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The Development and Validation of LGBT Bias Content for Use in an Online Training Program

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Previous research has shown that an individual's bias can have a negative impact on behavior. One proposed method of modifying such behavior is vicarious (observational) learning. In the current study, the researcher explored the possibility of using vicarious learning to create an effective training video on LGBT bias. The researcher…

Previous research has shown that an individual's bias can have a negative impact on behavior. One proposed method of modifying such behavior is vicarious (observational) learning. In the current study, the researcher explored the possibility of using vicarious learning to create an effective training video on LGBT bias. The researcher predicted that a vicarious learning video would be more effective at reducing negative LGBT bias than an informationally-equivalent control video. Participants completed the Explicit Attitudes of Sexuality questionnaire (EASQ), were randomized into one of two groups (vicarious or control), watched the assigned training video, and then completed the EASQ again to measure any changes in LGBT bias. The results of the study indicated that the vicarious video was no more effective in reducing negative LGBT bias when compared to the control. Additionally it was found that the vicarious training video was significantly more effective in eliciting new knowledge when compared to the control. The researcher discusses these findings in relation to Social Cognitive Theory for Personal and Social Change by Enabling Media. The researcher also explains how findings of insignificance could have been caused by a selection bias, self-report bias, and/or not enough treatment dosage.
ContributorsIoia, Kody Allan (Author) / Craig, Scotty (Thesis director) / Roscoe, Rod (Committee member) / Human Systems Engineering (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
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Analyzation of Hot Spot Policing Strategies Among Different Sized Departments

Description

Community-based policing and proactive policing are at the forefront of America’s efforts to improve policing. Research shows that data-driven policing, such as focusing efforts on crime hot spots, reduces crime not only in a certain area but in the overall community as well. However, each department may implement data-driven policing…

Community-based policing and proactive policing are at the forefront of America’s efforts to improve policing. Research shows that data-driven policing, such as focusing efforts on crime hot spots, reduces crime not only in a certain area but in the overall community as well. However, each department may implement data-driven policing differently depending on the unique features of the department. To examine this, interviews and observations were conducted of the Arizona State University Police Department and the Scottsdale Police Department. The results suggest that university police and municipality police have different methods, strategies, and information flow when recognizing and responding to hot spots. On this basis, police departments should develop a plan tailored to their community. Further research is needed to determine how police departments can respond to hot spots using specific community traits.
ContributorsWilson, Alex (Author) / Telep, Cody (Thesis director) / Gallagher, James (Committee member) / Barrett, The Honors College (Contributor) / School of Criminology and Criminal Justice (Contributor) / Human Systems Engineering (Contributor)
Created2021-12