{"title":"在已知的海洋中发现未知:健康监测、知识基础设施和寻求分类出口。","authors":"Francis Lee","doi":"10.1017/S0269889723000133","DOIUrl":null,"url":null,"abstract":"<p><p>The sociological study of knowledge infrastructures and classification has traditionally focused on the politics and practices of classifying things or people. However, actors' work to escape dominant infrastructures and pre-established classification systems has received little attention. In response to this, this article argues that it is crucial to analyze, not only the practices and politics of classification, but also actors' <i>work to escape dominant classification systems</i>. The article has two aims: First, to make a theoretical contribution to the study of classification by proposing to pay analytical attention to practices of escaping classification, what the article dubs <i>classification egress</i>. This concept directs our attention not only to the practices and politics of classifying things, but also to how actors work to escape or <i>resist classification systems</i> in practice. Second, the article aims to increase our understanding of the history of quantified and statistical health surveillance. In this, the article investigates how actors in health surveillance assembled a knowledge infrastructure for surveilling, quantifying, and detecting unknown patterns of congenital malformations in the wake of the thalidomide disaster in the early 1960s. The empirical account centers on the actors' work to detect congenital malformations and escape the dominant nosological classification of diseases, the International Classification of Diseases (ICD), by replacing it with a procedural standard for reporting of symptoms. Thus, the article investigates how actors deal with the tension between the-already-known-and-classified and the unknown-unclassified-phenomenon in health surveillance practice.</p>","PeriodicalId":49562,"journal":{"name":"Science in Context","volume":null,"pages":null},"PeriodicalIF":0.3000,"publicationDate":"2022-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Detecting the unknown in a sea of knowns: Health surveillance, knowledge infrastructures, and the quest for classification egress.\",\"authors\":\"Francis Lee\",\"doi\":\"10.1017/S0269889723000133\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>The sociological study of knowledge infrastructures and classification has traditionally focused on the politics and practices of classifying things or people. However, actors' work to escape dominant infrastructures and pre-established classification systems has received little attention. In response to this, this article argues that it is crucial to analyze, not only the practices and politics of classification, but also actors' <i>work to escape dominant classification systems</i>. The article has two aims: First, to make a theoretical contribution to the study of classification by proposing to pay analytical attention to practices of escaping classification, what the article dubs <i>classification egress</i>. This concept directs our attention not only to the practices and politics of classifying things, but also to how actors work to escape or <i>resist classification systems</i> in practice. Second, the article aims to increase our understanding of the history of quantified and statistical health surveillance. In this, the article investigates how actors in health surveillance assembled a knowledge infrastructure for surveilling, quantifying, and detecting unknown patterns of congenital malformations in the wake of the thalidomide disaster in the early 1960s. The empirical account centers on the actors' work to detect congenital malformations and escape the dominant nosological classification of diseases, the International Classification of Diseases (ICD), by replacing it with a procedural standard for reporting of symptoms. Thus, the article investigates how actors deal with the tension between the-already-known-and-classified and the unknown-unclassified-phenomenon in health surveillance practice.</p>\",\"PeriodicalId\":49562,\"journal\":{\"name\":\"Science in Context\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.3000,\"publicationDate\":\"2022-06-01\",\"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/S0269889723000133\",\"RegionNum\":4,\"RegionCategory\":\"哲学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2023/11/23 0:00:00\",\"PubModel\":\"Epub\",\"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/S0269889723000133","RegionNum":4,"RegionCategory":"哲学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2023/11/23 0:00:00","PubModel":"Epub","JCR":"Q2","JCRName":"Arts and Humanities","Score":null,"Total":0}
Detecting the unknown in a sea of knowns: Health surveillance, knowledge infrastructures, and the quest for classification egress.
The sociological study of knowledge infrastructures and classification has traditionally focused on the politics and practices of classifying things or people. However, actors' work to escape dominant infrastructures and pre-established classification systems has received little attention. In response to this, this article argues that it is crucial to analyze, not only the practices and politics of classification, but also actors' work to escape dominant classification systems. The article has two aims: First, to make a theoretical contribution to the study of classification by proposing to pay analytical attention to practices of escaping classification, what the article dubs classification egress. This concept directs our attention not only to the practices and politics of classifying things, but also to how actors work to escape or resist classification systems in practice. Second, the article aims to increase our understanding of the history of quantified and statistical health surveillance. In this, the article investigates how actors in health surveillance assembled a knowledge infrastructure for surveilling, quantifying, and detecting unknown patterns of congenital malformations in the wake of the thalidomide disaster in the early 1960s. The empirical account centers on the actors' work to detect congenital malformations and escape the dominant nosological classification of diseases, the International Classification of Diseases (ICD), by replacing it with a procedural standard for reporting of symptoms. Thus, the article investigates how actors deal with the tension between the-already-known-and-classified and the unknown-unclassified-phenomenon in health surveillance practice.
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.