Richterrecht der Arbeit – empirisch untersucht. Möglichkeiten und Grenzen computergestützter Textanalyse am Beispiel des Arbeitnehmerbegriffs.

Vogel, Friedemann; Pötters, Stephan; Christensen, Ralph

doi:10.3790/978-3-428-54636-7

Cited by 2 publications

(3 citation statements)

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“…With several journals now dedicated to this field (e.g., International Journal of Corpus Linguistics, Corpora, Corpus Linguistics and Linguistic Theory), most of its infrastructure has been in place for about twenty years (the International Journal of Corpus Linguistics was established in 1995, and McEnery and Wilson published their textbook in 1996; see also L€ udeling and Kyt€ o 2008). This research has also made its way into studies of law (Bhatia, Langton, and Lung 2004;Kredens and Go zd z-Roszkowski 2007;Go zd z-Roszkowski 2011;Mouritsen 2010Mouritsen , 2011Vogel 2012aVogel , 2015Vogel, Christensen, and P€ otters 2015), thus intersecting with another new strand of research.…”

Section: Computer-assisted Legal Linguisticsmentioning

confidence: 99%

“…The corpus included roughly 35,000 texts from legal areas such as criminal law, public law, and business law. Vogel, Christensen, and Pötters (2015) collected 9,000 court decisions from 1954 until 2012 to examine the usage of the term “employee” ( Arbeitnehmer ) in German jurisprudence. For an earlier study, Vogel (2012a) gathered 4,200 decisions from the German Federal Constitutional Court to investigate recurrent patterns in juridical discourse about “human dignity” ( Menschenwürde ).…”

Section: Existing Specialized Legal Corporamentioning

confidence: 99%

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Computer-Assisted Legal Linguistics: Corpus Analysis as a New Tool for Legal Studies

Vogel¹,

Hamann²,

Gauer³

2018

Law soc. inq.

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Law exists solely in and through language. Nonetheless, systematical empirical analysis of legal language has been rare. Yet, the tides are turning: After judges at various courts (including the US Supreme Court) have championed a method of analysis called corpus linguistics, the Michigan Supreme Court held in June 2016 that this method “is consistent with how courts have understood statutory interpretation.” The court illustrated how corpus analysis can benefit legal casework, thus sanctifying twenty years of previous research into the matter. The present article synthesizes this research and introduces computer-assisted legal linguistics (CAL2) as a novel approach to legal studies. Computer-supported analysis of carefully preprocessed collections of legal texts lets lawyers analyze legal semantics, language, and sociosemiotics in different working contexts (judiciary, legislature, legal academia). The article introduces the interdisciplinary CAL2 research group (www.cal2.eu), its Corpus of German Law, and other related projects that make law more transparent.

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Section: Computer-assisted Legal Linguisticsmentioning

confidence: 99%

Section: Existing Specialized Legal Corporamentioning

confidence: 99%

Computer-Assisted Legal Linguistics: Corpus Analysis as a New Tool for Legal Studies

Vogel¹,

Hamann²,

Gauer³

2018

Law soc. inq.

Self Cite

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“…https://www.ibm.com/watson/services/knowledge-studio/4 For an introduction to computer assisted, linguistic research in law, see[18] 5. For Labour Law, see[17] 6. See, e.g.…”

mentioning

confidence: 99%

LawStats – Large-Scale German Court Decision Evaluation Using Web Service Classifiers

Ruppert

Hartung

Sittig

et al. 2018

Lecture Notes in Computer Science

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LawStats provides quantitative insights into court decisions from the Bundesgerichtshof -Federal Court of Justice (BGH), the Federal Court of Justice in Germany. Using Watson Web Services and approaches from Sentiment Analysis (SA), we can automatically classify the revision outcome and offer statistics on judges, senates, previous instances etc. via faceted search. These statistics are accessible through a open web interface to aid law professionals. With a clear focus on interpretability, users can not only explore statistics, but can also understand, which sentences in the decision are responsible for the machine's decision; links to the original texts provide more context. This is the first largescale application of Machine Learning (ML) based Natural Language Processing (NLP) for German in the analysis of ordinary court decisions in Germany that we are aware of. We have analyzed over 50,000 court decisions and extracted the outcomes and relevant entities. The modular architecture of the application allows continuous improvements of the ML model as more annotations become available over time. The tool can provide a critical foundation for further quantitative research in the legal domain and can be used as a proof-of-concept for similar efforts.

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Richterrecht der Arbeit – empirisch untersucht. Möglichkeiten und Grenzen computergestützter Textanalyse am Beispiel des Arbeitnehmerbegriffs.

Cited by 2 publications

References 0 publications

Computer-Assisted Legal Linguistics: Corpus Analysis as a New Tool for Legal Studies

Computer-Assisted Legal Linguistics: Corpus Analysis as a New Tool for Legal Studies

LawStats – Large-Scale German Court Decision Evaluation Using Web Service Classifiers

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