RUEI-JIE (RACHEL) CHANG

I am an M.A. student in Digital Studies of Language, Culture, and History at the University of Chicago. My research leverages computational methods to interrogate questions of text, medium, and society, grounded in careful examination of material specificity and the epistemologies of computational systems: how their architectures and training assumptions organize knowledge, structure interpretation, and reproduce dominant narratives. This inquiry doesn't stop at analysis. I also explore ways to build new architectures and fine-tune models to reshape LLM behavior, from better reflecting low-resource data to shifting default outputs, intervening in what these systems render statistically hegemonic and countering that with more accessible technology.

Methodologically, I combine close reading with computational analysis. I build and curate structured textual corpora, design metadata schemas, and apply machine learning and other quantitative methods to trace conceptual shifts and patterns in dialogue with literary studies.

My current working thesis develops a computational framework for investigating what distinguishes prize-winning from non-winning literary fiction across five major English-language prizes, treating prize outcomes not as transparent indicators of literary quality but as acts of institutional consecration. I build a full-text corpus and apply deep learning and fine-tuning methods to investigate the sociological and literary patterns behind how literary prestige and value are evaluated across time.