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- All Subjects: Communication
- All Subjects: artificial intelligence
- Creators: Arizona State University
- Status: Published
Description
This study utilizes semiotic phenomenology as a method of inquiry to describe the lived experiences of Lesbian, Gay, Bisexual, Transgender, Queer (LGBTQ) gamers (gaymers). I begin by discussing my issues with the current gaming literature, arguing that the gamer community is a space that privileges cis, heterosexual, and hypermasculine men while oppressing those who may not fit this mold. I discuss the shortcomings of the current literature that attempts to critically look at race and gaming, noting that race in the gaming community is still portrayed as secondary. I focus special attention to how this space allows for more inclusion than the larger gamer and LGBTQ communities while also critiquing those whom this space privileges. Through interviews of members of the local gaymer organization, the Phoenix Gaymers, I discuss ways in which the gaymer community is more inclusive and conscious of others but still follows forms of what I describe to be gaymer privilege. I focus on gaymer privilege within the intersections of race, gender, and sexuality, where I argue from the phenomenological descriptions, reductions, and interpretations that there are still overt issues of sexism and transphobia as well as implicit issues of white privilege. While I describe the issues that are found within the Phoenix Gaymers, I also attempt to provide suggestions for change within the organization as well as in academic scholarship to create more awareness and inclusion for female, transgender, genderqueer, and queer people of color gaymers.
ContributorsOmori, Jeremy Michael (Author) / Sandlin, Jennifer (Thesis advisor) / Martinez, Jacqueline M (Committee member) / Pérez, Kimberlee (Committee member) / Linde, Jennifer (Committee member) / Arizona State University (Publisher)
Created2017
Description
This dissertation sought to understand how leaders in a public-private strategic alliance collaboratively address complex community problems. The study responded to the gap in academic research of leadership and public relations in alliances to solve complex social issues, as well as the scant scholarly attention to alliance leaders' communications with stakeholders. Its findings corresponded to framing theory, stakeholder theory, SWOT (strengths/weaknesses/opportunities/threats) theory, complexity theory, and the subtopic of complex leadership -- all through the lens of public relations. This investigation culminated in the introduction of the C.A.L.L. to Action Model of Community Engagement, which demonstrates the confluence of factors that were integral to the alliance's success in eliminating chronic homelessness among veterans in Maricopa County, Arizona -- Communication, Alliance, Leadership, and Leverage. This qualitative case study used the method of elite or in-depth interviews and grounded theory to investigate the factors present in a community engagement that achieved its purpose. It served as a foundation for future inquiry and contributions to the base of knowledge, including 1) additional qualitative case studies of homeless alliances in other communities or of other social issues addressed by a similar public-private alliance; 2) quantitative methods, such as a survey of the participants in this alliance to provide triangulation of the results and establish a platform for generalization of the results to a larger population.
ContributorsSweeter, Janice Martha (Author) / Matera, Frances (Thesis advisor) / Godfrey, Donald G. (Committee member) / Gilpin, Dawn (Committee member) / Shockley, Gordon (Committee member) / Arizona State University (Publisher)
Created2015
Description
ABSTRACT
This study examines the ways in which employees experience moral emotions that violate employee treatment and how employees co-construct moral emotions and subsequent expressions of dissent. This qualitative study consisted of 123 full-time employees and utilized open-coding, content analysis, constant comparison analysis, and concept mapping. The analysis revealed that employees expressed dissent laterally as a series of sensemaking processes, such as validation of feelings, moral assessments, and assessing the fear of moral transgressions. Employees also expressed dissent as a series of risk assessments that overlapped with the ways in which employees made sense of the perceived infraction. Employees' lateral dissent expression manifested as a form of social support which occasionally led to co-rumination. Employees expressed dissent upwardly when seeking a desired action or change. Circumvention was utilized as a direct reflection to the type and degree of moral transgression related to the person responsible for the mistreatment. Results indicated that experiencing moral emotions that led to expressing dissent with a designated audience was determined by where employees were situated in the cyclical model of communicating moral emotions and in relation to the co-construction of both the infraction related to employee mistreatment and the experience of moral emotions. Results contribute to the existing body of literature on dissent and emotions. A discussion synthesizing the findings and analysis is presented, in addition to the implications for future research.
