科学劳动分工测度研究综述

doi:10.3772/j.issn.1000-0135.2025.09.010

情报学报

2025, Vol. 44

Issue (9): 1204-1216 DOI: 10.3772/j.issn.1000-0135.2025.09.010

情报综述与述评

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科学劳动分工测度研究综述

田雪灿^1,2,3, 陈莉玥^1,2, 丁洁兰^1,2

1.中国科学院文献情报中心，北京 100190
2.中国科学院大学经济与管理学院信息资源管理系，北京 100190
3.武汉大学信息管理学院，武汉 430072

Review on Division of Labor in Scientometrics

Tian Xuecan^1,2,3, Chen Liyue^1,2, Ding Jielan^1,2

1.National Science Library, Chinese Academy of Sciences, Beijing 100190
2.Department of Information Resources Management, School of Economics and Management, University of Chinese Academy of Sciences, Beijing 100190
3.School of Information Management, Wuhan University, Wuhan 430072

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摘要科学合作是科研人员开展研究活动的重要模式，科学劳动分工作为科研合作的基础，对优化团队组织、提升科研效率和完善贡献评价机制具有重要意义。本文对科学计量学领域科学劳动分工的分类、识别与应用相关研究进行系统性梳理，为后续研究提供脉络参考。首先，本文从科学劳动分工的分类框架出发，系统调研和梳理了学术组织、学术期刊、研究学者所提出的劳动分工分类方式；其次，梳理了科学劳动分工的识别方法，分为基于小规模数据的人工识别方法和基于大规模数据的自动识别方法两个层面；再其次，从分布特征、结构和效用研究3个层面对科学劳动分工的应用研究进行梳理和评述；最后，论述人工智能作为新型劳动分工主体的前沿趋势。研究结果表明，现有科学劳动分工分类框架较为零散，以面向应用场景为主，缺乏系统理论研究；劳动分工识别方法逐步从人工标注转向文本挖掘与机器学习，但应用大语言模型的研究相对较少；在应用研究上，已有研究主要停留在特征揭示层面，科学劳动分工的组织模式及其效应研究相对较少。此外，人工智能作为新型分工主体引发了关于科研合作模式的全新思考。

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	田雪灿
	陈莉玥
	丁洁兰

关键词 ：劳动分工, 科学合作, 科学计量学, 团队科学, 人工智能

收稿日期: 2025-03-04

基金资助:国家社会科学基金一般项目“地域与文化复合视角下的国际合作测度方法研究”（23BTQ103）。

作者简介: 田雪灿，女，2000年生，博士研究生，主要研究方向为科学计量学、文本挖掘；陈莉玥，女，1992年生，博士，助理研究员，主要研究方向为科学计量学、学术文本量化；丁洁兰，通信作者，女，1987年生，博士，副研究员，硕士生导师，主要研究方向为科学计量学、科技文献数据内容治理挖掘，E-mail：dingjielan@mail.las.ac.cn；

引用本文:

田雪灿, 陈莉玥, 丁洁兰. 科学劳动分工测度研究综述[J]. 情报学报, 2025, 44(9): 1204-1216.
Tian Xuecan, Chen Liyue, Ding Jielan. Review on Division of Labor in Scientometrics. 情报学报, 2025, 44(9): 1204-1216.

链接本文:

https://qbxb.istic.ac.cn/CN/10.3772/j.issn.1000-0135.2025.09.010 或 https://qbxb.istic.ac.cn/CN/Y2025/V44/I9/1204

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