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Description
Social impact bonds (SIBs) are a multi-year contract between social service providers, the government, and private investors. The three parties agree on a specific outcome for a societal issue. Investors provide capital required for the service provider to operate the project. The service provider then delivers the service to the

Social impact bonds (SIBs) are a multi-year contract between social service providers, the government, and private investors. The three parties agree on a specific outcome for a societal issue. Investors provide capital required for the service provider to operate the project. The service provider then delivers the service to the target population. The success of the project is evaluated by outside party. If the target outcome is met, the government repays the investors at a premium. Nonprofit service providers can only serve a small community as they lack the funding to scale their programs and their reliance on government funding and philanthropy leads to a lot of time focused on raising money in the short-term and inhibits them from evolving their programs and projects for long-term strategic success. Government budgets decline but social problems persist. These contracts share risk between the government and the investors and allow governments to test out programs and alleviate taxpayer burdens from unsuccessful social service programs. Arizona has a severe homelessness problem. Nightly, 6000 people are homeless in Maricopa County. In a given year, over 32,000 individuals were homeless, composed of single adults, families, children, and veterans. Homelessness is not only a debilitating and difficult experience for those who experience it, but also has considerable economic costs on society. Homeless individuals use a number of government programs beyond emergency shelters, and these can cost taxpayers billions of dollars per year. Rapid rehousing was a successful intervention model that the state has been heavily investing in the last few years. This thesis aimed to survey the Arizona climate and determine what barriers were present for enacting an SIB for homelessness. The findings showed that although there are many competent stakeholder groups, lack of interest and overall knowledge of SIBs prevented groups from taking responsibility as the anchor for such a project. Additionally, the government and nonprofits had good partnerships, but lacked relationships with the business community and investors that could propel an SIB. Finally, although rapid rehousing can be used as a successful intervention model, there are not enough years of proven success to justify the spending on an SIB. Additionally, data collection for homelessness programming needs to be standardized between all relevant partners. The framework for an SIB exists in Arizona, but needs a few more years of development before it can be considered.
ContributorsAhmed, Fabeeha (Author) / Desouza, Kevin (Thesis director) / Lucio, Joanna (Committee member) / School of Politics and Global Studies (Contributor) / Department of Economics (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
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Description
As of late, many universities and colleges have been attempting to change their policies that surround campus sexual assault in order to maintain their compliance as an educational institution by the Department of Education Title IX, Clery Act, the Family Educational Rights and Privacy Act (FERPA) and locally, by the

As of late, many universities and colleges have been attempting to change their policies that surround campus sexual assault in order to maintain their compliance as an educational institution by the Department of Education Title IX, Clery Act, the Family Educational Rights and Privacy Act (FERPA) and locally, by the Arizona Board of Regents (ABOR). Currently, statistics show that 1 in 5 women will be sexually assaulted during her college career. Educational institutions are becoming overwhelmed by law suits and other remedies in order to satisfy complaints of campus sexual assault. To understand the current mood of students at Arizona State University (ASU) on the topic of campus sexual assault, the present study examined the current knowledge of students regarding resources at ASU, as well as their potential commitment to participate in new policies at ASU. The sample (N=238) consisted of 20.2% male and 79.8% female of varying years of study from undergraduate to masters who overwhelming agreed that they would adhere to the three (3) recommendations of policy change at ASU in order to educate students on the dangers of campus sexual assault. Survey evaluations are discussed to show support for the recommended policies. Keywords: campus sexual assault, rape myth acceptance, policy implementation, recommendations
ContributorsCervantes, Felix Del Campo (Author) / Desouza, Kevin (Thesis director) / Roe-Sepowitz, Dominique (Committee member) / Barrett, The Honors College (Contributor) / School of Public Affairs (Contributor)
Created2015-05
Description
Social media users are inundated with information. Especially on Instagram--a social media service based on sharing photos--where for many users, missing important posts is a common issue. By creating a recommendation system which learns each user's preference and gives them a curated list of posts, the information overload issue can

Social media users are inundated with information. Especially on Instagram--a social media service based on sharing photos--where for many users, missing important posts is a common issue. By creating a recommendation system which learns each user's preference and gives them a curated list of posts, the information overload issue can be mediated in order to enhance the user experience for Instagram users. This paper explores methods for creating such a recommendation system. The proposed method employs a learning model called ``Factorization Machines" which combines the advantages of linear models and latent factor models. In this work I derived features from Instagram post data, including the image, social data about the post, and information about the user who created the post. I also collect user-post interaction data describing which users ``liked" which posts, and this was used in models leveraging latent factors. The proposed model successfully improves the rate of interesting content seen by the user by anywhere from 2 to 12 times.
ContributorsFakhri, Kian (Author) / Liu, Huan (Thesis director) / Morstatter, Fred (Committee member) / Computer Science and Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2016-12