English Poor Law Cases, 1691-1834

Deakin, Simon and Shuku, Linda and Cheok, Vanessa (2024). English Poor Law Cases, 1691-1834. [Data Collection]. Colchester, Essex: UK Data Service. 10.5255/UKDA-SN-857470

This is the latest version of this item.

This dataset was constructed as part of a project ('Legal Systems and Artificial Intelligence') assessing the implications of the introduction of Artificial Intelligence (AI) into legal systems in Japan and the United Kingdom. The project was jointly funded by the UK’s Economic and Social Research Council, part of UKRI, and the Japanese Science and Technology Agency (JST), and involved collaboration between Cambridge University (the Centre for Business Research, Department of Computer Science, and Faculty of Law) and Hitotsubashi University, Tokyo (the Graduate Schools of Law and Business Administration). Additional funding was provided by the Keynes Fund of the University of Cambridge through the project ‘Legal Evolution and Industrialisation: Computational Analysis of Historical Poor Law and Workmen’s Compensation Cases’.

In November 2024 an updated version of the dataset was added to the one initially deposited.

Data description (abstract)

The dataset consists of annotated cases concerning the right to a settlement by hiring under poor law legislation which was in force between 1691 and 1834. During this period, parishes could contest their liabilities to pay poor relief by taking appeals from decisions of the quarter sessions to the Court of King’s Bench. The decisions of the Court of King’s Bench were recorded in a number of nominate reports, and analysed in several treatises and textbooks. The dataset contains the text of relevant cases with annotations designed to facilitate the application of natural language processing techniques.

For further detail on potential uses of the dataset, see Simon Deakin and Linda Shuku, 'Exploring computational approaches to law: the evolution of judicial language in the Anglo-Welsh poor law, 1691-1834', Journal of Law and Society (2024) and CBR working paper series, https://www.jbs.cam.ac.uk/centres/business-research-cbr/publications/working-papers/.

Data creators: