The Experts below are selected from a list of 141 Experts worldwide ranked by ideXlab platform
Monica Gaughan - One of the best experts on this subject based on the ideXlab platform.
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Ethnography, Demography and Service-Learning: Situating Lynwood Park
Critical Sociology, 2002Co-Authors: Monica GaughanAbstract:This paper reports the results of a one-year service-learning project that excited students about sociology, and created useful analytic tools for a modest-income African American community. In the course of deepening our understanding of one neighborhood — including collecting extant demographic data, conducting surveys and interviews, site visits, and simply “hanging out,” — it becomes possible to demonstrate how using Formal Demography and community ethnography together provide better understandings of the processes of social stratifi- cation, segregation, and gentrifi cation than would be possible using only one of the methodological orientations. The paper begins with an introduction to theoretical and didactic challenges, proceeds to describing Lynwood Park itself using insights derived from qualitative evidence, and then describes our eclectic means of investigating the community. The second half of the paper situates Lynwood Park demographically and ethnographically in terms of the larger Atlanta ...
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Ethnography, Demography and Service-Learning: Situating Lynwood Park
Critical Sociology, 2002Co-Authors: Monica GaughanAbstract:This paper reports the results of a one-year service-learning project that excited students about sociology, and created useful analytic tools for a modest-income African American community. In the course of deepening our understanding of one neighborhood — including collecting extant demographic data, conducting surveys and interviews, site visits, and simply “hanging out,” — it becomes possible to demonstrate how using Formal Demography and community ethnography together provide better understandings of the processes of social stratifi- cation, segregation, and gentrifi cation than would be possible using only one of the methodological orientations. The paper begins with an introduction to theoretical and didactic challenges, proceeds to describing Lynwood Park itself using insights derived from qualitative evidence, and then describes our eclectic means of investigating the community. The second half of the paper situates Lynwood Park demographically and ethnographically in terms of the larger Atlanta community, and then in increasingly smaller and more socially meaningful units. Once we focus the demographic lens as much as possible, we must again rely on qualitative information to probe the multiple meanings of Lynwood Park. The paper closes with recommendations about how the people of Lynwood Park can use the data, and suggests how these techniques can be implemented theoretically and practically in sociology as a whole.
Hal Caswell - One of the best experts on this subject based on the ideXlab platform.
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The Formal Demography of kinship III: Kinship dynamics with time-varying demographic rates
2021Co-Authors: Hal Caswell, Xi SongAbstract:AbstractBackgroundKinship models generally assume time-invariant demographic rates, and compute the kinship structures implied by those rates. It is important to compute the consequences of time variation in demographic rates for kinship stuctures.ObjectivesOur goal is to develop a matrix model for the dynamics of kinship networks subject to arbitrary temporal variation in survival, fertility, and population structure.MethodsWe develop a system of equations for the dynamics of the age structure of each type of kin of a Focal individual. The matrices describing survival and fertility vary with time. The initial conditions in the time-invariant model are replaced with a set of boundary conditions for initial time and initial age.ResultsThe time-varying model maintains the network structure of the time-invariant model. In addition to the results of the time-invariant model, it provides kinship structures by period, cohort, and age. It applies equally to historical sequences of past rates and to projections of future rates. As an illustration, we analyze the kinship structure of Sweden from 1891 to 2120.ContributionThe time-varying kinship model makes it possible to analyze the consequences of changing demographic rates, in the past or the future. It is easily computable, requires no simulations, and is readily extended to include additional, more distant relatives in the kinship network. The method can also be used to show the growth of families, lineages, and dynasties in populations across time and place and between social groups.
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The Formal Demography of kinship II: Multistate models, parity, and sibship
Demographic Research, 2020Co-Authors: Hal CaswellAbstract:Background: Recent kinship models focus on the age structures of kin as a function of the age of the focal individual. However, variables in addition to age have important impacts. Generalizing age-specific models to multistate models including other variables is an important and hitherto unsolved problem. Objective: The aim is to develop a multistate kinship model, classifying individuals jointly by age and other criteria (generically, “stages”). Methods: The vec-permutation method is used to create multistate projection matrices including age- and stage-dependent survival, fertility, and transitions. These matrices operate on block-structured population vectors that describe the age×stage structure of each kind of kin, at each age of a focal individual. Results: The new matrix formulation is directly comparable to, and greatly extends, the recent age-classified kinship model of Caswell (2019a). As an application, a model is derived including age and parity. It provides, for all types of kin, the joint age×parity structure, the marginal age and parity structures, and the (normalized) parity distributions, at every age of the focal individual. The age×parity distributions provide the distributions of sibship sizes of kin. As an example, the model is applied to Slovakia (1960–2014). The results show a dramatic shift in the parity distribution as the frequency of low-parity kin increased and that of high-parity kin decreased.
