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In Vietnamese medicine, gia truyen ("family recipes") refers to a set of texts, primarily in chu nôm (demotic Vietnamese characters), that preserves local knowledge about how practitioners in a specific family-based medical circle could use various plants and other materia medica to cure disease. This article traces the history of the transmission of gia truyen in the 19th and 20th centuries. It suggests that prior to the 1920s, gia truyen were written anonymously to protect the author's identity in the face of the Nguyen dynasty's repression of ch? nom writing. In the 1920s, precisely at the time that hán-nôm writing was being eclipsed by education in French and quoc ngu (Romanized Vietnamese), Vietnamese medical practitioners experienced a renaissance in the writing of chu nôm gia truyen. Moreover, chu nôm writing in the gia truyen genre continued until at least the 1990s. ©SOAS University of London 2017.
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Scientific communities as social groupings and the role that such communities play in scientific change and the production of scientific knowledge is currently under debate. I examine theory change as a complex social interaction among individual scientists and the scientific community, and argue that individuals will be motivated to adopt a more radical or innovative attitude when confronted with striking similarities between model systems and a more robust understanding of specialised vocabulary. Two case studies from the biological sciences, Barbara McClintock and Stanley Prusiner, help motivate the idea that sharing of models and specialised vocabulary fill the gap between discovery and scientific change by promoting the dispersal of important information throughout the scientific community. © 2017 Open Society Foundation.
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Mechanistic accounts of explanation have recently found popularity within philosophy of science. Presently, we introduce the idea of an extended mechanistic explanation, which makes explicit room for the role of environment in explanation. After delineating Craver and Bechtel’s (2007) account, we argue this suggestion is not sufficiently robust when we take seriously the mechanistic environment and modeling practices involved in studying contemporary complex biological systems. Our goal is to extend the already profitable mechanistic picture by pointing out the importance of the mechanistic environment. It is our belief that extended mechanistic explanations, or mechanisms that take into consideration the temporal sequencing of the interplay between the mechanism and the environment, allow for mechanistic explanations regarding a broader group of scientific phenomena. © 2016, Springer Science+Business Media Dordrecht.
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