{"title":"如何衡量跨学科研究?衡量模型的系统设计","authors":"Giulio Giacomo Cantone","doi":"10.1007/s11192-024-05085-1","DOIUrl":null,"url":null,"abstract":"<p>Interdisciplinarity is a polysemous concept with multiple, reasoned and intuitive, interpretations across scholars and policy-makers. Historically, quantifying the interdisciplinarity of research has been challenging due to the variety of methods used to identify metadata, taxonomies, and mathematical formulas. This has resulted in considerable uncertainty about the ability of quantitative models to provide clear insights for policy-making. This study proposes a systemic design, grounded in an advanced literature review, to demonstrate that the quantification of the interdisciplinarity of research can be treated as a process of decision-making in mathematical modelling, where alternatives choices are evaluated based on how closely their mathematical properties align with the theoretical objectives of the research design. The study addresses modeling choices regarding the stylisation of metadata into units of observation, and the operational definition of the conceptual dimensions of interdisciplinarity, presenting both established and novel methods and formulas. The final section discusses advanced topics in modelling the measurement, including a dedicated discussion on the difference in analysing the status of papers versus collective bodies of research; and distinguishing between reflective, formative, and inferential causal models of interdisciplinary research.</p>","PeriodicalId":21755,"journal":{"name":"Scientometrics","volume":"7 1","pages":""},"PeriodicalIF":3.5000,"publicationDate":"2024-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"How to measure interdisciplinary research? A systemic design for the model of measurement\",\"authors\":\"Giulio Giacomo Cantone\",\"doi\":\"10.1007/s11192-024-05085-1\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>Interdisciplinarity is a polysemous concept with multiple, reasoned and intuitive, interpretations across scholars and policy-makers. Historically, quantifying the interdisciplinarity of research has been challenging due to the variety of methods used to identify metadata, taxonomies, and mathematical formulas. This has resulted in considerable uncertainty about the ability of quantitative models to provide clear insights for policy-making. This study proposes a systemic design, grounded in an advanced literature review, to demonstrate that the quantification of the interdisciplinarity of research can be treated as a process of decision-making in mathematical modelling, where alternatives choices are evaluated based on how closely their mathematical properties align with the theoretical objectives of the research design. The study addresses modeling choices regarding the stylisation of metadata into units of observation, and the operational definition of the conceptual dimensions of interdisciplinarity, presenting both established and novel methods and formulas. The final section discusses advanced topics in modelling the measurement, including a dedicated discussion on the difference in analysing the status of papers versus collective bodies of research; and distinguishing between reflective, formative, and inferential causal models of interdisciplinary research.</p>\",\"PeriodicalId\":21755,\"journal\":{\"name\":\"Scientometrics\",\"volume\":\"7 1\",\"pages\":\"\"},\"PeriodicalIF\":3.5000,\"publicationDate\":\"2024-07-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Scientometrics\",\"FirstCategoryId\":\"91\",\"ListUrlMain\":\"https://doi.org/10.1007/s11192-024-05085-1\",\"RegionNum\":3,\"RegionCategory\":\"管理学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Scientometrics","FirstCategoryId":"91","ListUrlMain":"https://doi.org/10.1007/s11192-024-05085-1","RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
How to measure interdisciplinary research? A systemic design for the model of measurement
Interdisciplinarity is a polysemous concept with multiple, reasoned and intuitive, interpretations across scholars and policy-makers. Historically, quantifying the interdisciplinarity of research has been challenging due to the variety of methods used to identify metadata, taxonomies, and mathematical formulas. This has resulted in considerable uncertainty about the ability of quantitative models to provide clear insights for policy-making. This study proposes a systemic design, grounded in an advanced literature review, to demonstrate that the quantification of the interdisciplinarity of research can be treated as a process of decision-making in mathematical modelling, where alternatives choices are evaluated based on how closely their mathematical properties align with the theoretical objectives of the research design. The study addresses modeling choices regarding the stylisation of metadata into units of observation, and the operational definition of the conceptual dimensions of interdisciplinarity, presenting both established and novel methods and formulas. The final section discusses advanced topics in modelling the measurement, including a dedicated discussion on the difference in analysing the status of papers versus collective bodies of research; and distinguishing between reflective, formative, and inferential causal models of interdisciplinary research.
期刊介绍:
Scientometrics aims at publishing original studies, short communications, preliminary reports, review papers, letters to the editor and book reviews on scientometrics. The topics covered are results of research concerned with the quantitative features and characteristics of science. Emphasis is placed on investigations in which the development and mechanism of science are studied by means of (statistical) mathematical methods.
The Journal also provides the reader with important up-to-date information about international meetings and events in scientometrics and related fields. Appropriate bibliographic compilations are published as a separate section. Due to its fully interdisciplinary character, Scientometrics is indispensable to research workers and research administrators throughout the world. It provides valuable assistance to librarians and documentalists in central scientific agencies, ministries, research institutes and laboratories.
Scientometrics includes the Journal of Research Communication Studies. Consequently its aims and scope cover that of the latter, namely, to bring the results of research investigations together in one place, in such a form that they will be of use not only to the investigators themselves but also to the entrepreneurs and research workers who form the object of these studies.