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Snow on the Tongue

2026 · Journal of Edugeography · 0 citations

TL;DR

The work argues that autoethnography functions not merely as a qualitative method but as a phenomenological mode of being and knowing that safeguards the primacy of anthropic subjectivity against machinic imitation.

Abstract

This essay contributes to contemporary debates on artificial intelligence and qualitative inquiry by reflecting on what I argue are originary and epistemological limitations of AI. It interrogates these limits through a comparative engagement of AI-generated narratives and researcher-authored autoethnographic vignettes. While algorithms can reproduce structure and stylistic form, they remain devoid of our ordinary, specific realities, not archived on the internet, our lived memory and reflexive consciousness, which are the foundations of authentic autoethnographic practice. Grounded in embodied experiences of memory, materiality, and cultural belonging, the study demonstrates how autoethnography resists algorithmic generalization by foregrounding specificity, and situated truth. Through a comparative analysis of epistemic parameters (agency, data, methods, tools, techniques, results, origination, and growth), it delineates the ontological gulf separating computational synthesis from human meaning-making. Pedagogical experiments in a writing classroom further illustrate how students discern the irreplaceable value of specific lived knowledge when confronted with AI’s simulations. Ultimately, the work argues that autoethnography functions not merely as a qualitative method but as a phenomenological mode of being and knowing that safeguards the primacy of anthropic subjectivity against machinic imitation. In an age when digital systems increasingly simulate human expression, the findings affirm autoethnography as an epistemological site of resistance: reflexive and irreducibly human.

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