{"title":"计算裂缝:解析早期现代自然哲学的语境。","authors":"Andrea Sangiacomo, Raluca Tanasescu","doi":"10.1017/S0269889725100653","DOIUrl":null,"url":null,"abstract":"<p><p>Ongoing debates among historians of early modern philosophy are concerned with how to best understand the context of historical works and authors. Current methods usually rely on qualitative assessments made by the historians themselves and do not define constraints that can be used to profile a given context in more quantitative terms. In this paper, we present a computational method that can be used to parse a large corpus of works based on their linguistic features, alongside some preliminary information that can be retrieved from the associated metadata. The goal of the method is to use the available information about the corpus to create broad groups that can work as sub-contexts for better understanding different sorts of works and authors. In turn, this makes it possible to better profile each group and identify its most distinguishing linguistic features. Once these features are clarified, it will eventually become possible to also identify what the most representative works and authors in each group are and which of them may be worth exploring in greater detail. This classification method thus allows historians to integrate their qualitative assessments with quantitative studies in order to better define the relevant context for any given work.</p>","PeriodicalId":49562,"journal":{"name":"Science in Context","volume":" ","pages":"1-37"},"PeriodicalIF":0.3000,"publicationDate":"2025-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Computational Rifts: Parsing the Context of Early Modern Natural Philosophy.\",\"authors\":\"Andrea Sangiacomo, Raluca Tanasescu\",\"doi\":\"10.1017/S0269889725100653\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Ongoing debates among historians of early modern philosophy are concerned with how to best understand the context of historical works and authors. Current methods usually rely on qualitative assessments made by the historians themselves and do not define constraints that can be used to profile a given context in more quantitative terms. In this paper, we present a computational method that can be used to parse a large corpus of works based on their linguistic features, alongside some preliminary information that can be retrieved from the associated metadata. The goal of the method is to use the available information about the corpus to create broad groups that can work as sub-contexts for better understanding different sorts of works and authors. In turn, this makes it possible to better profile each group and identify its most distinguishing linguistic features. Once these features are clarified, it will eventually become possible to also identify what the most representative works and authors in each group are and which of them may be worth exploring in greater detail. This classification method thus allows historians to integrate their qualitative assessments with quantitative studies in order to better define the relevant context for any given work.</p>\",\"PeriodicalId\":49562,\"journal\":{\"name\":\"Science in Context\",\"volume\":\" \",\"pages\":\"1-37\"},\"PeriodicalIF\":0.3000,\"publicationDate\":\"2025-06-27\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Science in Context\",\"FirstCategoryId\":\"98\",\"ListUrlMain\":\"https://doi.org/10.1017/S0269889725100653\",\"RegionNum\":4,\"RegionCategory\":\"哲学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"Arts and Humanities\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Science in Context","FirstCategoryId":"98","ListUrlMain":"https://doi.org/10.1017/S0269889725100653","RegionNum":4,"RegionCategory":"哲学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"Arts and Humanities","Score":null,"Total":0}
Computational Rifts: Parsing the Context of Early Modern Natural Philosophy.
Ongoing debates among historians of early modern philosophy are concerned with how to best understand the context of historical works and authors. Current methods usually rely on qualitative assessments made by the historians themselves and do not define constraints that can be used to profile a given context in more quantitative terms. In this paper, we present a computational method that can be used to parse a large corpus of works based on their linguistic features, alongside some preliminary information that can be retrieved from the associated metadata. The goal of the method is to use the available information about the corpus to create broad groups that can work as sub-contexts for better understanding different sorts of works and authors. In turn, this makes it possible to better profile each group and identify its most distinguishing linguistic features. Once these features are clarified, it will eventually become possible to also identify what the most representative works and authors in each group are and which of them may be worth exploring in greater detail. This classification method thus allows historians to integrate their qualitative assessments with quantitative studies in order to better define the relevant context for any given work.
期刊介绍:
Science in Context is an international journal edited at The Cohn Institute for the History and Philosophy of Science and Ideas, Tel Aviv University, with the support of the Van Leer Jerusalem Institute. It is devoted to the study of the sciences from the points of view of comparative epistemology and historical sociology of scientific knowledge. The journal is committed to an interdisciplinary approach to the study of science and its cultural development - it does not segregate considerations drawn from history, philosophy and sociology. Controversies within scientific knowledge and debates about methodology are presented in their contexts.