This dissertation explores the underrepresentation of racially minoritized students in elite academic spaces by considering the New York City Specialized High Schools and the controversies surrounding their exam-based enrollment process. It does so by examining the arguments marshalled both for and against the use of the SHSAT entrance exam in order to better understand the role of public discourse in maintaining educational systems implicated in the reproduction of racial inequities.
Using a large-scale dataset of social media posts, this study employs a multi-tiered, mixed-methods approach to critical discourse analysis to investigate the linguistic and rhetorical contours of these debates, including the extent to which they rely on racially charged narratives around intelligence, ability, and merit.
This methodological strategy incorporates topic modeling, corpus linguistics, and lexical analysis to navigate the breadth and complexity of the SHSAT discourse, while also providing insight into the way that emerging forms of participatory engagement, like social media, are transforming the landscape of equity-oriented education reform.
This study finds that race is a central preoccupation of stakeholders on either side of the SHSAT debate, and that patterns of racialized discourse align closely to the articulation of specific policy objectives. The findings of this analysis also suggest that while social media has the potential to expand discursive access and foster dialogue, it can also amplify existing ideological divides and further polarize policy debates. The dualities of social media thus highlight the need for policymakers, researchers, and media consumers alike to critically evaluate the ways that these digital platforms are used to engage with policy and public discourse, as well as the equity implications of their evolving relationship.
| Identifer | oai:union.ndltd.org:columbia.edu/oai:academiccommons.columbia.edu:10.7916/ep3b-b408 |
| Date | January 2024 |
| Creators | Moftah, Linda |
| Source Sets | Columbia University |
| Language | English |
| Detected Language | English |
| Type | Theses |
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