KEYWORDS: Emotion, Dissent, Moral Emotions, Sensemaking, Risk-Assessment, Social Support, Co-Rumination
This study examines the ways in which employees experience moral emotions that violate employee treatment and how employees co-construct moral emotions and subsequent expressions of dissent. This qualitative study consisted of 123 full-time employees and utilized open-coding, content analysis, constant comparison analysis, and concept mapping. The analysis revealed that employees expressed dissent laterally as a series of sensemaking processes, such as validation of feelings, moral assessments, and assessing the fear of moral transgressions. Employees also expressed dissent as a series of risk assessments that overlapped with the ways in which employees made sense of the perceived infraction. Employees' lateral dissent expression manifested as a form of social support which occasionally led to co-rumination. Employees expressed dissent upwardly when seeking a desired action or change. Circumvention was utilized as a direct reflection to the type and degree of moral transgression related to the person responsible for the mistreatment. Results indicated that experiencing moral emotions that led to expressing dissent with a designated audience was determined by where employees were situated in the cyclical model of communicating moral emotions and in relation to the co-construction of both the infraction related to employee mistreatment and the experience of moral emotions. Results contribute to the existing body of literature on dissent and emotions. A discussion synthesizing the findings and analysis is presented, in addition to the implications for future research.
KEYWORDS: Emotion, Dissent, Moral Emotions, Sensemaking, Risk-Assessment, Social Support, Co-Rumination
ContributorsKamrath, Jessica K (Author) / Kassing, Jeffrey W. (Thesis advisor) / Waldron, Vincent R. (Committee member) / Meân, Lindsey J. (Committee member) / Arizona State University (Publisher)
Created2015
Description
Scholars have attended to paradoxes inherent in wider public discourse where subordinated groups most affected by laws and sanctions have the least political, material, and rhetorical capital to speak back to them. Such scholarship often focuses either on the subordinated status of a group or the work of subordinated groups going public as part of a collective mass movement for social change. In doing so, scholarship risks undermining the agency of subordinated rhetors or treating mass-movement rhetoric as somehow both exceptional and yet necessary for enacting cultural citizenship. What is less frequently studied is the agency that local publics demonstrate through their tenacious organizational decision-making in the face of political, material, and rhetorical sanctions.
In response to this gap, this project features the Puente Movement, a mixed-documentation-status grassroots organization in Phoenix, AZ. Specifically, I’ve analyzed this organization’s public efforts from April 23rd, 2010 to September 6th, 2012 to oppose Senate Bill 1070—a state-specific measure to stop undocumented immigration across the Mexico/Arizona border and deport current undocumented residents. I situate the study in the larger context of Latino cultural citizenship. Combining a critical-incident interview technique and a rhetorically informed decision-making framework, I analyze Puente’s active construction and public circulation of argumentative appeals in relation to their decision-making that attempted to leverage Puente’s identity and membership to serve its constituents and to continue to direct wider public attention to SB 1070. Using a five-part framework to assess potential risks and benefits, the study documents the complexity of this decision-making. For instance, the study shows how Puente’s strategy of Barrio Defense Committees negotiated the tension between protecting the identification of local residents and publically protesting the injustices of immigration sanctions. It also highlights how a strategy to use member’s undocumented status as a point of publicity actively engaged tensions between the narratives Puente members wanted to present to the public about undocumented people and the images otherwise circulated. Behind these strategies and others like them is Puente’s persistent effort to re-frame immigration controversy. Findings are relevant to the study of Latino/a social movements, public-spheres scholarship, and action-research with subordinated rhetors.
