LiFR-Law. Corpus of Paraphrased Czech Administrative Texts with Reading Comprehension for Readability Studies (2023-10-08)

LiFR-Law is a corpus of Czech legal and administrative texts with measured reading comprehension and a subjective expert annotation of diverse textual properties based on the Hamburg Comprehensibility Concept (Langer, Schulz von Thun, Tausch, 1974). It has been built as a pilot data set to explore the Linguistic Factors of Readability (hence the LiFR acronym) in Czech administrative and legal texts, modeling their correlation with actually observed reading comprehension. The corpus is comprised of 18 documents in total; that is, six different texts from the legal/administration domain, each in three versions: the original and two paraphrases. Each such document triple shares one reading-comprehension test administered to at least thirty readers of random gender, educational background, and age. The data set also captures basic demographic information about each reader, their familiarity with the topic, and their subjective assessment of the stylistic properties of the given document, roughly corresponding to the key text properties identified by the Hamburg Comprehensibility Concept. Changes to the previous version and helpful comments • File names of the comprehension test results (self-explanatory) • Corrected one erroneous automatic evaluation rule in the multiple-choice evaluation (zahradnici_3, TRUE and FALSE had been swapped) • Evaluation protocols for both question types added into Folder lifr_formr_study_design • Data has been cleaned: empty responses to multiple-choice questions were re-inserted. Now, all surveys are considered complete that have reader’s subjective text evaluation complete (these were placed at the very end of each survey). • Only complete surveys (all 7 content questions answered) are represented. We dropped the replies of six users who did not complete their surveys. • A few missing responses to open questions have been detected and re-inserted. • The demographic data contain all respondents who filled in the informed consent and the demographic details, with respondents who did not complete any test survey (but provided their demographic details) in a separate file. All other data have been cleaned to contain only responses by the regular respondents (at least one completed survey).