Legislative drafters use plain language drafting techniques to increase the readability of statutes in several Anglo-American jurisdictions. Existing readability metrics, such as Flesch-Kincaid, however, are a poor proxy for how effectively drafters incorporate these guidelines. This paper proposes a rules-based operationalization of the literature’s readability measures and tests them on legislation that underwent plain language rewriting. The results suggest that our readability metrics provide a more holistic representation of a statute’s readability compared to traditional techniques. Future machine-learning classifications promise to further improve the detection of complex features, such as nominalizations.
IOS Press, Inc.
6751 Tepper Drive
Clifton, VA 20124
Tel.: +1 703 830 6300
Fax: +1 703 830 2300 firstname.lastname@example.org
(Corporate matters and books only) IOS Press c/o Accucoms US, Inc.
For North America Sales and Customer Service
West Point Commons
Lansdale PA 19446
Tel.: +1 866 855 8967
Fax: +1 215 660 5042 email@example.com