ISSEP-2026-06

GRANT ID#: ISSEP-2026-06

GRANT TITLE: Who Am I? Exploring Cultural Variation in Essentialist Self-Narratives through LLM Powered Machine Learning.

GRANTEE: Kennesaw State University.

PRIMARY INVESTIGATOR: Yian Xu.

CO-PRIMARY INVESTIGATORS: Da Hu, Yianxia Li, Ruosi Wang.

GRANT AMOUNT: USD $2,166

DURATION OF GRANT PROJECT: June 30, 2026 – May 1, 2027.

Description of the Project

Executive summary:

This interdisciplinary project investigates cultural variation in self-essentialist beliefs (SEBs), or the extent to which individuals view their identity as biologically grounded and fixed over time. While psychological essentialism has been widely examined in social perception, surprisingly little is known about how individuals essentialize their own identities, especially across cultural contexts. Integrating perspectives from philosophy, psychology, and computational modeling, we apply a mixed-method design to analyze self-narratives in the U.S. and China. Thematic coding and Large Language Models (LLMs) will be combined to detect essentialist self-framing. Based on previous cross-cultural work in self-construct and essentialism, we hypothesize that U.S. participants will express stronger SEBs than Chinese participants. Additionally, we will test whether a brief mindfulness intervention can reduce SEBs in a laboratory setting. This research advances existential psychology by informing how culture shapes the self through an essentialism lens, and offering novel, scalable strategies to support adaptive identity development.

Itemized budget:

Participant Compensation ($1766): To support data collection, we request $1066 to recruit online participants from the US ($4 compensation + $1.33 Prolific platform service fee/per participant x 200) and $700 for China ($3 compensation + $0.5 Credamo platform service fee/per participant x 200) for the completion of Study 1.

API Fee ($400): To support the large-scale text analysis of self-narrative data, we request a small budget ($400) for natural language processing services using LLM APIs, such as OpenRouter API or OpenAI API, to conduct text classification, semantic pattern detection, and essentialist framing analysis.

The total amount approved for this project is USD $2,166.