本报讯 记者方亮 王奇报道 1月6日，省委书记许昆林到省纪委监委机关和省委巡视办调研。他强调，要 深入学习贯彻习近平总书记关于党的建设的重要思想、关于党的自我革命的重要思想，全面贯彻落实习 近平总书记对辽宁的重要讲话和重要指示精神，提高政治站位，始终保持永远在路上的清醒坚定，忠诚 履行职责使命，主动担当作为，纵深推进全面从严治党，为我省"十五五"开好局、起好步提供坚强政治 保障。 许昆林来到辽宁省反腐倡廉展览馆，参观辽宁正风肃纪反腐展览，重温党的自我革命历程，回顾我省推 动党风廉政建设和反腐败斗争不断向纵深发展的做法、成效。他指出，全省上下要准确把握我们党勇于 自我革命的历史逻辑和实践要求，全面一体落实推进党的自我革命"五个进一步到位"重要要求，以更高 标准、更实举措推进全面从严治党，把严的基调、严的措施、严的氛围一贯到底，着力营造风清气正的 政治生态。在省纪委监委综合保障中心，许昆林看望慰问一线办案人员，希望大家保持忠诚干净担当政 治本色，坚持实事求是，敢于善于斗争，练就担当尽责的铁肩膀、硬脊梁、真本事，不断提高依规依纪 依法办案质效。他强调，全省各级纪检监察机关要发扬彻底的自我革命精神，持续加强纪检监察工 ...

强化数据集成，促进从"单一作战"向贯通协同跃升 中央纪委国家监委网站 石毅鹏 曹欢欢 湖北省十堰市纪委监委不断强化数字技术与纪检监察工作深度融合，有效提升监督质效。图为近日，该 市纪委监委工作人员运用大数据监督模型对模拟案例进行分析、推演。李芳 摄 习近平总书记强调，"运用大数据提升国家治理现代化水平""使大数据在各项工作中发挥更大作用"，要 求"用科技手段加强监督"，为在纵深推进全面从严治党和反腐败斗争中持续用好大数据等信息化技术指 明了前进方向。 12月8日，湖北省纪委监委举办2025年度数字化监督办案评比评选活动，通过数字化精品案例集中展示 和监督建模新技术应用现场评比，全面展示全省各地开展数字化监督办案的实践成果，引导纪检监察干 部适应数字化、智能化发展趋势，会用、善用大数据监督。 二十届中央纪委四次全会提出，以大数据信息化赋能正风反腐。湖北省纪委监委深入贯彻落实相关部署 要求，把强化科技支撑作为推动纪检监察工作高质量发展的重要抓手，持续深化数字纪检监察体系建 设，推动构建以大数据资源中心为支撑、以职能部门行业监管为前端、以纪检监察专责监督为后墙、监 督整改治理贯通发力的公权力大数据监督格局。市、县纪 ...

Core Viewpoint - The current focus of the Party's integrity and anti-corruption efforts is to address the intertwined issues of improper conduct and corruption, emphasizing the need for a mechanism that investigates both simultaneously and utilizes big data for enhanced effectiveness [1] Group 1: Implementation of Big Data in Supervision - The Central Commission for Discipline Inspection (CCDI) is actively exploring the use of big data and information technology to enhance the supervision and investigation of improper conduct and corruption [1][4] - A digital supervision platform has been established to monitor real-time data related to issues such as the improper acceptance of gifts, misuse of public funds for dining, and unauthorized travel [2][4] - Since the launch of the digital supervision platform in March 2023, it has identified 334 problem clues, including 260 related to violations of the Central Eight Regulations [4] Group 2: Case Studies and Findings - A case involving employees from a subsidiary company revealed violations related to gift-giving and fraudulent invoicing, highlighting the effectiveness of the data model in identifying risks [3][4] - The platform's data analysis capabilities allowed for the detection of irregularities in expense reports, leading to the identification of hidden corruption risks [3][10] - In another case, a public servant was found to have engaged in corrupt practices through collusion with external parties, resulting in disciplinary actions and legal consequences [7][10] Group 3: Systematic Approach to Addressing Issues - The approach to tackling improper conduct and corruption involves a systematic method that integrates the investigation of both issues, ensuring that each is addressed in conjunction with the other [5][8] - The establishment of a tiered warning mechanism allows for the classification of risks based on severity, facilitating targeted preventive measures [8][9] - The integration of big data technology enhances the ability to monitor and analyze trends in corruption, providing a basis for continuous improvement in governance and oversight [10][11]

