This article falls into two parts. In the first the introduction of Darwinism into Japan up to the 1920s is described. The second is a bibliographical survey of Japanese versions of Darwin's work published between 1896 and 1974.

This is a brief history of Japanese science since the beginning of Japan as a modern state in 1868 to the end of the Second World War. It focuses on five aspects: The intellectual training in Chinese studies prior to the period was significant for the reception of Western science. Chinese ideograms were effectively utilized for creating technical terms for science. Western science and technology were intensively implanted in approximately the first 30 years with the help of a large number (...) of hired foreign experts, unparalleled in modern world history. A few major scientific personalities and a new, leading research institute emerged around the First World War. The wartime expansion of research expenditure occurred and Japanese research institutes were established in China. Maturity of Japanese science was attained, as seen in an example of theoretical physics. (shrink)

When Bouvet discovered the relationship between the binary arithmetic of Leibniz and the hexagrams of the I ching—in reality only a purely formal correspondence—he sent to Leibniz a woodcut diagram of the Fu-Hsi arrangement, which provides the key to the analogy. This diagram, in a re-drawn version, was first published by Gorai Kinzō in a study of Leibniz's interpretation of the I ching and Confucianism which has been influential in providing, indirectly, the principal source for the accounts of Wilhelm and (...) Needham. Yet this pioneering study of Leibniz's interpretation of the hexagrams is virtually unknown. Even the account of Needham, who saved it from complete obscurity, contains one or two inaccuracies about it and these are repeated by Zacher in his otherwise excellent monograph on Leibniz's binary arithmetic. (shrink)

The use of artificial intelligence (AI) to aid legal decision making has become prominent. This paper investigates the use of AI in a critical issue in employment law, the determination of a worker’s status—employee vs. independent contractor—in two common law countries (the U.S. and Canada). This legal question has been a contentious labor issue insofar as independent contractors are not eligible for the same benefits as employees. It has become an important societal issue due to the ubiquity of the gig (...) economy and the recent disruptions in employment arrangements. To address this problem, we collected, annotated, and structured the data for all Canadian and Californian court cases related to this legal question between 2002 and 2021, resulting in 538 Canadian cases and 217 U.S. cases. In contrast to legal literature focusing on complex and correlated characteristics of the employment relationship, our statistical analyses of the data show very strong correlations between the worker’s status and a small subset of quantifiable characteristics of the employment relationship. In fact, despite the variety of situations in the case law, we show that simple, off-the-shelf AI models classify the cases with an out-of-sample accuracy of more than 90%. Interestingly, the analysis of misclassified cases reveals consistent misclassification patterns by most algorithms. Legal analyses of these cases led us to identify how equity is ensured by judges in ambiguous situations. Finally, our findings have practical implications for access to legal advice and justice. We deployed our AI model via the open-access platform, https://MyOpenCourt.org/, to help users answer employment legal questions. This platform has already assisted many Canadian users, and we hope it will help democratize access to legal advice to large crowds. (shrink)