Date of Award

8-2018

Document Type

Thesis

Degree Comments

Submitted to the College of Graduate Studies Bridgewater State University Bridgewater, Massachusetts in partial fulfillment of the requirements for the Degree of Master of Science in Criminal Justice.

Degree Program

Criminal Justice

Degree Type

Master of Science

Abstract

Through the work done by Shaw & McKay (1942), Bursik (1989), Messner & Sampson (1991), and Sampson & Wilson (1995), social disorganization and focus on inner-city crime became a major point of interest for researchers. The idea of social disorganization looks at the weakening of social institutions, both formal and informal, that eventually lead to crime and the study of crime patterns in urban areas. This framework has been used to study crime and pinpoint areas where decisions from governmental officials and local communities have eroded the collective efficacy of neighborhoods, leading to crime. In 2003, the FCC made changes to the media ownership rules that allowed for the intrusion of implicit bias into news mediums like a virus, hijacking the content being sent out to the public for consumption. Then, in 2005, Jerry Kang came up with ideas that accused the FCC to be directly linked with the bias in media and for the increase of arrest rates in minority groups, mainly the Black population. Kang’s arguments piggybacked on the arguments of Sampson & Wilson in regards to utilizing the macro-structural approach when looking at conscious political decisions actively affecting crime, and positing that the FCC was responsible for doing just that. This study looks to use the framework and ideas put forth by both Sampson & Wilson (1995) and Kang (2005) to connect the FCC to media implicit bias and increased arrest rates of minority groups. The study utilized the top 110 cities or markets in terms of television and cable advertising to show how impactful implicit bias in in changing arrest rates, and also focuses on the arrest rates of both White and Black populations as well as demographic and population data to run a multivariate regression OLS analysis.

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