Core Insights - The article emphasizes the use of big data and information technology to enhance supervision and governance in rural collective asset management in Hainan Province, addressing issues such as unclear financial status and management inefficiencies [2][4][20] Group 1: Implementation of "Machine Management" Systems - Hainan Province has implemented the "Machine Management of Bidding" system to combat corruption in public engineering projects, which has been operational since November 2022, with the first project successfully completed [4][6] - The system automates the qualification assessment of bidders and the evaluation process, significantly reducing human interference and increasing transparency [5][6] - As of October 10, 2023, the "Machine Management of Bidding" system has processed 1,832 projects with a total bidding amount of 1,487.72 billion yuan, saving 62.56 billion yuan [6] Group 2: Integration with Supervision Networks - The "Supervision One Network" connects various supervisory departments and enables cross-regional and cross-departmental oversight, enhancing the ability to detect and rectify issues in real-time [8][19] - The integration of the "Machine Management of Bidding" system with the "Supervision One Network" allows for proactive monitoring and intervention in bidding processes, effectively reducing the risk of corruption [8][9] Group 3: Expansion of "Machine Management" Applications - The article discusses the expansion of "Machine Management" applications beyond bidding to include areas such as procurement and rural collective asset management, aiming for comprehensive oversight [12][14] - Future initiatives include the "Machine Management of Prescriptions" and "Machine Management of Campus Meals," which leverage technology to enhance regulatory compliance in healthcare and education sectors [13][14] Group 4: Impact on Governance and Transparency - The implementation of these systems has led to a significant reduction in corruption cases related to engineering projects, with no reported instances of interference in the bidding process since the system's launch [10][19] - The use of technology has transformed the oversight process from a reactive to a proactive approach, ensuring that potential issues are identified and addressed before they escalate [9][20]

Core Viewpoint - The article emphasizes the importance of integrating digital technology into the disciplinary inspection and supervision system to enhance efficiency and effectiveness in combating corruption and ensuring accountability [6][18]. Group 1: Digital Integration in Supervision - Various local governments, including those in Shandong, Chongqing, and Jiangsu, are advancing the construction of digital disciplinary inspection systems, focusing on cultivating digital thinking and literacy among inspectors [19]. - The integration of digital technology into disciplinary inspection processes is seen as a crucial method for improving the quality of supervision and law enforcement [7][9]. - Establishing a comprehensive data resource center and a digital supervision application platform is essential for optimizing data collection, sharing, and analysis [9][10]. Group 2: Data Utilization and Analysis - The development of customized data models and analytical tools is being prioritized to enhance the precision and effectiveness of supervision [8][12]. - A closed-loop governance chain is being established to address issues identified through data analysis, ensuring timely feedback and corrective actions [11][13]. - The use of big data for real-time monitoring and early warning systems is being implemented to detect irregularities in various sectors, such as education and healthcare [12][18]. Group 3: Training and Capacity Building - There is a strong emphasis on enhancing the digital skills and awareness of disciplinary inspection personnel through targeted training programs [15][16]. - The establishment of a talent pool for digital supervision is aimed at fostering a collaborative environment between technical and operational teams [15][19]. - Practical training and real-case simulations are being utilized to improve the operational capabilities of inspectors in data analysis and electronic evidence collection [16][18].

Core Viewpoint - The article emphasizes the integration of digital technology into the disciplinary inspection and supervision system, highlighting the importance of big data in enhancing proactive and precise oversight in combating corruption and improving governance efficiency [5][17]. Group 1: Digital Supervision Initiatives - The Hunan Province's Hengyang City is advancing the construction of a digital disciplinary inspection and supervision system, integrating digital technology into various business operations [5]. - The Zhejiang Province's Yongkang City is exploring new paths for digital supervision of rural "three assets" management, aiming to enhance grassroots governance effectiveness [3][5]. Group 2: Data Utilization and Model Development - Hengyang City has established a big data resource center that connects core data from 23 units, facilitating proactive supervision by creating supervision models that identify risk points [6]. - A total of 223 public power big data supervision models have been developed in Jinhua City, generating 6,830 red alerts that have been properly addressed [7]. Group 3: Enhancing Supervision Efficiency - The article discusses the importance of using big data to transition from reactive to proactive supervision, allowing for early detection of potential issues [6][9]. - The establishment of a closed-loop management mechanism for supervision, which includes data acquisition, model creation, alert processing, and governance promotion, is emphasized [8][12]. Group 4: Training and Capacity Building - There is a focus on cultivating a professional team skilled in big data analysis to enhance the precision and effectiveness of disciplinary inspection and supervision [9][10]. - The article highlights the need for continuous training and the establishment of a mechanism for regular skill enhancement among supervisory personnel [10][14]. Group 5: Future Directions and Goals - The article outlines plans to further integrate data resources and optimize supervision models, aiming for deeper data fusion and smarter, more precise oversight mechanisms [14][15]. - The goal is to create a comprehensive digital supervision framework that covers all elements and processes, ensuring effective collaboration across departments and enhancing the overall efficiency of disciplinary inspection work [13][17].

