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Towards Ethical Judicial Analytics: Assessing Readability of Immigration and Asylum Decisions in the United Kingdom

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Progress in Artificial Intelligence (EPIA 2021)


Motivated by the broader issues of open justice and access to justice, this paper explores the ethical application of judicial analytics through the lens of an assessment of readability of written judicial decisions. To that end the paper aims 1) to review and reproduce for the UK context previous work that assesses readability of legal texts, and 2) to reflect critically on the ethical implications of applied judicial analytics. Focusing on the use case of assessing the readability of judicial Immigration and Asylum decisions in the UK, we put forward recommendations for ethical judicial analytics that aim to produce results that meet the needs of and are accepted by the stakeholders of the legal system.

This work was supported by the Economic and Social Research Council [ES/P000630/1]. We thank Gregory Tourte for his valuable technical contributions.

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  1. 1.

    It should be noted, however, that readability formulas were never meant as a writing guide, though writing guidelines can be deduced accordingly [21].

  2. 2.

    Short for ‘Simple Measure of Gobbledygok’ [see 42].

  3. 3.

    Others do not find an effect of the type of judicial retention on opinion clarity [22].

  4. 4.

    Note that others find decreasing readability over time [13, 42].

  5. 5.

    Checking the robots.txt-file revealed no restrictions on such scraping activity.


  1. Alschner, W., D’Alimonte, D., Giuga, G.C., Gadbois, S.: Plain language assessment of statutes. In: Legal Knowledge and Information Systems: Proceedings of the 33rd JURIX Annual Conference, pp. 207–2010. IOS Press (2020).

  2. AoIR: The association of internet researchers ethics framework (2019).

  3. Assy, R.: Can the law speak directly to its subjects? The limitation of plain language. J. Law Soc. 38(3), 376–404 (2011).

    Article  Google Scholar 

  4. George Benjamin, R.: Reconstructing readability: recent developments and recommendations in the analysis of text difficulty. Educ. Psychol. Rev. 24(1), 63–88 (2012). ISSN 1573-336X.

  5. Bufithis, G.: Understanding the French ban on judicial analytics (2019).

  6. Burridge, A., Gill, N.: Conveyor-belt justice: precarity, access to justice, and uneven geographies of legal aid in UK asylum appeals. Antipode 49(1), 23–42 (2017).

    Article  Google Scholar 

  7. Butt, P.: The assumptions behind plain legal language. Hong Kong LJ 32, 173 (2002)

    Google Scholar 

  8. Campbell Pearson, W.: Clarity in the Court of Appeal: measuring the readability of judgments. Bachelor thesis, law, University of Otago (2013)

    Google Scholar 

  9. Crossley, S.A., Skalicky, S., Dascalu, M., McNamara, D.S., Kyle, K.: Predicting text comprehension, processing, and familiarity in adult readers: new approaches to readability formulas. Discourse Process. 54(5–6), 340–359 (2017).

    Article  Google Scholar 

  10. Crossley, S.A., Skalicky, S., Dascalu, M.: Moving beyond classic readability formulas: new methods and new models. J. Res. Read. 42(3–4), 541–561 (2019).

    Article  Google Scholar 

  11. Curtotti, M., McCreath, E.: Right to access implies right to know: an open online platform for research on the readability of law. J. Open Access Law 1(1), 1–56 (2013)

    Google Scholar 

  12. Curtotti, M., McCreath, E., Bruce, T., Frug, S., Weibel, W., Ceynowa, N.: Machine learning for readability of legislative sentences. In: Proceedings of the 15th International Conference on Artificial Intelligence and Law, ICAIL 2015, New York, NY, USA, pp. 53–62, 2015. Association for Computing Machinery. ISBN 9781450335225.

  13. Daily, C.M., Dorsey, R.W., Kumar, G.: Readability of tax court opinions. In: Stock, T. (ed.) Advances in Taxation, vol. 19, pp. 171–183. Emerald Group Publishing Limited (2010).

  14. Dale, E., Chall, J.S.: The concept of readability. Element. Eng. 26(1), 19–26 (1949). ISSN 00135968.

  15. Duffy, T.M.: Readability formulas: what’s the use? In: Duffy, T.M., Waller, R. (eds.) Designing Usable Texts, chapter 6, pp. 113–143. Academic Press (1985). ISBN 978-0-12-223260-2.

  16. European Commission for the Efficiency of Justice (CEPEJ): Cepej European ethical charter on the use of artificial intelligence (AI) in judicial systems and their environment (2019)

    Google Scholar 

  17. Elliot, M., Mackey, E., O’Hara, K.: The anonymisation decision-making framework 2nd edn. European practitioners’ guide. UKAN (2020)

    Google Scholar 

  18. Everson, E.: Privacy by design: taking ctrl of big data. Cleveland State Law Rev. 65, 27 (2017)

    Google Scholar 

  19. Fix, M.P., Fairbanks, B.R.: The effect of opinion readability on the impact of U.S. supreme court precedents in state high courts. Soc. Sci. Q. 101(2), 811–824 (2020).

