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- Creators: Duarte, Marisa E.
- Creators: Cooke, Nancy J.
- Resource Type: Text
- Status: Published
Description
Mexico City has an ongoing air pollution issue that negatively affects its citizens and surroundings with current structural disconnections preventing the city from improving its overall air quality. Thematic methodological analysis reveals current obstacles and barriers, as well as variables contributing to this persistent problem. A historical background reveals current programs and policies implemented to improve Mexico’s City air quality. Mexico City’s current systems, infrastructure, and policies are inadequate and ineffective. There is a lack of appropriate regulation on other modes of transportation, and the current government system fails to identify how the class disparity in the city and lack of adequate education are contributing to this ongoing problem. Education and adequate public awareness can potentially aid the fight against air pollution in the Metropolitan City.
ContributorsGarcia, Lucero (Author) / Duarte, Marisa E. (Thesis advisor) / Arzubiaga, Angela (Committee member) / Richter, Jennifer (Committee member) / Arizona State University (Publisher)
Created2018
Description
Civilian and military use of remotely piloted aircraft (RPA) has significantly increased in recent years. Specifically, the United States Air Force (USAF) has an insatiable demand for RPA operations, that are responsible for fulfilling critical demands in every theater 24 hours a day, 365 days a year (United States Air Force, 2015). Around the clock operations have led to a manning shortage of RPA pilots in the USAF. The USAF MQ-9 “Reaper” Weapons School trains tactical experts and leaders of Airmen skilled in the art of integrated battle-space dominance (United States Air Force, 2015). Weapons Officers for the MQ-9 platform are also critically under-manned, with only 17% of allocated slots filled (B. Callahan, personal communication, January 28, 2016). Furthermore, the leading cause of training attrition has been attributed to lack of critical thinking and problem solving skills (B. Callahan, personal communication, January 28, 2016); skills not directly screened for prior to entering the RPA pilot career field. The proposed study seeks to discover patterns of student behaviors in the brief and debrief process in Weapons School, with the goal of identifying the competencies that distinguish the top students in Weapons School.
ContributorsDriggs, Jade B (Author) / Cooke, Nancy J. (Thesis advisor) / Niemczyk, Mary (Committee member) / Roscoe, Rod (Committee member) / Arizona State University (Publisher)
Created2017
Description
Software systems can exacerbate and cause contemporary social inequities. As such, scholars and activists have scrutinized sociotechnical systems like those used in facial recognition technology or predictive policing using the frameworks of algorithmic bias and dataset bias. However, these conversations are incomplete without study of data models: the structural, epistemological, and technical frameworks that shape data. In Modeling Power: Data Models and the Production of Social Inequality, I elucidate the connections between relational data modeling techniques and manifestations of systems of power in the United States, specifically white supremacy and cisgender normativity. This project has three distinct parts. First, I historicize early publications by E. F. Codd, Peter Chen, Miles Smith & Diane Smith, and J. R. Abrial to demonstrate that now-taken-for-granted data modeling techniques were products of their social and technical moments and, as such, reinforced dominant systems of power. I further connect database reification techniques to contemporary racial analyses of reification via the work of Cheryl Harris. Second, I reverse engineer Android applications (with Jadx and apktool) to uncover the relational data models within. I analyze DAO annotations, create entity-relationship diagrams, and then examine those resultant models, again linking them back to systems of race and gender power. I craft a method for performing a reverse engineering investigation within a specific sociotechnical context -- a situated analysis of the contextual epistemological frames embedded within relational paradigms. Finally, I develop a relational data model that integrates insights from the project’s reverse and historical engineering phases. In my speculative engineering process, I suggest that the temporality of modern digital computing is incommensurate with the temporality of modern transgender lives. Following this, I speculate and build a trans-inclusive data model that demonstrates uses of reification to actively subvert systems of racialized and gendered power. By promoting aspects of social identity to first-order objects within a data model, I show that additional “intellectual manageability” is possible through reification. Through each part, I argue that contemporary approaches to the social impacts of software systems incomplete without data models. Data models structure algorithmic opportunities. As algorithms continue to reinforce systems of inequality, data models provide opportunities for intervention and subversion.
ContributorsStevens, Nikki Lane (Author) / Wernimont, Jacqueline D (Thesis advisor) / Michael, Katina (Thesis advisor) / Richter, Jennifer (Committee member) / Duarte, Marisa E. (Committee member) / Arizona State University (Publisher)
Created2022