Developing a Guideline for the Labovian-Structural Analysis of Oral Narratives in Japanese

2026-03-31

AI Summary

This study addresses the lack of guidelines for applying the Labovian narrative analysis framework to Japanese spoken discourse, whose grammatical and pragmatic conventions differ markedly from English, and for which annotated datasets have been limited to English. It presents the first systematic adaptation of the Labovian model to Japanese, introducing clause segmentation rules tailored to Japanese constructions that preserve all six canonical narrative components while expanding the range of analyzable clauses and narrative types. Through qualitative content analysis, structural annotation, and iterative hermeneutic cycles, intercoder reliability was assessed using Fleiss’ kappa and Krippendorff’s alpha. Results demonstrate high agreement in clause segmentation (κ = 0.80) and moderate agreement in structural classification (α = 0.41 and 0.45), slightly surpassing prior efforts and substantially enhancing the cross-linguistic applicability of the Labovian framework.

Abstract

Narrative analysis is a cornerstone of qualitative research. One leading approach is the Labovian model, but its application is labor-intensive, requiring a holistic, recursive interpretive process that moves back and forth between individual parts of the transcript and the transcript as a whole. Existing Labovian datasets are available only in English, which differs markedly from Japanese in terms of grammar and discourse conventions. To address this gap, we introduce the first systematic guidelines for Labovian narrative analysis of Japanese narrative data. Our guidelines retain all six Labovian categories and extend the framework by providing explicit rules for clause segmentation tailored to Japanese constructions. In addition, our guidelines cover a broader range of clause types and narrative types. Using these guidelines, annotators achieved high agreement in clause segmentation (Fleiss' kappa = 0.80) and moderate agreement in two structural classification tasks (Krippendorff's alpha = 0.41 and 0.45, respectively), one of which is slightly higher than that found in prior work despite the use of finer-grained distinctions. This paper describes the Labovian model, the proposed guidelines, the annotation process, and their utility. It concludes by discussing the challenges encountered during the annotation process and the prospects for developing a larger dataset for structural narrative analysis in Japanese qualitative research.

Problem

• Labovian narrative analysis
• Japanese oral narratives
• qualitative research
• cross-linguistic adaptation
• narrative structure

Innovation

• Labovian narrative analysis
• Japanese oral narratives
• clause segmentation
• annotation guidelines
• structural narrative analysis