Replication data for: Verbal borrowability and turnover ratesdoi:10.18710/JFNESUDataverseNO2019-11-191Arkhangelskiy, Timofey, 2019, "Replication data for: Verbal borrowability and turnover rates", https://doi.org/10.18710/JFNESU, DataverseNO, V1Replication data for: Verbal borrowability and turnover ratesdoi:10.18710/JFNESUArkhangelskiy, TimofeyHamburg University2019-06-21HamburgDataverseNOThe Tromsø Repository of Language and Linguistics (TROLLing)Arkhangelskiy, TimofeyArkhangelskiy, Timofey2019-11-18Arts and HumanitiesRussianverbal borrowingsloanwordsdiachronycorpusThis is the dataset used in the study of verbal and nominal borrowings in written literary Russian language, their diachronic developments and their connection to frequency. The files contain a list of Russian lexemes annotated for borrowing status and a number of files with calculated probabilities of disappearance for lexemes of different frequency ranks over different periods of time.Abstract: Conventional wisdom holds that verbs are more difficult to borrow than nouns. Recent studies have supported this claim, inferring it from the fact that synchronically almost every language studied contained a larger proportion of identifiable borrowings among nouns than among verbs. In this paper, I demonstrate that there is a logical fallacy in this inference. Using a large diachronic corpus of Russian texts, I show that verbs have lower turnover rates and, consequently, longer life expectancies than nouns, i.e. they are generally more difficult to replace. I argue that this fact alone could theoretically result in the synchronically observed disparities. The hypothesis of cross-linguistically lower verbal turnover rates, which I propose based on these findings, is difficult to verify directly on a large sample of languages. However, it makes a non-trivial prediciton, which can be tested more easily. It predicts that if a contact situation lasted for a while, but ceased to exist several centuries ago, the proportion of verbs borrowed during that period and survivng to the present day may equal or exceed the proportion of such borrowings among nouns. The data found in the World Loanword Database (Haspelmath & Tadmor 2009) are consistent with this prediction, thus providing evidence in favor of the hypothesis.1750-01-012009-12-31Russian Federationcorpus dataRussian National Corpus (http://ruscorpora.ru/new/search-main.html)Arkhangelskiy, Timofey. ‘Verbal Borrowability and Turnover Rates’. Diachronica, vol. 37, no. 4, Dec. 2020, pp. 451–73. www.jbe-platform.com, https://doi.org/10.1075/dia.19032.ark.10.1075/dia.19032.arkArkhangelskiy, Timofey. ‘Verbal Borrowability and Turnover Rates’. Diachronica, vol. 37, no. 4, Dec. 2020, pp. 451–73. www.jbe-platform.com, https://doi.org/10.1075/dia.19032.ark.00_ReadMe.txttext/plain01_rnc_borrowed_lemmata.txttext/plaindisapp_prob_N_10.txttext/plaindisapp_prob_N_100.txttext/plaindisapp_prob_N_110.txttext/plaindisapp_prob_N_120.txttext/plaindisapp_prob_N_130.txttext/plaindisapp_prob_N_140.txttext/plaindisapp_prob_N_150.txttext/plaindisapp_prob_N_20.txttext/plaindisapp_prob_N_30.txttext/plaindisapp_prob_N_40.txttext/plaindisapp_prob_N_50.txttext/plaindisapp_prob_N_60.txttext/plaindisapp_prob_N_70.txttext/plaindisapp_prob_N_80.txttext/plaindisapp_prob_N_90.txttext/plaindisapp_prob_V_10.txttext/plaindisapp_prob_V_100.txttext/plaindisapp_prob_V_110.txttext/plaindisapp_prob_V_120.txttext/plaindisapp_prob_V_130.txttext/plaindisapp_prob_V_140.txttext/plaindisapp_prob_V_150.txttext/plaindisapp_prob_V_20.txttext/plaindisapp_prob_V_30.txttext/plaindisapp_prob_V_40.txttext/plaindisapp_prob_V_50.txttext/plaindisapp_prob_V_60.txttext/plaindisapp_prob_V_70.txttext/plaindisapp_prob_V_80.txttext/plaindisapp_prob_V_90.txttext/plain