Core Insights - The Central Commission for Discipline Inspection and the National Supervisory Commission held the first Smart Modeling Competition for supervision and case handling, with 161 entries from 88 units of the China National Petroleum Corporation (CNPC) [1] - The competition aimed to integrate smart technologies into disciplinary inspection and supervision, addressing challenges such as hidden bidding violations and large data processing [1][2] - The CNPC's disciplinary inspection team is advancing a digital supervision system, including a big data resource center and multiple digital platforms, to enhance governance efficiency [2] Group 1 - The competition focused on practical needs across 16 business areas, including oil and gas sales and procurement, utilizing data capture, machine learning, and natural language processing [1] - The initiative aims to shift supervision from a reactive to a proactive approach, enhancing the ability to identify issues through data analysis [1][2] - The CNPC is implementing a comprehensive digital disciplinary inspection system, with a plan for 2023-2027 to improve governance effectiveness [2] Group 2 - The competition serves as a training platform to build a high-quality talent pool in data application for disciplinary inspection [3] - Participants are encouraged to learn and apply big data analysis tools, enhancing their capabilities in supervision and investigation [3] - Future efforts will focus on practical application of developed models, promoting data integration across various supervisory functions [3][4]

Core Viewpoint - The article emphasizes the importance of strengthening grassroots supervision in Harbin, Heilongjiang Province, as a means to enhance governance effectiveness and ensure the implementation of policies at the community level [2][3]. Group 1: Grassroots Supervision - Grassroots supervision is identified as the "last mile" of national governance, crucial for promoting strict party governance and improving governance efficiency [2][3]. - Harbin's disciplinary inspection and supervision agencies are actively exploring methods to enhance the quality and effectiveness of grassroots supervision [2][3]. Group 2: Economic Impact - The development of greenhouse economies in rural areas has led to an average annual increase of 500,000 yuan for village collectives and created jobs for 20 villagers, each earning nearly 3,000 yuan per month [2]. - This initiative exemplifies how grassroots supervision can support the growth of rural collective economies and enhance the role of local party organizations [2]. Group 3: Supervision Mechanisms - Harbin's disciplinary inspection and supervision agencies are integrating resources and extending supervision to create a collaborative and efficient grassroots supervision system [4]. - The city has established 79 collaborative supervision zones to enhance the effectiveness of disciplinary inspections across 303 townships [5]. Group 4: Training and Capacity Building - The city is focused on improving the capabilities of grassroots disciplinary inspection and supervision personnel through targeted training programs [8][9]. - Over 14,000 grassroots inspectors have received training this year, emphasizing practical skills and knowledge sharing [9]. Group 5: Technology and Data Utilization - The implementation of "smart seals" has improved the management of village-level organizations, allowing for real-time tracking of approval processes [12]. - Harbin's disciplinary inspection agencies are leveraging big data to enhance the precision and effectiveness of grassroots supervision, creating a closed-loop management system for problem detection and resolution [13].

Group 1 - The core viewpoint emphasizes the integration of big data and information technology to enhance anti-corruption efforts and improve the quality of disciplinary inspection and supervision in Linyi City, Shandong Province [1][2][3] Group 2 - The construction of a digital disciplinary inspection and supervision system is supported by a data center that integrates 329 data sources, collecting 350 million data entries from various public resources and internal business data [1][2] - The platform development focuses on enhancing political, special, daily, and grassroots supervision, with tools like a political ecology monitoring platform and a big data supervision warning platform [2][3] Group 3 - The emphasis on intelligent supervision aims to counter increasingly covert corruption methods by utilizing a "cloud workstation" big data case handling platform and developing 90 analytical methods for supervision and investigation [3][4] - Professional development is prioritized, with training sessions and workshops aimed at improving the ability of disciplinary inspection personnel to effectively use big data in their work [3][4]