This thesis critically examines the dominant narrative constructed in US-based news media about the United States’ institutions of violence, the Black Lives Matter movement (BLM), and the Immigrant Rights (IR) movements. Engaging multiple disciplines across the social science that engage race, immigration, the media, and American politics, the thesis situates the media’s role in racial injustice and nation-state violence against the Black and Immigrant communities. White Supremacy is deeply part of the United States' past and present, and the news media plays a critical role in capturing and framing the challenges to entrenched systemic racism led by social movement activism. The news media is situated in a powerful public position, capable of leading or supporting social justice work as well as further entrenching systems of oppression and injustice. This thesis explores whether the media challenges or reinforces the nation-state’s violent and racist institutions and practices. To operationalize the empirical work, the thesis asks how the news media (de)centers and (de)legitimizes social movements, impacted communities, and the nation-state when reporting on BLM and IR. Two original datasets of 8,742 news articles (for BLM) and 3,372 news articles (for IR), covering 2013 to 2023, are analyzed using machine learning techniques like named entity recognition and semantic networks of text, along with qualitative content analysis of select months as critical case studies. The thesis reveals how news media serves as a governance tool capable of stifling dissent by decentering the racial injustices that legitimize movement tactics and simultaneously centering partisan politics and the nation-state.

Smart cities surveil through ubiquitous and intrusive data collection via networked sensors. Smart city efforts are also frequently imagined as primarily top-down and male visions of the future in service of economic benefit. The smart campus presents a new dimension of smart city urbanism as an identified gap in literature. In the following dissertation, I trace sociotechnical imaginaries of a large R1 research university as a smart campus, using an Internet of Things (IoT) pole deployment as a case study. My primary research questions consider the localized co-production and imagining of the smart campus and its implications, explored through four research approaches: (1) interviews with designers, (2) archival review (3) qualitative analysis of visual case study artifacts, and (4) student interviews supported with observational study. Key findings include parallels to existing research on smart city imaginaries based in technosolutionistic, male-dominated, science fiction visions of the future. There is a reproduction of Big Data narratives of efficiency, and top-down implementation of visions extended to the smart campus. I also identify tensions in narratives of purpose, between privacy and surveillance, and digital citizenship dynamics. I employ an intersectional feminist technoscience lens rooted in Science and Technology Studies (STS), as well as notions of data justice and data power, from Critical Data Studies (CDS), and narrative inquiry methods to examine the stabilization and legitimization of these smart campus narratives. I also incorporate analysis of gender, power, and racialized surveillance relevant to carceral imaginaries in the smart campus. With support from narrative inquiry methods, I explore rhetoric underpinning the smart campus imaginary, specifically around promises of democracy, egalitarianism, and techno-utopias, tracing influences in national geopolitics, science fiction, and Silicon Valley ideology. This work contributes to existing knowledge on sociotechnical imaginaries of the smart city, documenting a genealogy as it is embedded into the urban space of the smart campus, and presenting an empirically grounded study of smart cities. This work also contributes to understandings of data as power, data assemblages, and data narratives, and to feminist technoscience literature on smart cities and the smart campus in the fields of CDS and STS.

Music is an integral part of a community's identity, and music streaming has changed the way in which people interact with popular music as a whole. While significant research has been done regarding how streaming services have impacted the way users engage with music, little has been done to account for how streaming has changed the creation of new music. Additionally, globalization in music results in unique hybrid genres rather than complete adoption of global culture, making it hard to measure the global impact on regional sounds, as chart diversity alone cannot account for this unique interaction. This research addresses this gap in literature by utilizing Spotify’s audio features to analyze regional popular music characteristics from 2010 through 2020 using the Top 100 tracks from the global, Korean, and Japanese charts. It then observes whether the chart data demonstrates a convergence or divergence in relation to the musical attributes of global popular music and the growth of music streaming, and if it is reflecting a globalization effect. The results suggest that local artists reflect global trends in already globalized markets, and that streaming may be having a heterogenization effect on popular music. Additionally, the data also suggests that observing the musical characteristics of a region may be able to measure how globalized a region's music culture is, allowing for the observation of globalization beyond looking at chart diversity and instead observing the music characteristics of domestic artists.

Drawing from feminist scholarship, this thesis re-articulates the concept of “liberal bargain” to makes sense of political parties, race and class in the United States. Specifically, the concept of “partisan liberal bargain” is developed in this thesis to capture how the Democratic party's behavior strategically de-centers race in favor of class discourse. These bargains, the thesis argues, reinforces how liberal orders and racial orders operate together to marginalize both racial and class-based minorities. Employing discourse analysis of over 1,000 news articles, the thesis reveals and unpacks bargains occurring during the 2016 and 2020 Democratic primaries, with a focus on three policy areas where racial justice is intimately and historically embedded: 1) criminal justice, 2) health care, and 3) environmental policy. Discourse analysis empirically captures the thesis’ concept of partisan liberal bargains, showing a prominent lack of concrete or substantial centering of race and strong centering of class and neoliberal discourse. Thus, despite the Democratic party’s strong African American voting bloc and association as the party of race and diversity, this thesis and the concept of partisan liberal bargains shows that racial justice is avoided and even delegitimized in party politics.