In U.S. society, the systems of gender and race operate to privilege and oppress individuals based on their location within these systems. All of the interactions an individual experiences as they go about their day-to-day lives are shaped by these interlocking systems. As a result, there is an extensive body of sociological literature addressing how individuals in U.S. society are privileged and oppressed on the basis of their perceived membership in gender and race categories; however, relatively little research exists examining how individuals come to be seen by others as members of gender and race categories in the first place. In order to address this gap in the existent literature, this thesis asked 354 participants to perform gender and race categorizations for 28 target individuals of various gender and race category memberships. Participants were asked to make a categorization, rate how confident they were in that categorizations accuracy, and then explain why they made the gender or race categorization that they did. In analyzing these categorizations, this thesis produced three important findings about the process of gender and race categorization. First, this thesis identified two gender categories ("female" and "male") and eight race categories ("White," " Black," "Latino," "Asian," "Southeast Asian," "South Asian/Indian," "Middle Eastern," and "Mixed Race") used in gender and race categorization. Second, particularly in the common usage of the biologically-based concepts of "sex" and "race," rather than the socially-based concepts of "gender" and "ethnicity." Third, this thesis found interactions between the gender and race systems in categorization, finding that White individuals and male individuals are gender categorized more easily than Black individuals or female individuals, and individuals will less "ambiguous" skin coloration are more easily categorized than others.
Identifer | oai:union.ndltd.org:ucf.edu/oai:stars.library.ucf.edu:etd-5493 |
Date | 01 January 2014 |
Creators | Simpkins, Joshua |
Publisher | STARS |
Source Sets | University of Central Florida |
Language | English |
Detected Language | English |
Type | text |
Format | application/pdf |
Source | Electronic Theses and Dissertations |
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