In response to this gap, this project features the Puente Movement, a mixed-documentation-status grassroots organization in Phoenix, AZ. Specifically, I’ve analyzed this organization’s public efforts from April 23rd, 2010 to September 6th, 2012 to oppose Senate Bill 1070—a state-specific measure to stop undocumented immigration across the Mexico/Arizona border and deport current undocumented residents. I situate the study in the larger context of Latino cultural citizenship. Combining a critical-incident interview technique and a rhetorically informed decision-making framework, I analyze Puente’s active construction and public circulation of argumentative appeals in relation to their decision-making that attempted to leverage Puente’s identity and membership to serve its constituents and to continue to direct wider public attention to SB 1070. Using a five-part framework to assess potential risks and benefits, the study documents the complexity of this decision-making. For instance, the study shows how Puente’s strategy of Barrio Defense Committees negotiated the tension between protecting the identification of local residents and publically protesting the injustices of immigration sanctions. It also highlights how a strategy to use member’s undocumented status as a point of publicity actively engaged tensions between the narratives Puente members wanted to present to the public about undocumented people and the images otherwise circulated. Behind these strategies and others like them is Puente’s persistent effort to re-frame immigration controversy. Findings are relevant to the study of Latino/a social movements, public-spheres scholarship, and action-research with subordinated rhetors.
ContributorsOliver, Veronica (Author) / Long, Elenore (Committee member) / Miller, Keith (Committee member) / Bebout, Lee (Committee member) / Arizona State University (Publisher)
Created2015
Description
This study applies Relational Dialectic Theory to analyze the stepparent and stepchild relationship of one family. The data is documented in an autoethnography. Autoethnography is an approach to data collection in which the researcher’s own experience is the source of data, and the experience is studied to deepen understandings of social reality. This study highlights the complexity of the stepparent-stepchild relationship, the uncertainty surrounding the stepparent role, and identifies the dialectic tensions that exist within the stepparent-stepchild relationship. The dialectics identified by this study include: emotional-closeness-distance, past-present, autonomy connection, and parent-friend. The findings related to how these dialectic tensions emerge and are managed within stepparent-stepchild relationships have implications for stepparents and spouses of stepparents and for new parents and parents in traditional family structures.
ContributorsRoush, Krysti (Author) / Mean, Lindsay A (Thesis advisor) / Gaffney, Cynthia (Committee member) / Waldron, Vincent (Committee member) / Arizona State University (Publisher)
Created2015
Description
To ensure system integrity, robots need to proactively avoid any unwanted physical perturbation that may cause damage to the underlying hardware. In this thesis work, we investigate a machine learning approach that allows robots to anticipate impending physical perturbations from perceptual cues. In contrast to other approaches that require knowledge about sources of perturbation to be encoded before deployment, our method is based on experiential learning. Robots learn to associate visual cues with subsequent physical perturbations and contacts. In turn, these extracted visual cues are then used to predict potential future perturbations acting on the robot. To this end, we introduce a novel deep network architecture which combines multiple sub- networks for dealing with robot dynamics and perceptual input from the environment. We present a self-supervised approach for training the system that does not require any labeling of training data. Extensive experiments in a human-robot interaction task show that a robot can learn to predict physical contact by a human interaction partner without any prior information or labeling. Furthermore, the network is able to successfully predict physical contact from either depth stream input or traditional video input or using both modalities as input.
