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大数据驱动下的政府治理机制研究——基于2020年后精准扶贫领域的返贫阻断分析
引用本文:刘泽,陈升.大数据驱动下的政府治理机制研究——基于2020年后精准扶贫领域的返贫阻断分析[J].重庆大学学报(社会科学版),2020,26(5):216-229.
作者姓名:刘泽  陈升
作者单位:清华大学 公共管理学院, 北京 100084;重庆大学 公共管理学院, 重庆 400044
基金项目:国家社会科学基金重点项目"我国中长期规划决策机制及方法论研究:基于五年规划实施绩效视角"(15AZD016);自然科学基金项目"高效减灾与重建:灾害冲击与灾后重建绩效的影响因素及其作用机制研究——基于灾害周期的视角"(71473022)
摘    要:大数据时代已经到来,大数据驱动下的政府治理发生何种改变,目前相关研究较少。当前政府治理的考验集中在2020年实现全面脱贫后精准扶贫领域的返贫阻断。文章以该领域为切入点,探索大数据驱动下政府治理的内在机制。研究发现:大数据背景下,政府治理能力催生出新的核心能力,即数据治理能力。数据治理能力驱动下,政府治理主体多元化有利于实现政府治理资源的宽范围、精准化动员;政府治理方式实现经验式决策向数据化决策转变,有利于实现政府资源的高效率和公平配置;政府治理客体的精准识别,有利于政府资源的精准化和最优化运用。但是客观上必须具备数据治理能力,主观上必须按照大数据驱动的要求重构政府治理体系(包括治理主体、治理方式和治理客体),才能真正实现以数据治理驱动政府治理,进而提高政府治理能力的目的。而数据治理能力客观上也加速了政府治理体系的重构,进而加快了政府治理能力的提升,并最终提高政府治理绩效。在对标大数据应用不同阶段分析常规式返贫阻断和大数据返贫阻断的不足和差距的基础上,笔者提出重构政府治理体系和提升数据治理能力等针对性建议。

关 键 词:大数据  政府治理  治理体系  治理能力  数据治理能力  精准扶贫  全面脱贫  返贫阻断
修稿时间:2020/1/16 0:00:00

Research of government governance under the driven of big data: Take the prevention of poverty return in the field of targeted poverty alleviation after 2020 as an example
LIU Ze,CHEN Sheng.Research of government governance under the driven of big data: Take the prevention of poverty return in the field of targeted poverty alleviation after 2020 as an example[J].Journal of Chongqing University(Social Sciences Edition),2020,26(5):216-229.
Authors:LIU Ze  CHEN Sheng
Institution:School of Public Management, Tsinghua University, Beijing 100084, P. R. China; School of Public Affairs, Chongqing University, Chongqing 400044, P. R. China
Abstract:Big data age is coming. What changes will happen to government governance under the driven of big data? There are few studies. The current test of government governance focuses on the prevention of poverty return in the field of targeted poverty alleviation. Based on this perspective, this paper explores the internal mechanism of government governance driven by big data. The study finds that: under the background of big data, the government''s governance ability has spawned new core competence, namely data management ability. Diversification of government governance subjects is beneficial to realize the wide range and precision mobilization of government governance resources. The change from empirical decision-making to data decision-making is beneficial to realize the high efficiency and fair allocation of government resources. The precise identification of object of government governance is conducive to the accurate and optimal use of government resources. Objectively, we must have the ability of data governance. Subjectively, we must reconstruct the government governance system (including governance subject, governance mode and governance object) according to the requirements of big data driving. Only in this way can we truly realize the purpose of data governance driving government governance and improve the government governance ability. Objectively, data management ability can accelerate the reconstruction of the government governance system, then accelerate the improvement of government governance capacity and finally improve governance performance. Based on the analysis of the deficiencies and gaps between conventional and big data prevention of poverty return according to the different stages of big data application, some targeted suggestions such as reconstruction of government governance system and improvement of data governance capability are put forward.
Keywords:big data  government governance  management system  management capacity  data management ability  take targeted measures to help people lift themselves out of poverty  comprehensive poverty alleviation  prevention of poverty return
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