To the methodology of socio-geographical research of the internal displacement of the population - Lohvynova, Maryna (Human Geography Journal, 2019)
In this article, the author analyzes the approaches and methods of studying migration processes, in particular, forced internal displacement of the population. The analysis of foreign and domestic literature showed that domestic researchers of migration processes use traditional methods and approaches, while foreign scientists use interdisciplinary tools of approaches and methods. For a comprehensive socio-geographical study, it is necessary to combine traditional industry and interdisciplinary methods, which will reveal the real extent of forced internal displacement of the population at the regional and national levels. In addition, the use of this technique will allow conducting qualitative or quantitative studies of migrations, assessing the scale of migration processes, and revealing the structural and dynamic characteristics of migrants.To study the internal population displacement, the author suggests using the following approaches: geographical, systemic, synergetic, informational, historical, demographic, economic, legal, sociological, psychological, individual. The author considers the use of traditional methods of socio-geographical research of migration processes. Of great importance are philosophical and general scientific methods, in particular analysis and synthesis, induction and deduction, observation, abstraction, and others. The necessity of using sociological and mathematical-statistical methods is substantiated. In this case, depending on the type of data collected, use qualitative (coding or content analysis) or quantitative (statistical methods: regression, descriptive statistics or modeling of structural equations) methods. The effectiveness of research on migration processes is enhanced by mathematical methods, in particular modeling. The following types of models are used in forecasting migration processes: open or closed models; discrete or continuous models; deterministic or stochastic models. The most effective, in our opinion, is the G. Zipf gravity model, as well as various types of regression models.