Reflections on Inductive Thematic Saturation as a potential metric for
  measuring the validity of an inductive Thematic Analysis with LLMs
Stefano De Paoli Walter Stan Mathis
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 cumulative codes and unique codes. The paper
contributes to the initial body of work exploring how to perform qualitative
analysis with LLMs.