Analysis of the population structure by level of education
Автор: Ketova K.V., Vavilova D.D., Kuzmin M.S.
Журнал: Международный журнал гуманитарных и естественных наук @intjournal
Рубрика: Социологические науки
Статья в выпуске: 6-2 (45), 2020 года.
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The article is analyzed the population structure by educational level for the period 2000-2018, using the example of the regional socio-economic system of the Udmurt Republic. A technique is proposed for converting the initial statistical information from census and micro census data to solve the problem of analyzing the level of education of the population using a schematic representation of the education system in the Russian Federation. Given the periods of study at different levels of education, the number of graduates of higher educational institutions, secondary specialized vocational institutions, school graduates, as well as migration processes in the region, the number of population groups by the level of education in the Udmurt Republic was calculated. As a result of the analysis, it was found that a significant increase in the share of the population with higher education is observed in the region (it increased from 13,2 % in 2000 to 30,9 % in 2018), as well as an increase in the share of the population with secondary specialized education over the past decade. The percentage of the population with secondary vocational education has been decreasing since 2000, from 49 % to 44 % in 2010, then there is an increase in the percentage of this population to 50 % in 2018. The share of people in the population of the Udmurt Republic with a degree over the period 2000-2018 increased from 0,2 % in 2000 to 0,5 % in 2018. The percentage of people in the population of the UR with secondary and basic general education for the period 2000-2018 decreased from 30% in 2000 to 16% in 2018. The share of the population without education has decreased over the past 18 years from 2 % to 1 %.
Regional socio-economic system, population, educational levels, investment in education
Короткий адрес: https://sciup.org/170190823
IDR: 170190823 | DOI: 10.24411/2500-1000-2020-10692