数据密集型社会科学中的分配性认知非正义  

Distributive Epistemic Injustice in Data-intensive Social Science

作　　者：白惠仁[1] 郭卓睿 BAI Hui-ren;GUO Zhuo-rui(School of Philosophy,Zhejiang University,Hangzhou 310058,China)

机构地区：[1]浙江大学哲学学院,杭州310058

出　　处：《自然辩证法研究》2025年第1期85-92,共8页Studies in Dialectics of Nature

基　　金：2024年度浙江省哲学社会科学规划之江青年专项课题(24ZJQN012Y);国家社会科学基金青年项目“当代科学中的认知非正义问题研究”(22CZX026)。

摘　　要：在当代数据密集型社会科学研究中,大数据已成为社会科学知识生产中重要的认知益品。然而,私人企业对个人数据的控制和商业化导致了大数据资源的不平等分配,社会经济地位较高的社会科学研究者和研究机构更易获取数据,造成社会科学共同体内的分配性认知非正义,从而加剧了学术不平等并限制了社会科学研究的多样性。鉴于此,已与数据企业建立深度合作的资深学者们应该承担相关的集体认知责任,成为企业与社会科学共同体之间值得信赖的第三方,以应对大数据分配的非正义。In contemporary data-intensive social science research,big data has emerged as a critical epistemic good for knowledge production.However,the privatization and commercialization of personal data by private corporations have exacerbated unequal distribution of big data resources.Researchers and institutions with higher socioeconomic status often enjoy privileged access to these resources,leading to distributive epistemic injustice within the social science community.This disparity exacerbates academic inequalities and limits the diversity of social science research.To address this issue,senior academics who have established deep collaborations with data corporations should assume collective epistemic responsibility.They can serve as a trusted intermediaries between corporations and the social science community to mitigate distributive injustice of big data.

关 键 词：数据密集型社会科学 分配性认知非正义 集体认知责任 

分 类 号：N031[自然科学总论—科学技术哲学]