A Statistical Exploration of Text Partition Into Constituents: The Case of the Priestly Source in the Books of Genesis and Exodus
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Abstract (arXiv)
We present a pipeline for a statistical textual exploration, offering a stylometry-based explanation and statistical validation of a hypothesized partition of a text. Given a parameterization of the text, our pipeline: (1) detects literary features yielding the optimal overlap between the hypothesized and unsupervised partitions, (2) performs a hypothesis-testing analysis to quantify the statistical significance of the optimal overlap, while conserving implicit correlations between units of text that are more likely to be grouped, and (3) extracts and quantifies the importance of features most responsible for the classification, estimates their statistical stability and cluster-wise abundance. We apply our pipeline to the first two books in the Bible, where one stylistic component stands out in the eyes of biblical scholars, namely, the Priestly component. We identify and explore statistically significant stylistic differences between the Priestly and non-Priestly components.
Key facts. Cited by 3 papers in the map (data through 14 Oct 2026). Builds on 4 of its 75 references that are in the map. First posted on arXiv 3 May 2023.
Builds on
4 of 75 references.
References · 4
- 2021On Calibration and Out-of-domain Generalizationcited by 134
- 2020Artificial intelligence based writer identification generates new evidence for the unknown scribes of the Dead Sea Scrolls exemplified by the Great Isaiah Scroll (1QIsaa)cited by 8
- 2022Introducing BEREL: BERT Embeddings for Rabbinic-Encoded Languagecited by 3
- 2015The Hebrew Bible as Data: Laboratory - Sharing - Experiencescited by 1
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Citing papers per year: 2024: 2; 2025: 1.
3 papers.
- 2024Critical biblical studies via word frequency analysis: unveiling text authorshipcited by 2
- 2024Estimating the Influence of Sequentially Correlated Literary Properties in Textual Classification: A Data-Centric Hypothesis-Testing Approachcited by 0
- 2025An Information-Theoretic Approach to Identifying Formulaic Clusters in Textual Datacited by 0
- 2025An Information-Theoretic Approach to Identifying Formulaic Clusters in Textual Data10 Mar 2025
- 2024Estimating the Influence of Sequentially Correlated Literary Properties in Textual Classification: A Data-Centric Hypothesis-Testing Approach7 Nov 2024
- 2024Critical biblical studies via word frequency analysis: unveiling text authorship24 Oct 2024