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Reflections on inductive thematic saturation as a potential metric for measuring the validity of an inductive thematic analysis with LLMs

Author

Listed:
  • Stefano De Paoli

    (Abertay University)

  • Walter S. Mathis

    (Yale School of Medicine)

Abstract

This paper presents a set of reflections on saturation and the use of Large Language Models (LLMs) for performing Thematic Analysis (TA). The paper suggests that initial thematic saturation (ITS) could be used as a metric to assess part of the transactional validity of TA with LLM, focusing on the initial coding. The paper presents the initial coding of two datasets of different sizes, and it reflects on how the LLM reaches some form of analytical saturation during the coding. The procedure proposed in this work leads to the creation of two codebooks, one comprising the total cumulative initial codes and the other the total unique codes. The paper proposes a metric to synthetically measure ITS using a simple mathematical calculation employing the ratio between slopes of the unique and total codes. The paper contributes to the initial body of work exploring how to perform qualitative analysis with LLMs.

Suggested Citation

  • Stefano De Paoli & Walter S. Mathis, 2025. "Reflections on inductive thematic saturation as a potential metric for measuring the validity of an inductive thematic analysis with LLMs," Quality & Quantity: International Journal of Methodology, Springer, vol. 59(1), pages 683-709, February.
    • Handle: RePEc:spr:qualqt:v:59:y:2025:i:1:d:10.1007_s11135-024-01950-6
    DOI: 10.1007/s11135-024-01950-6
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