Date of Award

8-2014

Degree Type

Dissertation

Degree Name

Doctor of Philosophy (PhD)

Department

Political Science, International Development, and International Affairs

Committee Chair

David Butler

Committee Chair Department

Political Science, International Development, and International Affairs

Committee Member 2

Edward Sayre

Committee Member 2 Department

Political Science, International Development, and International Affairs

Committee Member 3

Amy Miller

Committee Member 3 Department

Anthropology and Sociology

Committee Member 4

JJ St. Marie

Committee Member 4 Department

Political Science, International Development, and International Affairs

Committee Member 5

Robert Pauly

Committee Member 5 Department

Political Science, International Development, and International Affairs

Abstract

This dissertation uses a three-article dissertation model to 1) compare how deviance is defined and what is considered deviant comparing the United States to South Korea using content analysis, 2) test socio-demographic and social network variables in the development of one’s approval of deviance using eleven ordinary least squared regression models, and 3) examine the association between social networks and approval of deviant behaviors using social network analysis. All three articles use data from a survey on perceptions of deviant behavior. The survey was conducted in English and Korean. The first article provides comparisons on how deviance is defined and what is defined as deviant. Although the research did not find a consensus, nor did it expect to find a consensus, on how deviance is defined, a strong majority of survey respondents define deviance as behaviors that go against social norms and are negative. This research also reveals that there is a greater consensus as to what behaviors are considered deviant in South Korea than in the United States. The second article tests the hypothesis that perceived approval of one’s social network is a greater predictor (i.e., statistically significant across more models) than traditional socio-demographic variables (i.e., gender, age, and income will not be as strong an indicator as social network) in an individual’s approval of deviance. The results of regression analysis indicate that 1) one’s social network is the greatest predictor of his/her tolerance of deviance behaviors and 2) there is more consensus among South Koreans regarding what is considered deviant than among Americans. The third article finds a statistically significant correlation between an ego’s approval of seven deviant behaviors and that of the perceived approval of his/her network. Respondents reporting that they approve of a behavior have at least one alter that also approves of the behavior but an average of two or three alters approving of the behavior. The research concludes that relational data is more robust than attribute data in the study of perceptions of deviance but emphasizes that attribute data must be understand as a factor in relational data.

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