Bias in the basics: a multiloop framework for auditing foundational medical texts through an equity lens

This article critically examines the exclusionary dimensions faced by the marginalized transgender, diverse sexual orientation, gender identity, and expression (SOGIESC), and disability community in foundational medical physiology textbooks. A literature review of both international and Indian textbooks was conducted to identify stereotypes and other forms of discriminatory language. These linguistic choices are not neutral: they shape the attitudes of future health care professionals and contribute to the systemic inaccessibility of care for these communities. Our analysis revealed a pervasive presence of exclusionary terms and implicit biases that we feel perpetuate stigma, erase identities, and normalize marginalization of these population. Recognizing that merely correcting isolated terms is insufficient, we propose an Inclusive Language Textbook Audit Tool grounded in a multiloop learning framework. This tool moves from surface-level corrections (single-loop learning) to questioning underlying assumptions (double-loop learning) and transforming the cultural and institutional contexts that sustain exclusion (triple-loop learning). Embedding this framework in textbook audits offers a systematic path from tokenistic edits to systemic inclusion. We call on textbook authors, publishers, and educators to adopt this tool to ensure linguistic equity in medical education. Revising foundational texts is not only a matter of accuracy; it is an ethical imperative to cultivate a generation of health care professionals committed to equity, dignity, and justice for all patients.<b>NEW & NOTEWORTHY</b> A preliminary analysis of foundational medical textbooks for possible exclusionary or invalidating microaggressions and a proposed multiloop framework for auditing foundational medical texts through an equity lens are presented.