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The Formal Demography of kinship II: Multistate models, parity, and sibship
2020Co-Authors: Hal CaswellAbstract:Background: Recent kinship models focus on the age structures of kin as a function of the age of the focal individual. However, variables in addition to age have important impacts. Generalizing age-specific models to multistate models including other variables is an important and hitherto unsolved problem. Objectives: Our aim is to develop a multistate kinship model, classifying individuals jointly by age and other criteria (generically, 99stages99). Methods: We use the vec-permutation method to create multistate projection matrices including age- and stage-dependent survival, fertility, and transitions. These matrices operate on block-structured population vectors that describe the ageXstage structure of each kind of kin, at each age of a focal individual. Results: The new matrix formulation is directly comparable to, and greatly extends, the recent age-classified kinship model of Caswell (2019). As an application, we derive a model that includes age and parity. We obtain, for all types of kin, the joint ageXparity structure, the marginal age and parity structures, and the (normalized) parity distributions, at every age of the focal individual. We show how to use the ageXparity distributions to calculate the distributions of sibship sizes of kin. As an example, we apply the model to Slovakia (1960--2014). The results include a dramatic shift in the parity distribution as the frequency of low-parity kin increased and that of high-parity kin decreased. Contribution: The new model extends the Formal demographic analysis of kinship to ageXstage-classified models. In addition to parity, other stage classifications, including marital status, maternal age effects, and sex are now open to analysis.
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The Formal Demography of kinship: A matrix formulation
Demographic Research, 2019Co-Authors: Hal CaswellAbstract:Background: Any individual is surrounded by a network of kin that develops over her lifetime. In a justly famous paper, Goodman, Keyfitz, and Pullum (1974) presented Formal calculations of the mean numbers of (female, matrilineal) kin implied by a mortality and fertility schedule. Objective: The aim of this paper is a new theory of kinship Demography that provides age distributions as well as expected numbers, permits calculation of properties (e.g., dependency) of kin, is easily computable, and does not require simulation. Methods: The analysis relies on a novel application of the matrix formulation of cohort component population projection to describe the dynamics of a kinship network. The approach arises from the observation that the kin of a focal individual form a population, and can be modelled as one. Results: Kinship dynamics are described by a coupled system of non-autonomous matrix equations. I show how to calculate age distributions, total numbers, prevalence, dependency, and the experience of the death of relatives. As an example, I compare the kinship networks implied by the period vital rates of Japanese women in 1947 and 2014. Over this interval, fertility declined by 70% while life expectancy increased by 60%. The implications of these changes for kinship structure are profound; a lifetime dominated, under 1947 rates, by the experience of the death of kin has changed to one in which the death of kin is a rare event. On the other hand, the burden of dependent aged kin, including those suffering from dementia, is many-fold larger under 2014 rates. Conclusions: This new theory opens to investigation hitherto inaccessible aspects of kinship, with potential applications to many problems in family Demography.
Lucky M. Tedrow - One of the best experts on this subject based on the ideXlab platform.
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Exploring Stable Population Concepts from the Perspective of Cohort Change Ratios: Estimating the Time to Stability and Intrinsic r from Initial Information and Components of Change
Dynamic Demographic Analysis, 2016Co-Authors: David A. Swanson, Lucky M. Tedrow, Jack BakerAbstract:Cohort Change Ratios (CCRs) appear to have been overlooked in regard to a major canon of Formal Demography, stable population theory. CCRs are explored here as a tool for examining the transient dynamics of a population as it moves toward the stable equivalent that is captured in most Formal demographic models based on asymptotic population dynamics. We employ simulation and a regression-based approach to model trajectories toward this stability. This examination is done in conjunction with the Leslie Matrix and data for 62 countries selected from the US Census Bureau’s International Data Base. We use an Index of Stability (S), which defines stability as the point when S is equal zero (operationalized as S = 0.000000). The Index also is used to define initial stability for a given population and four subsequent “quasi-stable” points on the temporal path to stability (S = .01, S = .05, S = .001, and S = .0005). The regression-based analysis reveals that the initial conditions as defined by the initial Stability Index along with fertility and migration play a role in determining time to stability up until the quasi-stable point of S = .0005 is reached. After this point, the initial conditions are no longer a factor and mortality joins the fertility and migration components in determining the remaining time to stability. Overall all, we find that fertility and mortality have an inverse relationship with time to stability while migration has a positive relationship. The initial Stability Index has an inverse relationship with time to quasi-stability at S = .01, S = .005, S = .001, and S = .0005. We also find that a regression model works very well in estimating the intrinsic rate of increase from the initial rate of increase, but that this model can be improved by adding the components of change. We also compare time to stability and intrinsic r as estimated using the CCR Leslie Matrix approach to, respectively, estimates of time to stability and intrinsic r found using analytic methods and find that the former are consistent with the latter.
