The perception of economic inequality in everyday life: My friends with the most and the least money

 

Đã lưu trong:
Chi tiết về thư mục
Nhiều tác giả: García Castro, Juan Diego, García Sánchez, Efraín, Montoya Lozano, Mar, Rodríguez Bailón, Rosa
Định dạng: artículo original
Ngày xuất bản:2021
Miêu tả:The study of perceived economic differences in everyday life is relevant to deepen the knowledge of how inequality shapes psychological processes. In the current research, Spanish undergraduates (N=547) were asked what their friends with the most and least money could do with their resources. Using a qualitative and quantitative approach, we performed a content analysis of the 1,085 open-ended responses given, ran latent class analyses with the coded material to identify groups of participants, and explored whether class membership was associated with their awareness of inequality and support for redistribution. Participants perceived inequality among their friends through daily indicators such as consumption, opportunities, leisure, and mental health; some participants used compensatory strategies to mitigate perceived inequality. Latent class analyses suggested that participants differed mostly in the attention paid to consumption and in the use of compensatory strategies. Exploratory analyses suggested that perceiving inequality in everyday life in terms of consumption, negative attributes towards the wealthy, or positive attributes towards low socioeconomic groups was related to acknowledging economic differences among individuals and support for redistribution. The study of perceived economic inequality in everyday life continues a new line of research with the potential to obtain results more consistent with people's experiences.
Quốc gia:Kérwá
Tổ chức giáo dục:Universidad de Costa Rica
Repositorio:Kérwá
Ngôn ngữ:Inglés
OAI Identifier:oai:kerwa.ucr.ac.cr:10669/83063
Truy cập trực tuyến:https://hdl.handle.net/10669/83063
Từ khóa:perceived inequality
everyday life
reference groups
social class
economic inequality
latent class analysis