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Dieses Gespräch wurde am 6. Februar 2023 in den Räumlichkeiten des Marsilius-Kollegs der Universität Heidelberg aufgenommen. Es spiegelt den Austausch zwischen den beteiligten Wissenschaftlerinnen und Wissenschaftlern wider und gibt einen ersten Einblick in die Themen und Fragen, die in diesem Sammelband eine Rolle spielen. Das Gespräch wurde transkribiert und an denjenigen Stellen sprachlich überarbeitet, die es aus Gründen der Verständlich- und Lesbarkeit erforderten. Der mündliche, im Nachdenken begriffene Charakter des Gesprächs wurde gewahrt.
KonsortSWD ist das NFDI Konsortium für die Sozial-, Verhaltens-, Bildungs- und Wirtschaftswissenschaften. Für die äußerst vielfältigen Datentypen und Forschungsmethoden bauen die Beteiligten im Rahmen der NFDI eine bereits bestehende Forschungsdateninfrastruktur aus und ergänzen neue integrierende Dienste. Basis sind die heute 41 vom Rat für Sozial- und Wirtschaftsdaten akkreditierten Forschungsdatenzentren (FDZ). FDZ sind Spezialsammlungen zu jeweils spezifischen Forschungsdaten, z.B. aus der qualitativen Sozialforschung, und können so Forschende auf Basis einer ausführlichen Expertise zu diesen Daten beraten. Neben der Unterstützung der FDZ baut KonsortSWD auch neue Dienste in den Bereichen Datenproduktion, Datenzugang und Technische Lösungen auf.
This paper presents a compositional annotation scheme to capture the clusivity properties of personal pronouns in context, that is their ability to construct and manage in-groups and out-groups by including/excluding the audience and/or non-speech act participants in reference to groups that also include the speaker. We apply and test our schema on pronoun instances in speeches taken from the German parliament. The speeches cover a time period from 2017-2021 and comprise manual annotations for 3,126 sentences. We achieve high inter-annotator agreement for our new schema, with a Cohen’s κ in the range of 89.7-93.2 and a percentage agreement of > 96%. Our exploratory analysis of in/exclusive pronoun use in the parliamentary setting provides some face validity for our new schema. Finally, we present baseline experiments for automatically predicting clusivity in political debates, with promising results for many referential constellations, yielding an overall 84.9% micro F1 for all pronouns.
The debate on the use of personal data in language resources usually focuses — and rightfully so — on anonymisation. However, this very same debate usually ends quickly with the conclusion that proper anonymisation would necessarily cause loss of linguistically valuable information. This paper discusses an alternative approach — pseudonymisation. While pseudonymisation does not solve all the problems (inasmuch as pseudonymised data are still to be regarded as personal data and therefore their processing should still comply with the GDPR principles), it does provide a significant relief, especially — but not only — for those who process personal data for research purposes. This paper describes pseudonymisation as a measure to safeguard rights and interests of data subjects under the GDPR (with a special focus on the right to be informed). It also provides a concrete example of pseudonymisation carried out within a research project at the Institute of Information Technology and Communications of the Otto von Guericke University Magdeburg.
In a previous study published in Nature Human Behaviour, Varnum and Grossmann claim that reductions in gender inequality are linked to reductions in pathogen prevalence in the United States between 1951 and 2013. Since the statistical methods used by Varnum and Grossmann are known to induce (seemingly) significant correlations between unrelated time series, so-called spurious or non-sense correlations, we test here whether the statistical association between gender inequality and pathogens prevalence in its current form also is the result of mis-specified models that do not correctly account for the temporal structure of the data. Our analysis clearly suggests that this is the case. We then discuss and apply several standard approaches of modelling time-series processes in the data and show that there is, at least as of now, no support for a statistical association between gender inequality and pathogen prevalence.
Digital humanities research under United States and European copyright laws. Evolving frameworks
(2021)
This chapter summarizes the current state of copyright laws in the United States and European Union that most affect Digital Humanities research, namely the fair use doctrine in the US and research exceptions in Europe, including the Directive on Copyright in the Digital Single Market, which has been finally adopted in 2019. This summary begins with a description of recent copyright advances most relevant to DH research, and finishes with an analysis of a significant remaining legal hurdle which DH researchers face: how do fair use and research exceptions deal with the critical issue of circumventing technological protection measures (TPM, a.k.a. DRM). Our discussion of the lawful means of obtaining TPM-protected material may contribute to both current DH research and planning decisions and inform future stakeholders and lawmakers of the need to allow TPM circumvention for academic research.
The General Data Protection Regulation (GDPR) on personal data protection in the European Union entered into application on 25 May 2018. With its 173 recitals and 99 articles, it may be one of the most ambitious pieces of EU legislation to date. Rather than a guide to GDPR compliance for Digital Humanities researchers, this chapter looks at the use of personal data in DH projects from the data subject’s perspective, and examines to what extent the GDPR kept its promise of enabling the data subject to “take control of his data”. The chapter provides an overview of the right to privacy and the right to data protection, a discussion of the relation between the concept of data control and privacy and data protection law, an introduction to the GDPR, and an explanation of its relevance for scientific research in general and DH in particular. The main section of the chapter analyses two types of data control mechanisms (consent and data subject rights) and their impact on DH research.
Who is we? Disambiguating the referents of first person plural pronouns in parliamentary debates
(2021)
This paper investigates the use of first person plural pronouns as a rhetorical device in political speeches. We present an annotation schema for disambiguating pronoun references and use our schema to create an annotated corpus of debates from the German Bundestag. We then use our corpus to learn to automatically resolve pronoun referents in parliamentary debates. We explore the use of data augmentation with weak supervision to further expand our corpus and report preliminary results.