Article Now Available on Textual Layers in Codex Bezae

I recently published an article on textual layers in Codex Bezae found here:

Analyzing Textual Stratification in the Greek Gospel Text of Codex Bezae: Comparing Three Approaches to Layer Extraction in John 4,1–42 (2015)

It is one thing of course to suggest that Codex Bezae attests a mixed text with readings from multiple sources combined into its final text. But it is quite another matter to identify and extract these sources in a systematic and repeatable way. The basic method was proposed by Michael Holmes in a 1996 essay (“Codex Bezae as a Recension of the Gospels”). Holmes then successfully demonstrated this method on the text of Matthew. The consistency of his results speaks for itself.

My goal in this paper is to identify more accurate and efficient techniques to extract Bezae’s layers based on Holmes key insights, namely

  1. That the same witnesses are often found together in support of distinct subsets of Bezae’s readings and
  2. That any group of readings supported by essentially the same selection of witnesses represents a ‘layer,’ which we can treat as a distinct element of Bezae’s tradition.

The motivation is to repeat Holmes’ proof-of-concept on the text of Matthew with other full-scale applications in other parts of Bezae. The article uses complete IGNTP transcriptions for a small part of John.

From the abstract:

It has been suggested that Codex Bezae’s Greek column (D) attests a stratified text, consisting of distinct layers of readings that reflect its historical contact with different traditions. Using John 4:1-42 as a case study, this paper compares three methods of partitioning D’s readings by layer: first, Holmes’ (1996) method based on patterns of agreement; second, a proposed method based on the levels of D’s readings in local genealogies; and, third, a proposed method based on multivariate clustering.

The result shows that Bezae’s readings tend to bifurcate cleanly between two main layers, a mainstream layer and an Old Latin layer.

What do you think?