Theses and dissertations

This collection includes both ASU Theses and Dissertations, submitted by graduate students, and the Barrett, Honors College theses submitted by undergraduate students. 

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Female Microaggressions Scale (FeMS): A Comprehensive Sexism Scale

Description
Overt forms of sexism have become less frequent (Swim Hyers, Cohen & Ferguson, 2001; Sue & Capodilupo, 2008). Nonetheless, scholars contend that sexism is still pervasive but often manifests as female microaggressions, which have been defined as often subtle, covert forms of gender discrimination (Capodilupo et al., 2010). Extant sexism…

Overt forms of sexism have become less frequent (Swim Hyers, Cohen & Ferguson, 2001; Sue & Capodilupo, 2008). Nonetheless, scholars contend that sexism is still pervasive but often manifests as female microaggressions, which have been defined as often subtle, covert forms of gender discrimination (Capodilupo et al., 2010). Extant sexism scales fail to capture female microaggresions, limiting understanding of the correlates and consequences of women’s experiences of gender discrimination. Thus, the purpose of the current study was to develop the Female Microaggressions Scale (FeMS) based on an existing theoretical taxonomy and content analysis of social media data, which identifies diverse forms of sexism. Two separate studies were conducted for exploratory factor analysis (N = 582) and confirmatory factor analysis (N = 325). Exploratory factor analyses supported an eight-factor, correlated structure and confirmatory factor analyses supported a bifactor model, with eight specific factors and one general FeMS factor. Overall, reliability and validity of the FeMS (general FeMS and subscales) were mostly supported in the two present samples of diverse women. The FeMS’ subscales and body surveillance were significantly positively correlated. Results regarding correlations between the FeMS subscales and anxiety, depression, and life satisfaction were mixed. The FeMS (general FeMS) was significantly positively correlated with anxiety, body surveillance, and another measure of sexism but not depression or life satisfaction. Furthermore, the FeMS (general FeMS) explained variance in anxiety and body surveillance (but not depression, self-esteem, or life satisfaction) above and beyond that explained by an existing sexism measure and explained variance in anxiety and depression (but not self-esteem) above and beyond that explained by neuroticism. Implications for future research are discussed.
ContributorsMiyake, Elisa (Author) / Tran, Giac-Thao Thanh (Thesis advisor) / Bernsten, Bianca (Committee member) / Tracey, Terence (Committee member) / Arizona State University (Publisher)
Created2018
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Ethnic Discrimination, Socioeconomic Status, and Health in India

Description

Significant health inequalities exist between different castes and ethnic communities in India, and identifying the roots of these inequalities is of interest to public health research and policy. Research on caste-based health inequalities in India has historically focused on general, government-defined categories, such as “Scheduled Castes,” “Scheduled Tribes,” and “Other…

Significant health inequalities exist between different castes and ethnic communities in India, and identifying the roots of these inequalities is of interest to public health research and policy. Research on caste-based health inequalities in India has historically focused on general, government-defined categories, such as “Scheduled Castes,” “Scheduled Tribes,” and “Other Backward Classes.” This method obscures the diversity of experiences, indicators of well-being, and health outcomes between castes, tribes, and other communities in the “scheduled” category. This study analyzes data on 699,686 women from 4,260 castes, tribes and communities in the 2015-2016 Demographic and Health Survey of India to: (1) examine the diversity within and overlap between general, government-defined community categories in both wealth, infant mortality, and education, and (2) analyze how infant mortality is related to community category membership and socioeconomic status (measured using highest level of education and household wealth). While there are significant differences between general, government-defined community categories (e.g., scheduled caste, backward class) in both wealth and infant mortality, the vast majority of variation between communities occurs within these categories. Moreover, when other socioeconomic factors like wealth and education are taken into account, the difference between general, government-defined categories reduces or disappears. These findings suggest that focusing on measures of education and wealth at the household level, rather than general caste categories, may more accurately target those individuals and households most at risk for poor health outcomes. Further research is needed to explain the mechanisms by which discrimination affects health in these populations, and to identify sources of resilience, which may inform more effective policies.
ContributorsClauss, Colleen (Author) / Hruschka, Daniel (Thesis director) / Davis, Mary (Committee member) / Barrett, The Honors College (Contributor) / School of Human Evolution & Social Change (Contributor) / Department of Psychology (Contributor)
Created2022-05