  20. François, T., Miltsakaki, E.: Do NLP and machine learning improve traditional readability formulas? In: Proceedings of the First Workshop on Predicting and Improving Text Readability for target reader populations, Montréal, Canada, pp. 49–57, June 2012. Association for Computational Linguistics (2012)

    Google Scholar 

  21. Fry, E.B.: Writeability: the principles of writing for increased comprehension. In: Zakaluk, B.L., Samuals, S.J. (eds.) Readability: Its Past, Present, and Future, chapter 5, Newark, Delaware, pp. 77–97. International Reading Association (1988)

    Google Scholar 

  22. Goelzhauser, G., Cann, D.M.: Judicial independence and opinion clarity on state supreme courts. State Politics Pol. Q. 14(2), 123–141 (2014).

    Article  Google Scholar 

  23. Horton, B.G., Thompson, L.R.: Jury instructions: are they too complicated for jurors to understand? Commun. Law Rev. 4, 1–8 (2002)

    Google Scholar 

  24. Klare, G.R.: Assessing readability. Read. Res. Q. 10(1), 62–102 (1974). ISSN 00340553.

  25. Martindale, B.C., Koch, B.S., Karlinsky, S.S.: Tax law complexity: the impact of style. J. Bus. Commun. (1973) 29(4), 383–400 (1992).

  26. Martínez, A., da Silva, R.: Tax law readability and tax complexity (2019)

    Google Scholar 

  27. McGill, J., Salyzyn, A.: Judging by numbers: how will judicial analytics impact the justice system and its stakeholders? Working paper, Ottawa Faculty of Law (2020)

    Google Scholar 

  28. Jerry McHale, M.: What does “access to justice” mean? UVic Ace (2016).

  29. Mindlin, M.: Is plain language better a comparative readability study of court forms. Scribes J. Legal Writ. 10, 55–66 (2005)

    Google Scholar 

  30. Nelson, M.N.: Elections and explanations: judicial retention and the readability of judicial opinions (2013).

  31. Petrozzino, C.: Big data analytics: ethical considerations make a difference. Scitech Lawyer 16(3), 14–21 (2020)

    Google Scholar 

  32. Pikulski, J.J.: Readability. Houghton Mifflin, Boston (2002)

    Google Scholar 

  33. Pitler, E., Nenkova, A.: Revisiting readability: a unified framework for predicting text quality. In: Proceedings of the Conference on Empirical Methods in Natural Language Processing, EMNLP 2008, USA, pp. 186–195. Association for Computational Linguistics (2008)

    Google Scholar 

  34. Samaha, A.M.: Judicial transparency in an age of prediction symposium: the future of judicial transparency - panel one: transparent virtues. Villanova Law Rev. 53, 829 (2008)

    Google Scholar 

  35. Sikkema, T.: Does plain language only benefit the higher literate? avoiding the Matthew-effect in plain language revisions. Clarity J. 80, 19–22 (2019). ISSN 2378-2056

    Google Scholar 

  36. Spencer, S.B., Feldman, A.: Words count: the empirical relationship between brief writing and summary judgment success. Legal Writ. J. Legal Writ. Inst. 22, 61–108 (2018)

    Google Scholar 

  37. Stalla-Bourdillon, S., Knight, A.: Legal and privacy toolkit v1.0 (2017)

    Google Scholar 

  38. Sullivan, R.: The promise of plain language drafting. McGill LJ 47, 97 (2001)

    Google Scholar 

  39. Sung, Y.-T., Chen, J.-L., Cha, J.-H., Tseng, H.-C., Chang, T.-H., Chang, K.-E.: Constructing and validating readability models: the method of integrating multilevel linguistic features with machine learning. Behav. Res. Methods 47(2), 340–354 (2014).

    Article  Google Scholar 

  40. Todirascu, A., François, T., Gala, N., Fairon, C., Ligozat, A.-L., Bernhard, D.: Coherence and cohesion for the assessment of text readability. In: Proceedings of 10th International Workshop on Natural Language Processing and Cognitive Science (NLPCS 2013), Marseille, France, pp. 11–19, October 2013.

  41. Wahlstrom, K., Roddick, J.F., Sarre, R., Estivill-Castro, V., deVries, D.: On the ethical and legal implications of data mining. School of Informatics and Engineering Flinders University (2006)

    Google Scholar 

  42. Whalen, R.: Judicial gobbledygook: the readability of Supreme Court writing. Yale Law J. Forum 125(19), 200–211 (2015)

    Google Scholar 

  43. Williams, C.: Changing with the times: the evolution of plain language in the legal sphere. Revista Alicantina de Estudios Ingleses 28, 183–203 (2015).

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Scheinert, L., Tonkin, E.L. (2021). Towards Ethical Judicial Analytics: Assessing Readability of Immigration and Asylum Decisions in the United Kingdom. In: Marreiros, G., Melo, F.S., Lau, N., Lopes Cardoso, H., Reis, L.P. (eds) Progress in Artificial Intelligence. EPIA 2021. Lecture Notes in Computer Science(), vol 12981. Springer, Cham.

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