Russian middle classes criterial identification

 
PIIS013216250004592-4-1
DOI10.31857/S013216250004592-4
Publication type Article
Status Published
Authors
Occupation: Head of Laboratory of the Problems of Level of Life and Quality of Life; Chief Research Scientist
Affiliation:
Institute of Socio-Economic Studies of Population of the Russian Academy of Sciences
Plekhanov Russian University of Economics
Address: Russian Federation, Moscow
Occupation: Leading Researcher of Laboratory of the Problems of Level of Life and Quality of Life
Affiliation: Institute of Socio-Economic Studies of Population of the Russian Academy of Sciences
Address: Russian Federation, Moscow
Occupation: Senior Lecturer
Affiliation: Plekhanov Russian University of Economics
Address: Russian Federation, Moscow
Journal nameSotsiologicheskie issledovaniya
EditionIssue 4
Pages118-125
Abstract

The article is devoted to the problem of middle classes identification. The authors propose criterial approach according to which middle classes are identified according to predetermined criteria. These criteria could be determined in relation to social and economic situation in particular society. There are two types of criteria: objective criterion that includes professional status, education, income, wealth, property etc.; subjective criterion – self-identification of middle classes representatives. To specify these criteria for Russian society the authors conducted expert poll among highly experienced in this topic individuals. Respondents were asked to estimate proposed in the questionnaire criteria for middle classes identification. After conducting analysis of the survey’ results the authors proposed model of criteria relevance to Russian conditions depending on the assessment by the expert.

Keywordsmiddle classes, identification criteria, criteria boundaries, social standards, education, employment position, prosperity, self-identification, expert poll, mass survey
AcknowledgmentThe research is supported by Russian Foundation for Basic Research, project №16-02-00533-OGN.
Received28.05.2019
Publication date28.05.2019
Number of characters19037
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