Last few decades, demographers have observed changes in the organization of the individual's life course. This study is devoted to comparing Russia with other European countries in terms of matrimonial behavior modernization, identifying clusters of Russians depending on their family formation trajectories, analyzing the spread of modern trajectories among generations of Russians, finding out factors of choosing each trajectory. Parameters of family formation behavior available in the second wave of the international survey "Generation and Gender Program" demonstrated that Russia follows one way of modernization with European countries. The results of cluster analysis based on the panel data of Russian part of "Generation and Gender Survey" revealed 9 clusters of Russians according to the sequence and time of first cohabitation, marriage and firstborn. The trajectories "Early marriage, birth of a child" and "Late marriage, birth of a child" are the most common. More than 60% of the respondents from soviet generations followed these two trajectories. In case of modern generations, they were displaced by trajectories, where early or late cohabitation precedes marriage and the trajectory "Cohabitation, birth of a child". The frequencies of choosing the other four trajectories are statistically stable for different generations. Multinomial logistic regression showed that a type of settlement, level of education, ages of separation from parents and the first job, gender, generation and parents’ matrimonial experience are the factors of the family formation trajectory’s choice.
The first objective of this study was to provide an overview that briefly describes how modern research explains changes in matrimonial behavior in time and space (heterogeneity between European countries and within Russia). The second objective was to identify the main determinants of the choice of the first matrimonial union that function at macro-, meso-, and micro-levels. The third and main objective was to find an answer to the question of how changes in the matrimonial behavior of Russians are correlated with trends observed in other European countries. For this purpose, the second wave data of the international survey "Generation and Gender" and panel data of the Russian part of the same survey were employed. The analysis demonstrated that in Russia, changes typical for the unified social spaces of industrial and post-industrial societies are taking place: an increase in the number of partners over a lifetime, a gradual decrease in the proportion of people getting married, an increase in the share of single people, and a decrease in the number of second marriages. Intercountry differences in matrimonial behavior are explained by a country's historically formed type of marriage, the values profile of the population, and the family policy regime (macro-level). In Russia, as well as in other countries, the choice of first matrimonial event type is determined by the type of settlement (meso-level), age at the first union, conception preceding the union, the matrimonial experience of parents, the circumstances of leaving the parental home and entering the job market, and the level of education (micro-level).
Nowadays there is a large amount of demographic data which should be analysed and interpreted. From accumulated demographic data, more useful information can be extracted by applying modern methods of data mining. The aim of this study is to compare the methods of classification of demographic data by customizing the SVM kernels using various similarity measures. Since demographers are interested in sequences without discontinuity, formulas for such sequences similarity measures were derived. Then they were used as kernels in the SVM method, which is the novelty of this study. Recurrent neural network algorithms, such as SimpleRNN, GRU and LSTM, are also compared. The best classification result with SVM method is obtained using a special kernel function in SVM by transforming sequences into features, but recurrent neural network outperforms SVM.
This paper presents recent results of studies in application of sequence-based pattern structures and emerging patterns to analysis of demographic sequences in Russia. This study is performed on data of 11 generations from 1930 till 1984 for the panel of three waves of the Russian part of Generation and Gender Survey, which took place in 2004, 2007, and 2011. The main goal is to develop methods of extracting emerging patterns (EP) with the following restrictions: the obtained patterns need to be (closed) frequent contiguous prefixes of the input sequences. These constraints were required by demographers for proper interpretation and understanding of early life course events that lead to adulthood. To fulfil this requirement we used modified FP-trees based on pattern structures of contiguous prefixes. After extraction of EP we use CAEP(Classification by Aggregating Emerging Patterns) classifier to predict gender of respondents using their demographic sequences of the first life course events. The best results in terms of TPR-FPR have been obtained for large values of minimum growth-rate parameter (with some objects left without classification).
The article is devoted to the migration processes of the Crimea in the last decades. Conducted census data analysis allowed us to track changes in migration processes Peninsula. For the Crimea is characterized by migration exchanges with the neighboring regions of Ukraine and Russia. Forced deportations during World War II caused further repatriation from Uzbekistan and Kazakhstan. Generally speaking, the role of migration in the formation of the region’s population over time is reduced, increasing the share of natives of the Crimea. This is possible a short burst of migration associated with the entry of the peninsula in Russia. However, offcial estimates of migration are posted on the websites of statistical offces of regions represented overestimated. Among the migrants is increasing the proportion of old-timers – who lives long enough in the place of introduction, and has the lowest probability of further migration.
