, they include the direct financial compensation to the population, development of traditional enterprisers, reduction of environmental pollution, infrastructure development, etc. We focused on two logically connected tasks: 1) assessing the significance of compensation projects and funding by the regional budget and the mining enterprise; 2) determining the sequencing of the considered projects. For solving the first task, we proposed a method of the multi-criteria significance assessment of program projects from the perspective of the population, the regional authorities and the mining enterprise, based on a specific unified rating scale. This method uses a technique that cuts off options with low interest in the projects. Thus, it allows assessing the significance of the program projects, as well as calculating the shares of funding by the mining enterprise and the regional budget. For solving the second task, we applied the economic and mathematical model and the heuristic method, determining which projects should be implemented first. The experimental calculations showed that the developed compensation programs comply with the preferences of the stakeholders. The application of the developed approach can contribute to the balanced socio-economic development of the mining regions in conditions of intensive field development and exploitation.

Purpose The formation of an information society in Russia requires new approaches in the implementation of citizen’s rights to access information. At a modern time, when the resources of internet are available to almost everyone, the modern financial and legal institutions adapt or are obliged to adapt to the modern model of the information society. Not so long ago, just at the beginning of the twenty-first century, new information and legal concept – Civil budget – was introduced. The authors tried to show concrete examples of what it is, what it is, its structure and principles. The authors believe that the realization of the idea of a Civic budget in the Russian Federation will increase the accessibility of information for citizens about the financial performance and financial state and municipalities will allow the State itself, through its Government and the Parliament, to form the budget, based not only on macroeconomic goals and objectives of the country, and objectives of each, even the most small territorial unit in accordance with the needs of living of its citizens. Design/methodology/approach The problem is not new and, in one way or another, exists in all States, but many countries have undertaken very effective reforms and have made improvements in the situation. For example, in Brazil, in the city of Port Alegre, a budget initiative was launched in 1990. Then, it was “replicated” in 400 prefectures throughout the country. The procedure begins with the assembly of residents of the district, where citizens discuss and outline budget priorities, and ends with the approval of the city budget by delegates directly elected at district assemblies. The success achieved in Porto Alegre was further spread: in 1996-2000, budgeting options were implemented in 100 municipal districts, including São Paulo. In 2000-2004, it is estimated to be implemented in another 250 municipalities. Findings The access of the population to budget information is a positive factor not only from the point of view of budgetary law but also in the legal field of information law. Such an opportunity is a direct implementation of principles of the industry such as the principle of publicity and the principle of priority of individual rights. State bodies that form and execute the state budget are, initially, already subjects of the information law, but the above-mentioned activities for monitoring, collecting and providing information within the framework of the Civil budget concept lead them to a new qualitative level of rights and obligations within the framework of information relations, which is unquestionably a positive factor for the activities of these bodies. Originality/value The authors believe that the realization of the idea of a Civic budget in the Russian Federation will increase the accessibility of information for citizens about the financial performance and financial state, and municipalities will allow the State itself, through its Government and the Parliament, to form the budget, based not only on macroeconomic goals and objectives of the country, and objectives of each, even the most small territorial unit in accordance with the needs of living of its citizens.

The extraction of natural resources in the mining regions causes environmental pollution, changes the landscape, and reduces biodiversity, and leads to conflicts between the local population and the mining enterprises. The paper aims to design a methodological tool for eliminating social tensions in the mining regions during field development and exploitation. The goal can be achieved by creating compensation projects that take into account the priorities assessed by the stakeholders: the population, the regional authorities and the mining enterprise. As the compensation projects strive to solve social and environmental problems in the mining regions, they include the direct financial compensation to the population, development of traditional enterprisers, reduction of environmental pollution, infrastructure development, etc. We focused on two logically connected tasks: 1) assessing the significance of compensation projects and funding by the regional budget and the mining enterprise; 2) determining the sequencing of the considered projects. For solving the first task, we proposed a method of the multi-criteria significance assessment of program projects from the perspective of the population, the regional authorities and the mining enterprise, based on a specific unified rating scale. This method uses a technique that cuts off options with low interest in the projects. Thus, it allows assessing the significance of the program projects, as well as calculating the shares of funding by the mining enterprise and the regional budget. For solving the second task, we applied the economic and mathematical model and the heuristic method, determining which projects should be implemented first. The experimental calculations showed that the developed compensation programs comply with the preferences of the stakeholders. The application of the developed approach can contribute to the balanced socio-economic development of the mining regions in conditions of intensive field development and exploitation.

Environmental exposure assessment seeks to quantify exposure to potentially toxic environmental stressors, especially airborne pollutants. Health effects are typically estimated by regressing health outcome data on estimates of pollution exposure. Environmental exposure assessment is concerned with measuring or estimating exposure for the population of interest. The formulation of exposure assessment as a supervised learning regression problem naturally led to the use of machine learning models. A wide variety of machine learning models have been used, including generalized additive models, multivariate adaptive regression splines, kernel‐based regularized least squares, support vector regression, deletion/substitution/addition, cubist regression, cluster‐based bagging of mixed‐effect models, random forest, gradient boosting, neural networks, Bayesian regularized neural networks, generative adversarial networks. Model comparison, tuning, averaging, and feature selection all require reliable evaluation procedures. Cross‐validation and the bootstrap are two such procedures that are commonly used to evaluate exposure models.

The take-away message of this chapter is to build in, from the beginning of any new practice, the mechanisms for identity-protected data collection (with proper signed permissions from your patients) so you can track and explore all possible areas of practice evaluation and research interest. This can include basic demographic information on the populations you see, such as age, diagnosis, education, occupation, and referral sources. It also includes specific test data so you have the potential to explore a range of questions. For example, how does performance on the Buschke Selective Reminding Test compare to patients' performances on the California Verbal Learning Test-2? How do NPE profiles of patients with primary progressive multiple sclerosis differ from patients with relapsing-remitting MS at the same point in time from disease onset? The answers to such questions maximize our effective treatment of these patients.