In 2021 I joined the DISSINET project as an associate researcher in order to apply the project’s data model to one of the most intriguing late medieval heresy trials, Petrus Zwicker’s inquisition against Waldensians in Stettin. In the Stettin trials, the deponents came from the dioceses of Cammin, Brandenburg and Poznań. The trials took place in two stages: November 1392 to March 1393 and February to March 1394. In total, there were ca. 455 deponents, out of which we still have 195 extant protocols. In addition to a few thousand Waldensian followers and their relatives, almost every deposition recounts clerical witnesses to the hearing. Therefore, the Stettin protocols are an excellent source for both dissident and inquisitorial networks.
The data in my analysis is based on the regesta edition of the Stettin protocols in Dietrich Kurze, ed., Quellen zur Ketzergeschichte Brandenburgs und Pommerns (Berlin: de Gruyter, 1975). Kurze’s edition provides a summary of each protocol, with all the names and information relevant for recognising the individuals as well for understanding the questions, dates and statements important for Brandenburgian-Pomeranian Waldensians. However, many of the routine-like answers, such that the deponent did not believe in the invocation of saints but honoured the Virgin Mary, are not recorded in Kurze’s edition.
The edition’s strength is that it gives a structured overview of all the persons included. It is thus a very good source for Social Network Analysis. However, Kurze’s editorial choices mean that the edition is of limited use for those interested in the interaction between the inquisitor and the deponent, or in Waldensian lived religion, both topics of interest in the DISSINET project. Therefore, there was a choice to be made: either to model the depositions in full from the original protocols, or make a social network data table out of Kurze’s edition.
As modelling the social network of German Waldensians is for me a side project and I cannot dedicate several months to model the data, we opted for the latter option and decided to use the DISSINET data model and its principles selectively. This proved to be a good solution. A more selective coding, focusing on the social relations, requires only ca. one hour per protocol, making the task feasible.
I presented the first, preliminary results in October 2021 at the conference ‘Radical Religious Communities in Premodern Societies’, organized jointly by the Centre for Medieval Studies (Institute of Philosophy, Czech Academy of Sciences) and the Hussite Museum in Tábor. Although based only on a small dataset of 15 protocols, already the first analysis revealed intriguing features of the German Waldensians’ relations. For example, female clusters in the network seem to be far less prominent in Stettin than in some other inquisitorial data. The first results were received with enthusiasm, and we are eager to see what we can find out on the basis of the full data of 195 depositions.
I also find the whole process of experimenting with the DISSINET data model an extremely educating experience. Accurate modelling of the data, although with quantitative and statistical analysis in mind, is in fact very close, qualitative reading. The medieval inquisition depositions often include sentences where syntax and the intended meaning is unclear. A structured data modelling forces one to make some decision – instead of hopping over uncertain passages, often possible in selective reading – and state to both oneself and others, why that decision is made.
DISSINET has developed an interactive map of the occupations, dissident religious affiliations, and locations of residence of nearly 900 persons suspected of heresy in the inquisition register of Bologna, 1291–1310.
Building upon the invaluable work of modern editors, the DISSINET project is building a textual corpus of medieval inquisitorial material, which now contains 15 registers, totals over 1.6 million tokens, and ranges from North-Central Italy through Languedoc to England, and from the 1230s until the 1520s.
