JOURNAL ARTICLE
Gloria Steinem: The childhood foundations of a feminist.
Published In: Journal of Personality, 2023, v. 91, n. 1. P. 193 1 of 3
Database: Academic Search Ultimate 2 of 3
Authored By: Duncan, Lauren E. 3 of 3
Abstract
Objective: Gloria Steinem is one of the best‐known feminists active in the United States today. This article addresses aspects of Steinem's childhood and adolescence to help us understand how her experiences helped set the stage for Steinem's development into a feminist in midlife. Methods: Using holistic narrative analysis, I identified themes that seemed to impact some of the fundamental values, assumptive frameworks, and expectations about the world that Steinem developed in childhood. Results: Specifically, from her relationship with her father, Steinem learned that men were not responsible providers but could be fun adventure partners, and that women were just as competent as men. From witnessing her mother's psychological problems, Steinem learned that women's traditional roles could be damaging to women, that she did not want to be a traditional wife and mother, and that psychological treatment could be ineffective if underlying life circumstances were not addressed. Conclusions: Because her parents were not reliable caregivers, Steinem developed an insecure attachment style characterized by precocious independence and compulsive self‐reliance, which allowed her to defy the gendered expectations of her emerging adulthood and set her up to be profoundly influenced by the 1970s Women's Movement in midlife. [ABSTRACT FROM AUTHOR]
Additional Information
- Source:Journal of Personality. 2023/02, Vol. 91, Issue 1, p193
- Document Type:Article
- Subject Area:Literature and Writing
- Publication Date:2023
- ISSN:0022-3506
- DOI:10.1111/jopy.12732
- Accession Number:161007935
- Copyright Statement:Copyright of Journal of Personality is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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