walternmoss/Quantifying-the-Philosophical-Signatures-of-Marcus-Aurelius-and-Epictetus: Quantifying the Philosophical Signatures of Marcus Aurelius and Epictetus using Lexical Diversity and LLM Classifiers

Abstract

This repository contains the complete supplementary materials, computational pipelines, datasets, and statistical validation files supporting the manuscript: "Quantifying the Philosophical Signatures of Marcus Aurelius and Epictetus using Lexical Diversity and LLM Classifiers" (Walter N. Moss). Repository Files and Descriptions Supplementary_File_S1.zip: Compressed archive containing the complete Python 3.11 computational pipeline. Includes scripts for data acquisition from the LAGT corpus and LSJ dictionary, text preprocessing and Unicode normalization, lexical richness metrics (TTR, Guiraud's R, hapax legomena), relative frequency difference calculations, vector visualization plotting, and the LLM classification pipeline. A detailed README.md and requirements.txt are included for full technical reproducibility. Supplementary_File_S2.tsv: Comprehensive master lexical comparison table between Marcus Aurelius (Meditations) and Epictetus (Discourses and Enchiridion). This tab-separated dataset includes unique lemmata, raw token counts, size-normalized relative frequencies (per 10,000 words), delta-RF values, and standardized LSJ definitions. Supplementary_File_S3.pdf: Supplemental statistical visualizations, including Kernel Density Estimation (KDE) relative frequency overlap curves with annotated overlap coefficients, as well as frequency histograms and statistical summaries (mean, standard deviation, and mean absolute deviation) for both unfiltered and verb-filtered datasets. Supplementary_File_S4.zip: Compressed archive containing the sentence-level thematic analysis dataset across 5,371 sentences extracted from both corpora. Each record provides the original Ancient Greek sentence, natural language English translation, target philosophical stem, and categorical thematic tag (Ethics, Physics, or Logic) with the qualitative rationale provided by the generative AI model. Supplementary_File_S5.zip: Thematic classification validation dataset and inter-annotator agreement package evaluating an independent random sample of 100 sentences (seed = 42). Contains: Supplementary_File_S5.csv: Complete audit table with Greek text, translations, automated LLM tags, model rationales, blind human ratings, adjudicated human ratings, and qualitative evaluator notes. validation_kappa_report.txt: Statistical verification report detailing 4x4 confusion matrices, observed agreement (82.0% blind; 93.0% adjudicated), expected chance agreement, Cohen’s Kappa (κ = 0.668 blind; κ = 0.855 adjudicated), and itemized persistent discrepancies. calculate_kappa.py: Standalone Python script to reproduce all agreement statistics and export the validation report. Supplementary_File_S6.xlsx: Excel workbook containing normalized co-occurrence matrices for 19 key Stoic technical terms across Marcus Aurelius and Epictetus. Values are reported as normalized observations per 1,000 sentences alongside p-values derived from Pearson's Chi-square tests of independence. Code and Environment All scripts are written for Python 3.11. The full codebase, NLP pipelines, and validation tools are actively maintained on GitHub: https://github.com/walternmoss/Quantifying-the-Philosophical-Signatures-of-Marcus-Aurelius-and-Epictetus