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Kulikova A.V., Grinko M.A., Grunin G.A. [Рroblems of inequality in the modern labor market: identification of discriminatory patterns in job postings] World of Science. Series: Sociology, Philology, Cultural Studies, 2025, Vol. 16, No. 1. Available at: https://sfk-mn.ru/PDF/33SCSK125.pdf (in Russian).

Рroblems of inequality in the modern labor market: identification of discriminatory patterns in job postings

Kulikova Aleksandra Vladimirovna
National Research Lobachevsky State University of Nizhny Novgorod, Nizhny Novgorod, Russia
E-mail: kulikova-alex@yandex.ru
ORCID: https://orcid.org/0000-0002-2393-6560
RSCI: https://elibrary.ru/author_profile.asp?id=360583

Grinko Maxim Aleksandrovich
National Research Lobachevsky State University of Nizhny Novgorod, Nizhny Novgorod, Russia
E-mail: maxim.grinko@bk.ru
ORCID: https://orcid.org/0009-0006-1080-8830

Grunin Grigory Alekseevich
National Research Lobachevsky State University of Nizhny Novgorod, Nizhny Novgorod, Russia
E-mail: grigory_grunin@mail.ru
ORCID: https://orcid.org/0009-0004-7864-9878
RSCI: https://elibrary.ru/author_profile.asp?id=1287023

Abstract. The article describes the forms of inequality in the labor market when hiring employees. It was written based on the results of an empirical study aimed at identifying types of discrimination, stereotypes, and hidden biases in job postings. The research is interdisciplinary in nature, involving the study of a key social problem in the labor market, which traditionally lies in the field of interests of economic sociology, the modern field of digital sociology, big data analysis and methods of natural language processing (Natural Language Processing).
An algorithm has been developed for the automated detection of discriminatory patterns in job texts using natural language processing methods. The study is based on an analysis of the corpus of vacancy texts collected on the online recruiting portal. hh.ru from December 1 to December 25, 2024. The results of the study emphasize the importance of systematic monitoring of discrimination in the hiring process. The created tools can be used to optimize hiring practices.

The job analysis revealed several key patterns: discriminatory requirements were found in more than a quarter of the texts, which indicates the systemic nature of the problem. The predominant types of discriminatory restrictions are ethnic and age-based, gender discrimination is almost not found in the description of candidate requirements today. It was found that the level of discrimination varies depending on the profession: the largest proportion of restrictive requirements is observed in the fields of education, nutrition, management and medicine. The heterogeneous relationship between illegal demands and the level of wages has been revealed. Rather, there is no correlation between wages and discriminatory hiring criteria.

Keywords: labor market; discrimination; discrimination in employment; forms of discrimination in employment; employment inequality; natural language processing (NLP) methods; big data

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