Narrative Continuity and Transformation in the Gog and Magog Tradition: A Human-in-the-Loop Computational Humanities Study

Abstract

This pilot study investigates long-term continuity and transformation in the Gog and Magog tradition using a Human-in-the-Loop computational humanities approach. The objective was to evaluate the feasibility and applicability of a standardized narrative coding framework for comparative analysis of long-duration cultural traditions. A purposive corpus of ten historically influential sources spanning approximately twenty-six centuries—from Ezekiel to nineteenth-century Protestant interpretations—was analyzed using a Narrative Unit framework consisting of five components: Actor, Threat, Cause, Solution, and Outcome. Artificial intelligence was employed as a research support tool for information extraction, textual comparison, consistency checking, and preliminary coding suggestions, while all substantive decisions regarding source selection, ontology development, coding, validation, and interpretation remained under direct researcher supervision. The analysis demonstrated that all ten sources could be represented using the same Actor–Threat–Cause–Solution–Outcome architecture, with all five components identifiable across the entire corpus. At the same time, substantial variation was observed in individual narrative components. The Actor category displayed the greatest diversity, ranging from specific historical rulers to eschatological enemies, frontier peoples, historically identified populations, and modern geopolitical actors, whereas Threat and Outcome exhibited comparatively lower variability. The findings suggest that continuity within the Gog and Magog tradition may depend less on preservation of specific historical content than on the persistence of recurring narrative functions. The corpus also exhibits a pattern of narrative layering in which newly introduced interpretative elements coexist with inherited narrative structures. Preliminary framework validation further indicated that the Narrative Unit model was sufficiently flexible to accommodate substantial historical variation while maintaining a consistent analytical structure. Although exploratory and limited in scope, the study demonstrates the potential of Human-in-the-Loop narrative coding for investigating long-term cultural transmission and transformation and provides a transparent and reproducible framework for comparative analysis of historical narratives across extended temporal scales.

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