ContributorsSur, Indranil (Author) / Amor, Heni B (Thesis advisor) / Fainekos, Georgios (Committee member) / Yang, Yezhou (Committee member) / Arizona State University (Publisher)
Created2017
ContributorsLee, Ji Young (Performer) / ASU Library. Music Library (Publisher)
Created2019-04-06
Description
ABSTRACTThis dissertation addresses two pivotal challenges within the US technology industry: racial equity and the rise of artificial intelligence (AI). It investigates whether the integration of AI in human resources (HR) can foster inclusivity and diversity for Black women in the tech workforce. Despite numerous diversity initiatives, Black women account for less than 2% of the US tech workforce, symbolizing a persistent challenge. Furthermore, AI often perpetuates structural biases, magnifying workforce inequities. This dissertation employs intersectionality, responsible innovation, and algorithmic bias theories to amplify the voices of Black women. It poses three critical questions: 1) How have Black women's HR experiences influenced diversity issues in the tech industry? 2) How is AI in HR developed considering the experiences of Black women? 3) What measures can enhance the role of AI in HR to promote diversity without deepening inequalities? Key findings reveal that current HR practices do not adequately serve Black women, driven by competing corporate priorities. Solutions should concentrate on recruiting, developing, promoting, and retaining Black women. Black women acknowledge the potential of AI to either reinforce or mitigate biases, yet they express apprehension about the development and implementation of AI in HR, which often lacks Black women's input. For AI to facilitate positive diversity results, companies must actively involve Black women in its development. This entails understanding the problems Black women face, using insights to design AI that addresses these issues and supports Black women's success, and engaging Black women in the development and assessment of AI implementations in HR, thereby enhancing accountability for diversity outcomes.
ContributorsWhye, Barbara Hickman (Author) / Miller, Clark (Thesis advisor) / Richter, Jennifer (Committee member) / Scott, Kimberly (Committee member) / Arizona State University (Publisher)
Created2023
Description
A lack of public trust in governance institutions such as governments, federal agencies, and public health organizations limits national capacities to mitigate climate-related risks. Trustworthy sources of risk information are theorized to be more persuasive and more likely to motivate adaptive behaviors. Accordingly, this dissertation addresses relational and translational challenges of risk communication to support public health and safety by making climate science more accessible to communities at risk from extreme heat. This project developed and applied a theory-driven model of trust determination to understand how United States residents evaluate the trustworthiness of state governments and emergency management agencies. Using confirmatory factor analysis, a two-factor model of trustworthiness as self-reliability and source reliability was strongly empirically supported. This measurement model of trustworthiness was translated into experimental trustworthiness manipulations capable of creating statistically significant differences in perceptions of source reliability. The dissertation then tested the persuasive efficacy of trust-building risk messaging using randomized controlled trials, finding that when controlling for political ideology, message trust condition had a significant effect on attitudes toward extreme heat risk and preparedness as well as intentions to prepare for extreme heat events. Practical and theoretical implications are discussed.
ContributorsMattson, LD (Author) / Adame, Bradley (Thesis advisor) / Corman, Steven R (Committee member) / Eakin, Hallie (Committee member) / Arizona State University (Publisher)
Created2024
Description
In today’s world, artificial intelligence (AI) is increasingly becoming a part of our daily lives. For this integration to be successful, it’s essential that AI systems can effectively interact with humans. This means making the AI system’s behavior more understandable to users and allowing users to customize the system’s behavior to match their preferences. However, there are significant challenges associated with achieving this goal. One major challenge is that modern AI systems, which have shown great success, often make decisions based on learned representations. These representations, often acquired through deep learning techniques, are typically inscrutable to the users inhibiting explainability and customizability of the system. Additionally, since each user may have unique preferences and expertise, the interaction process must be tailored to each individual. This thesis addresses these challenges that arise in human-AI interaction scenarios, especially in cases where the AI system is tasked with solving sequential decision-making problems. This is achieved by introducing a framework that uses a symbolic interface to facilitate communication between humans and AI agents. This shared vocabulary acts as a bridge, enabling the AI agent to provide explanations in terms that are easy for humans to understand and allowing users to express their preferences using this common language. To address the need for personalization, the framework provides mechanisms that allow users to expand this shared vocabulary, enabling them to express their unique preferences effectively. Moreover, the AI systems are designed to take into account the user’s background knowledge when generating explanations tailored to their specific needs.
ContributorsSoni, Utkarsh (Author) / Kambhampati, Subbarao (Thesis advisor) / Baral, Chitta (Committee member) / Bryan, Chris (Committee member) / Liu, Huan (Committee member) / Arizona State University (Publisher)
Created2024