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作 者:吕鹏[1,2] 陈典涵 Lv Peng;Chen Dianhan
机构地区:[1]中南大学公共管理-自动化-法学院、社会计算研究中心,湖南长沙410083 [2]北京大学武汉人工智能研究院 [3]中南大学公共管理学院社会学系,湖南长沙410083
出 处:《南开学报(哲学社会科学版)》2025年第1期45-60,共16页Journal of Nankai university Philosophy,Literature and Social Science Edition
基 金:国家社会科学基金重大项目(24ZDA91);北京市社会科学基金一般项目(16SRB014);中央引导地方科技发展专项项目(2023EGA035)“;东湖高新区国家智能社会治理实验综合基地”项目。
摘 要:社会科学研究核心任务之一是“通过社会现象研究社会本质”,即从社会现象(实证研究资料)中获取对社会本质的知识过程。在此知识实践过程中,出现了两个方向的分野。一是典型性研究,以微观过程与深度分析为核心特征(解剖一只麻雀),侧重行动与过程分析;二是代表性研究,以局部对总体的推广性、代表性为要求,侧重结构性分析,核心是追求等价性。从典型性到等价性,不同的方法存在各异的二元属性权重配置,现有方法集合形成了一个谱系生态相位图。相关方法的理论效力与相对位势分析,部分得到了1998—2024中文CSSCI数据库的科研大数据的实证支撑。智能体模拟(ABM)能够兼顾研究的典型性、代表性,有机整合并均衡两个维度的知识生产能力,助力社会行动—结构对流分析。方法系统不是一成不变,存在演化的动力学逻辑。展望未来,随着新技术持续涌现,研究方法必将走向新的生态,助力社会科学的知识生产与高质量发展。A central objective in social science research is to“understand the essence of society through social phenomena”,that is,to derive knowledge of the social essence from empirical data.In this process of knowledge generation,two distinct methodological approaches emerge.The first,typicality,emphasizes micro-level processes and in-depth analysis,often through case studies that explore actions and processes(e.g.,“dissecting a sparrow”).The second,representativeness,focuses on generalizing findings from local contexts to the broader population,prioritizing structural analysis,with the core focus on pursuing equivalence.These two approaches–typicality and representativeness–are not mutually exclusive but represent different weightings of binary attributes in research methods.Consequently,they form a methodological ecosystem,represented as a spectrum and phase diagram.The theoretical effectiveness and potential of these methods have been partially validated through empirical evidence derived from the Chinese CSSCI database(1998-2024).Agent-based modeling(ABM)offers a way to reconcile the tension between typicality and representativeness,effectively integrating and balancing both dimensions in knowledge production.Furthermore,the methodological system is dynamic,evolving according to the logic of evolutionary dynamics.Looking ahead,the continuous emergence of new technologies will likely reshape the research methods landscape,fostering the development of an innovative ecosystem that supports the high-quality advancement of social science knowledge.
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