{"title":"通过大数据进行科学认识:从无知到洞察再到理解","authors":"María del Rosario Martínez-Ordaz","doi":"10.1177/27538699231176523","DOIUrl":null,"url":null,"abstract":"Here I argue that scientists can achieve some understanding of both the products of big data implementation as well as of the target phenomenon to which they are expected to refer—even when these products were obtained through essentially epistemically opaque processes. The general aim of the paper is to provide a road map for how this is done; going from the use of big data to epistemic opacity (Sec. 2), from epistemic opacity to ignorance (Sec. 3), from ignorance to insights (Sec. 4), and finally, from insights to understanding (Sec. 5, 6)","PeriodicalId":147349,"journal":{"name":"Possibility Studies & Society","volume":"26 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Scientific understanding through big data: From ignorance to insights to understanding\",\"authors\":\"María del Rosario Martínez-Ordaz\",\"doi\":\"10.1177/27538699231176523\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Here I argue that scientists can achieve some understanding of both the products of big data implementation as well as of the target phenomenon to which they are expected to refer—even when these products were obtained through essentially epistemically opaque processes. The general aim of the paper is to provide a road map for how this is done; going from the use of big data to epistemic opacity (Sec. 2), from epistemic opacity to ignorance (Sec. 3), from ignorance to insights (Sec. 4), and finally, from insights to understanding (Sec. 5, 6)\",\"PeriodicalId\":147349,\"journal\":{\"name\":\"Possibility Studies & Society\",\"volume\":\"26 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-06-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Possibility Studies & Society\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1177/27538699231176523\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Possibility Studies & Society","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1177/27538699231176523","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Scientific understanding through big data: From ignorance to insights to understanding
Here I argue that scientists can achieve some understanding of both the products of big data implementation as well as of the target phenomenon to which they are expected to refer—even when these products were obtained through essentially epistemically opaque processes. The general aim of the paper is to provide a road map for how this is done; going from the use of big data to epistemic opacity (Sec. 2), from epistemic opacity to ignorance (Sec. 3), from ignorance to insights (Sec. 4), and finally, from insights to understanding (Sec. 5, 6)