The first task for eradicating poverty is accurate poverty identification. Deep poverty identification is conducive to investing resources to help deeply poor populations achieve prosperity, one of the most challenging tasks in poverty eradication. This study constructs a deep poverty identification model utilizing explainable artificial intelligence (XAI) to identify deeply poor households based on the data of 23,307 poor households in rural areas in China. For comparison, a logistic regression-based model and an income-based model are developed as well. We found that our XAI-based model achieves a higher identification performance in terms of the area under the ROC curve than both the logistic regression-based model and the income-based model. For each rural household, the odds of being identified as deeply poor are obtained. Additionally, multidimensional household characteristics associated with deep poverty are specified and ranked for each poor household, while ordinary feature ranking methods can only provide ranking results for poor households as a whole. Taking all poor households into consideration, we found that common important characteristics that can be used to identify deeply poor households include household income, disability, village attributes, lack of funds, labor force, disease, and number of household members, which are validated by mutual information analysis. In conclusion, our XAI-based model can be used to identify deep poverty and specify key household characteristics associated with deep poverty for individual households, facilitating the development of new targeted poverty reduction strategies.

基于2019年中国东部3省和中西部22省(市、区)建档立卡实地监测调研数据,明确建档立卡户主要的致贫原因和帮扶措施,并以致贫原因为参照,运用交互信息分析技术评估了帮扶措施的精准性,提出精准扶贫的改进措施.结果表明:首先,贫困户致贫原因类型多样,当前缺技术是贫困户致贫的首要原因,缺资金是第二重要的原因,因病致贫为第三重要的原因.其次,健康扶贫和产业扶贫是最主要的帮扶措施.最后,现有帮扶措施整体上看较精准,但教育扶贫和金融扶贫的精准性有待提高.建议进一步加强致贫原因和帮扶措施的关联分析,提高帮扶措施的精准性,巩固脱贫攻坚成效,转向相对贫困治理.

电商扶贫是脱贫攻坚的重要举措,电商扶贫农产品销售额屡创新高,对扶贫农产品的食品安全监管亟需重视.在脱贫攻坚背景下,贫困地区基层政府克服基础设施与公共服务相对落后的困难,创造性地采取促进型模式对扶贫农产品进行监管,呈现出监管动机一致性、监管工具平台化、监管过程相促进的特征.本文基于实地调研选取了四个案例对促进型监管模式中顾问式、培育式、动员式、教练式四种典型形式进行比较分析,丰富和发展了促进型监管研究.

基于2019年25省(区、市)建档立卡实地监测调研的贫困户数据,建立基于逻辑回归方法的贫困风险预测模型,评估返贫风险.运用优势比和交互信息,分析各致贫因素对返贫风险预测的影响,结果表明:预测模型的ROC曲线下面积达到0.706,模型可用于预测返贫的风险.在解决相对贫困问题阶段,应针对返贫风险高的家庭加强贫困风险预测研究;创新发展基于"预警+救助+赋能"的扶贫策略;在实施保障救助的同时,加强致贫因素分析,采取有针对性的扶贫措施,防止返贫发生.

<span id="ChDivSummary" name="ChDivSummary" class="abstract-text">作为我国扶贫开发"六大工作机制"之一,干部驻村帮扶在打赢脱贫攻坚战中发挥了重要的抓手作用。本文基于在陕甘宁深度贫困地区采集的2万多建档立卡贫困户数据建立回归模型进行实证分析,从第一书记的个人特征、人力资本、派出单位层级、村庄资源禀赋以及贫困户属性等因素入手,验证第一书记贫困治理的"先锋"角色和派出单位的"后盾"作用。本文发现:（1）第一书记派出单位层级和职务职级越高越有助于提升贫困治理绩效;（2）第一书记年龄越大、学历越高则贫困治理绩效越低。本文为考察第一书记驻村帮扶提供了一个"先锋"与"后盾"的互动视角,并在实证分析中优化了贫困治理绩效评价方法,研究结论和政策启示有助于完善第一书记选派制度,提升第一书记选派精准度和匹配度,从而提高干部驻村帮扶绩效。本文的局限在于缺少对贫困治理绩效进行动态分析以及对第一书记有关个体特征的控制,这是后续需要予以关注的方面。</span>