Article

Name: Self-identification of people at the age of late adulthood: a comprehensive linguistic study

Authors: L. O. Butakova, E. N. Goots, N. V. Orlova, M. A. Kharlamova

Dostoevsky Omsk State University, Omsk, Russian Federation

In the section Linguistics

Abstract: For the first time, a linguistic reconstruction of the self-identification of people in late adulthood is proposed. Based on the hypothesis about the sociocultural conditionality of gerontogenesis, groups of informants are delimited by the number of years lived (from 60, from 75), gender, education, and belonging to urban or rural culture. The associative experiment, guided interviews, and participant observations allowed revealing the features of self- identification in a group of women over 75, with higher and secondary special education, urban dwellers. This group is characterized by both negative (diseases, wrinkles) and positive (rest, freedom, grandmother, assistant) components in the representation of one’s age. More pessimistic is the self-identification of rural women over 75, with a secondary and lower secondary education: in this group, the discourse was studied, but no associative experiment was conducted. Women perceive the experienced age not as a stage of life but as its outcome, with a striking feature being a return to the past. Women and men over 60 years old demonstrate a wide variability of self-identification determined by the state of health, the status of working or non-working, personal characteristics. A study of the self-identification of people in late adulthood showed the effectiveness of the methods selected with regard to the sociocultural characteristics of informants. Social signs – gender, age (elderly / senile), level of education, cultural affiliation (city / village) – affect how people see themselves at their age, that is, determine the higher or lower level of uniformity of self-identification results.

Keywords: late adulthood, self-identification, social group, semantic gestalt, text concept, associative- semantic concept deployment

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