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Exploring Stable Population Concepts from the Perspective of Cohort Change Ratios
The Open Demography Journal, 2013Co-Authors: David A. Swanson, Lucky M. TedrowAbstract:Cohort Change Ratios (CCRs) have a long history of use in Demography. In spite of their history of use, they appear, however, to have been overlooked in regard to the major canon of Formal Demography, stable population theory. In this paper, CCRs are explored as a tool for examining the idea of a stable population. In comparing the approach using CCRs to the traditional analytical approach, benefits and drawbacks are noted. The paper also introduces an Index of Sta- bility, which is used in a regression model to estimate the number of years before the population in question becomes (ap- proximately) stable. The regression model works reasonably well and, as such, provides something not available in the traditional analytical approach, which is an estimate of the time to (approximate) stability for a given population.
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Exploring Stable Population Concepts from the Perspective of Cohort Change Ratios: Estimating Time to Stability and Intrinsic r
2004Co-Authors: David A. Swanson, Lucky M. TedrowAbstract:Cohort Change Ratios (CCRs) have a long history of use in Demography. In spite of their history of use, they appear, however, to have been overlooked in regard to a major canon of Formal Demography, stable population theory. In this paper, CCRs are explored as a tool for examining the idea of a stable population. In comparing the approach using CCRs to the traditional analytical approach, benefits and drawbacks are noted. The paper also introduces an Index of Stability, which is used in a regression model to estimate the number of years before the population in question becomes (approximately) stable. The regression model works reasonably well and, as such, provides something not available in the traditional analytical approach, which is an estimate of the time to (approximate) stability for a given population. Continuing the use of regression analysis, we also find that a regression model works reasonably well in estimating the intrinsic rate of increase from the initial rate of increase. We know that regression models are generally not as satisfying as analytical expressions in regard to describing relationships. It would be much more elegant to express the time to stability in terms of an analytic expression that incorporates the initial stability index (and probably other information about initial conditions) than it is to express the relationship in the form of a regression model. The same can be said about the relationship between the initial rate of increase in a given population and its intrinsic rate of increase. However, we also note that regression analysis has already been successfully employed in conjunction with stable population analysis, to include estimating intrinsic r from the proportional age distribution of a given population, mean generation length from a trial value of the intrinsic rate of increase, and the generation of model life table families and stable populations.
David A. Swanson - One of the best experts on this subject based on the ideXlab platform.
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Exploring Stable Population Concepts from the Perspective of Cohort Change Ratios: Estimating the Time to Stability and Intrinsic r from Initial Information and Components of Change
Dynamic Demographic Analysis, 2016Co-Authors: David A. Swanson, Lucky M. Tedrow, Jack BakerAbstract:Cohort Change Ratios (CCRs) appear to have been overlooked in regard to a major canon of Formal Demography, stable population theory. CCRs are explored here as a tool for examining the transient dynamics of a population as it moves toward the stable equivalent that is captured in most Formal demographic models based on asymptotic population dynamics. We employ simulation and a regression-based approach to model trajectories toward this stability. This examination is done in conjunction with the Leslie Matrix and data for 62 countries selected from the US Census Bureau’s International Data Base. We use an Index of Stability (S), which defines stability as the point when S is equal zero (operationalized as S = 0.000000). The Index also is used to define initial stability for a given population and four subsequent “quasi-stable” points on the temporal path to stability (S = .01, S = .05, S = .001, and S = .0005). The regression-based analysis reveals that the initial conditions as defined by the initial Stability Index along with fertility and migration play a role in determining time to stability up until the quasi-stable point of S = .0005 is reached. After this point, the initial conditions are no longer a factor and mortality joins the fertility and migration components in determining the remaining time to stability. Overall all, we find that fertility and mortality have an inverse relationship with time to stability while migration has a positive relationship. The initial Stability Index has an inverse relationship with time to quasi-stability at S = .01, S = .005, S = .001, and S = .0005. We also find that a regression model works very well in estimating the intrinsic rate of increase from the initial rate of increase, but that this model can be improved by adding the components of change. We also compare time to stability and intrinsic r as estimated using the CCR Leslie Matrix approach to, respectively, estimates of time to stability and intrinsic r found using analytic methods and find that the former are consistent with the latter.
