The effects of weighting kinds of variants

Spencer, Matthew; Mooney, Linne R.; Barbrook, Adrian C.; Bordalejo, Barbara; Howe, Christopher; Robinson, Peter

doi:10.1075/z.125.13spe

Cited by 9 publications

(6 citation statements)

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“…a widely available lexicon that includes entries for the headwords in question) and can therefore not be counted as genealogical. Our findings broadly support the conclusions reached by Spencer et al (2004b) and suggest that even the most trivial changes, taken in aggregate, have some text-genealogical significance that should not be discounted.…”

Section: 'Significant' Variation In Transmitted Textssupporting

confidence: 88%

“…This example is taken from the 'Parzival' artificial tradition (Spencer et al 2004b); the majority of witnesses have the reading 'clash', whereas two have 'clas' and two have 'dash'. The stemma displayed is the true stemma for the tradition; our solver has detected that the variation in the witnesses does follow the stemma.…”

Section: Analysis Of a Stemma Graphmentioning

confidence: 99%

“…1 See (Salemans 2000) and (Spencer et al 2004b) for opposing opinions. 2 The Heinrichi tradition could arguably be an exception; its creators hoped that the non-standard spelling of Old Finnish and the relative unfamiliarity of the language would simulate diachronic shifts.…”

Section: Notesmentioning

confidence: 99%

“…Only a few empirical studies have ever been carried out, each limited to the study of a single text (e.g. Schmid 2004;Schøsler 2004;Spencer et al 2004b), but a broader study has not yet been attempted. A quarter-century ago, Timpanaro observed that it was not practically feasible to collect statistics on the genealogical significance of many variations across a wide range of texts.…”

Section: Introductionmentioning

confidence: 99%

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Beyond the tree of texts: Building an empirical model of scribal variation through graph analysis of texts and stemmata

Andrews

Macé

2013

Literary and Linguistic Computing

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Stemmatology, or the reconstruction of the transmission history of texts, is a field that stands particularly to gain from digital methods. Many scholars already take stemmatic approaches that rely heavily on computational analysis of the collated text (e.g. Robinson and O'Hara 1996;Salemans 2000;Heikkilä 2005;Windram et al. 2008 among many others). Although there is great value in computationally assisted stemmatology, providing as it does a reproducible result and allowing access to the relevant methodological process in related fields such as evolutionary biology, computational stemmatics is not without its critics. The current state-ofthe-art effectively forces scholars to choose between a preconceived judgment of the significance of textual differences (the Lachmannian or neo-Lachmannian approach, and the weighted phylogenetic approach) or to make no judgment at all (the unweighted phylogenetic approach). Some basis for judgment of the significance of variation is sorely needed for medieval text criticism in particular. By this, we mean that there is a need for a statistical empirical profile of the textgenealogical significance of the different sorts of variation in different sorts of medieval texts. The rules that apply to copies of Greek and Latin classics may not apply to copies of medieval Dutch story collections; the practices of copying authoritative texts such as the Bible will most likely have been different from the practices of copying the Lives of local saints and other commonly adapted texts. It is nevertheless imperative that we have a consistent, flexible, and analytically tractable model for capturing these phenomena of transmission. In this article, we present a computational model that captures most of the phenomena of text variation, and a method for analysis of one or more stemma hypotheses against the variation model. We apply this method to three 'artificial traditions' (i.e. texts copied under laboratory conditions by scholars to study the properties of text variation) and four genuine medieval traditions whose transmission history is known or deduced in varying degrees. Although our findings are necessarily limited by the small number of texts at our disposal, we demonstrate here some of the wide variety of calculations that can be made using our model. Certain of our results call sharply into question the utility of excluding 'trivial' variation such as orthographic and spelling changes from stemmatic analysis.

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Section: 'Significant' Variation In Transmitted Textssupporting

confidence: 88%

Section: Analysis Of a Stemma Graphmentioning

confidence: 99%

Section: Notesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Beyond the tree of texts: Building an empirical model of scribal variation through graph analysis of texts and stemmata

Andrews

Macé

2013

Literary and Linguistic Computing

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“…As d is symmetric, this matrix is also symmetric, besides it has only zeros in its diagonal (the distance between any text and itself being zero), thus only the subspace ℝ n(n-1)/2 is relevant.12 This approach sequentially groups taxa by joining the two most similar ones. Details with an example in the Parvum Lexicon Stemmatologicum: https://www.sglp.uzh.ch/static/MLS/stemmatology/Neighbour-joining_229149983.html.13 https://evolution.gs.washington.edu/phylip/doc/main.html.14 Possibly also substitution and transposition: this is known as the Damerau-Levenshtein distance.15Spencer et al 2004 studied the influence of manual weighting in a Middle English text (Lydgate's Kings of England). They weighted omissions or changes in meaning strongly but did not use traditional significant errors.…”

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confidence: 99%

On the Usability of Available Digital Tools for Reconstructive TextualEditing

Roelli

2023

Journal of Data Mining &Amp; Digital Humanities

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This article reviews some of the digital tools currently available for reconstructive textual editing. First the main idea of reconstructive textual editing is summarised, then its steps amenable to algorithmic description are compared to similar ones in evolutionary biology. The the unequal ability of its variants to be relationship revealing is an important difference between the two fields. Two Latin texts with a complicated transmission are then introduced and used as data to illustrate some available tools in praxi. The main focus is on stemma reconstruction. Some steps of the process can already be largely automated, especially collating texts. On the whole it is found that tree-constructing software is of little help in the case of the medical text Liber Aurelii, whereas it is somewhat more helpful for Plato of Tivoli’s translation of the Centiloquium. In a concluding part, the main problems for algorithmic approaches to the stemma are discussed: incomplete witnesses leading to only partly overlapping text samples, contamination in some witnesses, and rooting the automatically generated trees.

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Article: Collating Texts Using Progressive Multiple Alignment

Spencer

Howe

2004

Computers and the Humanities

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To reconstruct a stemma or do any other kind of statistical analysis of a text tradition, one needs accurate data on the variants occurring at each location in each witness. These data are usually obtained from computer collation programs. Existing programs either collate every witness against a base text or divide all texts up into segments as long as the longest variant phrase at each point. These methods do not give ideal data for stemma reconstruction. We describe a better collation algorithm (progressive multiple alignment) that collates all witnesses word by word without a base text, adding groups of witnesses one at a time, starting with the most closely related pair.

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The effects of weighting kinds of variants

Cited by 9 publications

References 0 publications

Beyond the tree of texts: Building an empirical model of scribal variation through graph analysis of texts and stemmata

Beyond the tree of texts: Building an empirical model of scribal variation through graph analysis of texts and stemmata

On the Usability of Available Digital Tools for Reconstructive TextualEditing

Article: Collating Texts Using Progressive Multiple Alignment

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