This study focuses on changing family formation trajectories in the Russian Federation. In European countries, pathways to family ceased being stable several decades ago, while in Russia – as in any post-socialist country – such features of life course deinstitutionalization as postponement of marriage, rising cohabitation, and reordering of events were revealed only in the 1990s and explained from the perspective of the Second Demographic Transition (SDT). Our aim is to demonstrate how family formation trajectories of men and women from different generations were transforming with the incorporation of data mining. The three-wave panel data of the Russian part of the “Generations and Gender Survey” (2004, 2007, 2011; N=5321) and the retrospective data of the survey “Person, Family, Society” (2013; N=4477) are used for achieving this aim. Sequence Analysis shows that generations born after 1970 started to exhibit de-standardized family formation trajectories. As the proportion of Russians who raise children in cohabitation or while single rises, such models of behavior become more widely accepted and practiced in contemporary Russia. Women experience more events in the family trajectory, take steps toward family formation earlier, and stay alone with children more often than men. Matrimonial and reproductive behavior has become diverse, proving that Russia fully exhibits the SDT.
Russia has long been characterized by early and universal marriage. After the Soviet Union collapse, the average age of marriage has been rising, and cohabitations have become common. Many scholars explain the causes of this trend through the perspective of the Second Demographic Transition. The aim of this research was to define the nature of cohabitations in Russia, reveal the factors of entrance to non-marital unions in order to discuss how and why non-marital union is implicated in recent dialogues about family policy. In order to achieve the aim, such methods as Event History Analysis and Sequence Analysis were used.
Cohabitation is not a complete alternative to marriage in Russia yet, but the proportion of Russians from various social strata for whom cohabitation does not grow into a marriage is on the rise. Young, non-religious, educated people from big cities have started to consider non-marital union appropriate for childbearing and childrearing. It demonstrates that cohabitation is close to becoming an independent social institution which is a trend of great concern to policymakers due to its implications for children’s well-being.
We investigated the factors which influence whether people prefer marriage or cohabitation as the first union. We revealed that the generations who were before 1965 chose marriage in 75% of cases. People were born after 1975 preferred cohabitation (55% of cases).
The revealed factors confirm the main tendencies of the Second Demographic Transition: people who prefer marriage as the first union more often conceived a child before starting a union; they lived with parents before the start of the union; they came from wealthy families; and they postponed their careers. The only difference is that, usually, people who started with cohabitations have higher education, but in Russia these are people with lower levels of education.
In this paper, we summarize the results of recent studies on the application of pattern mining and machine learning to the analysis of demographic sequences. The main goal is the demonstration of demographers’ needs, including next-event prediction and the extraction of interesting patterns from substantial datasets of demographic data, which cannot be handled by conventional demographic techniques. We use decision trees as a technique for demographic event prediction, and emerging sequential patterns and pattern structures for discovering relevant interpretable sequences. The emerging problem statements and positive prospects of the usage of pattern mining in the demography domain are worth dissemination in the data mining community.
his paper presents the first results of studies in application of sequence-based pattern structures and emerging patterns to analysis of demographic sequences in Russia. This study is performed on data of 11 generations from 1930 till 1984 for the panel of three waves of the Russian part of Generation and Gender Survey, which took place in 2004, 2007, and 2011. The main goal is to develop methods of extracting emerging patterns (EP) with the following restrictions: the obtained patterns need to be (closed) frequent gapless prefixes of the input sequences. These constraints were required by demographers since it is necessary for proper interpretation and understanding of early life course events that lead to adulthood. To solve this problem, we used pattern structures of gapless prefixes and modified FP-trees. After extraction of EP we use CAEP classifier to predict gender of respondents using their demographic sequences of the first life course events. The best results in terms of TPR-FPR have been obtained for large values of minimum growth-rate parameter (with some objects left without classification).
The paper was prepared within the framework of the Academic Fund Program at HSE in 2016 (grant № 16-05-0011 ``Development and testing of demographic sequence analysis and mining techniques'') and supported within the framework of a subsidy granted to the HSE by the Government of the Russian Federation for the implementation of the Global Competitiveness Program.