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There is, however, no publicly available repository of judgments concerning the emerging practice area of animal protection law. This has hindered the identification of individual animal protection law judgments and comprehension of the scale of animal protection law made by courts. Thus, we detail the creation of an initial animal protection law repository using natural language processing and machine learning techniques. This involved domain expert classification of 500 judgments according to whether or not they were concerned with animal protection law. 400 of these judgments were used to train various models, each of which was used to predict the classification of the remaining 100 judgments. The predictions of each model were superior to a baseline measure intended to mimic current searching practice, with the best performing model being a support vector machine (SVM) approach that classified judgments according to term frequency\u2014inverse document frequency (TF-IDF) values. Investigation of this model consisted of considering its most influential features and conducting an error analysis of all incorrectly predicted judgments. This showed the features indicative of animal protection law judgments to include terms such as \u2018welfare\u2019, \u2018hunt\u2019 and \u2018cull\u2019, and that incorrectly predicted judgments were often deemed marginal decisions by the domain expert. The TF-IDF SVM was then used to classify non-labelled judgments, resulting in an initial animal protection law repository. Inspection of this repository suggested that there were 175 animal protection judgments between January 2000 and December 2020 from the Privy Council, House of Lords, Supreme Court and upper England and Wales courts.<\/jats:p>","DOI":"10.1007\/s10506-022-09313-y","type":"journal-article","created":{"date-parts":[[2022,5,8]],"date-time":"2022-05-08T14:02:32Z","timestamp":1652018552000},"page":"293-324","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["Using machine learning to create a repository of judgments concerning a new practice area: a case study in animal protection law"],"prefix":"10.1007","volume":"31","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4205-0543","authenticated-orcid":false,"given":"Joe","family":"Watson","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8726-2799","authenticated-orcid":false,"given":"Guy","family":"Aglionby","sequence":"additional","affiliation":[]},{"given":"Samuel","family":"March","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2022,5,8]]},"reference":[{"key":"9313_CR2","unstructured":"Advocates for Animals, Advocates for Animals. https:\/\/advocates-for-animals.com\/. 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There is and has been no financial relationship between any author and any organisation of relevance to this work. Further, no author is currently in any negotiations regarding future paid employment with any organisation of relevance. Samuel March (the third author and domain expert in this research) works as a part-time paralegal (volunteer) at Advocates for Animals, having held this position since April 2020. Joe Watson (the first author) also works as a part-time paralegal (volunteer) at Advocates for Animals and began this position in December 2020. The voluntary positions held by Samuel March and Joe Watson are provided for reasons of transparency, yet Advocates for Animals has had no influence on the contents of this paper.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflicts of interest"}},{"value":"Numerous ethical considerations were taken into account. The manuscript has not been submitted or published anywhere else, nor will it be submitted elsewhere until completion of the editorial process. We provide access to our code and information on where the data underlying our research is available. Additionally, all authors have approved the manuscript for submission and consent to publication should this submission be successful. This research did not directly involve any human or animal participants. All humans (aside from the domain expert, who is also the third author) and animals mentioned in the document text are present in court judgments publicly available on BAILII.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethical approval"}},{"value":"No humans or animals beyond the listed authors participated directly in this research. As such, consent to participate was not sought.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Consent to participate"}},{"value":"No humans or animals beyond the listed authors participated directly in this research, and all humans (aside from the domain expert) and animals mentioned in the document text are present in court judgments publicly available on BAILII. Consent to publish was therefore not sought.","order":5,"name":"Ethics","group":{"name":"EthicsHeading","label":"Consent for publication"}}]}}