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This quantitative study examines preservice teacher (PST) motivations to enter the profession. We use a natural language processing approach to categorize into topical groups roughly 2,800 essay responses to the prompt, “Explain why you decided to become a teacher.” We identify 15 topics such as wanting to help others or family connection to teaching. We then connect these codes to PST demographics (race, family income, academic qualifications) to examine if there are relationships with motivational codes and background characteristics. Finally, we examine whether these codes are associated with labor market outcomes of being employed as K–12 public school teacher in Texas and early-career retention. Findings have implications for teacher recruitment to improve potential pipeline shortages.