Academic Writing
This page features two academic research papers completed for the course Cluster: Data, Justice, and Society. In this class, we explore the ethical dimensions of data and technology in everyday life. We examine how data is collected, often invisibly, and how it functions as a tool of surveillance, shaping our social experiences, identities, and opportunities. Through concrete case studies, we critically analyze the role of algorithms, predictive models, and artificial intelligence in reinforcing or challenging systems of power. The course encourages us to rethink how data can be used responsibly and equitably in a data-driven society.
Uncovering the Missing Data in Corporal Punishment
This paper explores the critical gap in data on corporal punishment (CP), emphasizing the lack of qualitative information from victims’ perspectives. While existing research often relies on parental reports and recollections, these sources are biased and incomplete. Cultural stigma, family pressure, and feelings of shame often silence victims, further contributing to the absence of detailed accounts. The paper argues that collecting first-hand narratives is essential to understanding the psychological harm caused by CP. It also highlights the ethical challenge of minimizing harm to victims during data collection, calling for empathetic research methods.
Unveiling Bias in the Getty Vocabularies
This paper critiques the Getty Vocabularies, a set of databases used in the visual arts, for reinforcing Western biases despite claims of inclusivity. It examines how each of the three main databases (TGN, ULAN, and AAT) reflects Eurocentric perspectives through naming conventions, categorization, and omissions, particularly of non-Western artists and cultural concepts. The paper argues that these practices contribute to cultural marginalization and proposes solutions such as incorporating diverse perspectives, revising classification systems, and supporting cross-cultural research.