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Exploring Stable Population Concepts from the Perspective of Cohort Change Ratios
The Open Demography Journal, 2013Co-Authors: David A. Swanson, Lucky M. TedrowAbstract:Cohort Change Ratios (CCRs) have a long history of use in Demography. In spite of their history of use, they appear, however, to have been overlooked in regard to the major canon of Formal Demography, stable population theory. In this paper, CCRs are explored as a tool for examining the idea of a stable population. In comparing the approach using CCRs to the traditional analytical approach, benefits and drawbacks are noted. The paper also introduces an Index of Sta- bility, which is used in a regression model to estimate the number of years before the population in question becomes (ap- proximately) stable. The regression model works reasonably well and, as such, provides something not available in the traditional analytical approach, which is an estimate of the time to (approximate) stability for a given population.
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Exploring Stable Population Concepts from the Perspective of Cohort Change Ratios: Estimating Time to Stability and Intrinsic r
2004Co-Authors: David A. Swanson, Lucky M. TedrowAbstract:Cohort Change Ratios (CCRs) have a long history of use in Demography. In spite of their history of use, they appear, however, to have been overlooked in regard to a major canon of Formal Demography, stable population theory. In this paper, CCRs are explored as a tool for examining the idea of a stable population. In comparing the approach using CCRs to the traditional analytical approach, benefits and drawbacks are noted. The paper also introduces an Index of Stability, which is used in a regression model to estimate the number of years before the population in question becomes (approximately) stable. The regression model works reasonably well and, as such, provides something not available in the traditional analytical approach, which is an estimate of the time to (approximate) stability for a given population. Continuing the use of regression analysis, we also find that a regression model works reasonably well in estimating the intrinsic rate of increase from the initial rate of increase. We know that regression models are generally not as satisfying as analytical expressions in regard to describing relationships. It would be much more elegant to express the time to stability in terms of an analytic expression that incorporates the initial stability index (and probably other information about initial conditions) than it is to express the relationship in the form of a regression model. The same can be said about the relationship between the initial rate of increase in a given population and its intrinsic rate of increase. However, we also note that regression analysis has already been successfully employed in conjunction with stable population analysis, to include estimating intrinsic r from the proportional age distribution of a given population, mean generation length from a trial value of the intrinsic rate of increase, and the generation of model life table families and stable populations.
Dirk J. Van De Kaa - One of the best experts on this subject based on the ideXlab platform.
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Emerging Issues in Demographic Research for Contemporary Europe
Population studies, 1991Co-Authors: Dirk J. Van De KaaAbstract:For those who love semantics the title of this chapter really is a godsend. When is an issue an 'emerging' issue? When is it an issue in demographic research? For whom? What is demographic research? What is (contemporary) Europe? The list of questions that can be asked about the meaning of the phrase appears endless. Moreover, not all of those questions are largely irrelevant. Three points in particular deserve some attention. Emerging issues can be identified from two quite different perspectives and the results are not necessarily the same. The first perspective may be called the scientific perspective. The demographer or social scientist involved then acts solely as an observer or an investigator who seeks to understand what is observed and to increase knowledge for its own sake. The approach of such demographers may be completely theoretical. They are not interested in influencing the processes they see unfolding, nor in the utility of their findings for those people who concern themselves with the formulation and design of policies, or for the population at large. It is a discipline oriented perspective. The second perspective may be referred to as the applied or policy perspective. These researchers are concerned with obtaining results that have some practical significance. They focus on issues identified as 'societal problems'. They may want to change them, and to seek a specific solution to them. Influencing the processes observed and highlighting the possible ways in which this can be done effectively may be the main interest. Emerging issues are not identified on the basis of their relevance for the development of the discipline, but on the basis of their (potential) relevance for developments in society. The perspective is problem oriented. In the European setting 'Demography' is an ambiguous term. In German, for example, Demographie is usually considered to be quite distinct from Bevo6lkerungswissenschaft. While the first has the connotation of being basically confined to pure or Formal Demography and to deal essentially with the internal relations between demographic variables sensu stricto the second concept is much broader. It can be translated literally as 'population science' and is then akin to population studies. It deals with variables external to the population process as such and thus with the relations between that process and cultural, social and other conditions in society (Mackensen, 1981a, pp. 19, 20). Epistemologically this has important consequences. For, while Demography as the 'skeleton of a discipline' will seek its foundation in the logic of mathematics and statistics, the 'science of population' will build on the theories of sociology, psychology, economics and the like. Other European language areas may have their own concepts and terminology. The heterogeneity of Europe is frequently underestimated. Geographically it can be considered to range from Iceland and Ireland in the West to Turkey and the USSR in the East. Countries like Albania, Liechtenstein and San Marino are hardly visible on a map of Europe, while Norway, Italy and Poland are stretched out over hundreds of