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

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-of-the-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 text-genealogical 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.

When language of instruction and language of application differ: Cognitive costs of bilingual mathematics learning

Bilingual education programs implicitly assume that the acquired knowledge is represented in a language-independent way. This assumption, however, stands in strong contrast to research findings showing that information may be represented in a way closely tied to the specific language of instruction and learning. The present study aims to examine whether and to which extent cognitive costs appear during arithmetic learning when language of instruction and language of retrieving differ. Thirty-nine high school students participating in a bilingual education program underwent a four-day training on multiplication and subtraction problems in one language (German or French), followed by a test session in which they had to solve trained as well as untrained problems in both languages. We found that cognitive costs related to language switching appeared for both arithmetic operations. Implications of our findings are discussed with respect to bilingual education as well as to cognitive mechanisms underlying different arithmetic operations.

An overview of positive and negative effects of gender-fair language use

The basic principle of gender-fair language is symmetric linguistic treatment of women and men. Depending on the structure of the respective language, two principle strategies can be deployed to make a language gender-fair. In languages with few gender-differentiating forms, such as English, there is a tendency towards neutralization. Here, gender-unmarked forms such as police officer or chairperson are used to substitute the male-biased policeman or chairman. The second strategy, feminization, implies that feminine forms of human nouns are used more frequently and systematically to make female referents visible.Since the 1970s, gender-fair language has been suggested, if not prescribed, for both scientific and official texts and its positive effects are widely documented. The use of gender-fair language increases the cognitive availability of feminine exemplars. Also in an applied context women responding to job advertisements formulated in gender-fair language feel more motivated to apply for the position. However, "side effects" of gender-fair language have also been observed: For instance, women referred to with a gender-fair title (e.g. chairperson) were evaluated as lower in status than women referred to with a masculine generic (e.g. chairman). Similarily, social initiatives framed with the use of gender-fair language were evaluated less-favourably than initiatives using traditional language. This presentation presents the gender-fair language use in the framework of a social dilemma. In order to protect themselves (or initiatives they stand for) from being ascribed incompetence or a lower status, women may avoid feminine forms and thus contribute to the perpetuation of gender-unfair language, which may be detrimental for women in general. Raising awareness for this social concern, and framing it both in terms of group and individual interest can direct the discussion about gender-fair language into a broader perspective of gender equality.

Gender-fair Language Changes the Social Perception of Professional Groups: The Case of German and Italian.

Gender-fair language, including women and men, such as word pairs has a substantial impact on the mental representation, as a large body of studies have shown. When using exclusively the masculine form as a generic, women are mentally significantly less represented than men. Word pairs, however, lead to a higher cognitive inclusion of women. Surprisingly little research has been conducted to understand how the perception of professional groups is affected by gender-fair language. Providing evidence from an Italian-Austrian cross-cultural study with over 400 participants, we argue that gender-fair language impacts the perception of professional groups, in terms of perceived gender-typicality, number of women and men assumed for a profession, social status and average income. Results hint at a pervasive pay-off: on the one hand, gender-fair language seems to boost the mental representations in favor of women and professions are perceived as being rather gender-neutral. On the other hand professional groups are assigned lower salary and social status with word pairs. Implications of results are discussed.