Israeli scholars from Tel Aviv University and Ariel University in Samaria have utilized a machine learning algorithm to confirm ancient rabbinic theories regarding linguistic variations within specific tractates of the Talmud. The study, published in the Journal of Jewish Studies, highlights the presence of unique language features in certain sections of the Babylonian Talmud that had been identified by medieval rabbis as special tractates.
The research team, led by Jakub Zbrzeżny, found that the algorithm was able to detect a significant number of non-Babylonian linguistic features in these special tractates, aligning with the insights of renowned Torah scholars like Rashi. One notable finding was in the tractate Tamid, which discusses Temple sacrifices, where the algorithm flagged numerous lines related to stories about Alexander the Great, hinting at potential external sources for these passages.
Moreover, the algorithm identified other Talmudic sections with language similarities to the special tractates and highlighted certain tractates with a more uniform dialect than average, shedding new light on this linguistic phenomenon in Jewish studies.
This groundbreaking study marks a milestone in the intersection of technology and ancient scholarship, providing empirical evidence for long-held rabbinic theories about the linguistic intricacies of the Talmud. By leveraging machine learning, Israeli scholars have brought a fresh perspective to the study of these sacred texts, bridging the gap between tradition and scientific innovation.
