[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"item-2513":3},{"id":4,"title":5,"url":6,"summary":7,"summary_zh":8,"content":9,"source_name":10,"source_url":6,"published_at":11,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":15,"score_detail":16,"sources":24,"tags":26,"view_count":32,"doi":33,"paper":34,"created_at":47},2513,"Mining Externalities and Climate-Smart Agriculture Portfolios: Evidence from Mining-Affected Communities in Ghana","https:\u002F\u002Fdoi.org\u002F10.20944\u002Fpreprints202609.1089.v1","This study examines how mining-related environmental pressure is associated with the breadth and composition of climate-smart agriculture (CSA) portfolios among 485 farming households in Tarkwa Nsuaem and Prestea Huni Valley, Ghana. We develop an adaptation-paradox framework in which environmental stress may strengthen incentives to adopt risk-mitigating practices while severe degradation may simultaneously reduce expected returns and implementation capacity. Because CSA adoption is almost universal in the sample, the analysis focuses on portfolio breadth, complete seven-practice adoption, and practice composition rather than a nearly degenerate adopter\u002Fnon-adopter outcome. The empirical strategy combines fractional-response estimation, stacked practice-level logit models, nonlinear specifications, alternative exposure measures, small-cluster robustness checks, Double Machine Learning, and repeated nested cross-validation. In the fully adjusted fractional-logit model with community fixed effects, the average marginal association between the core Mining Externality Severity Index (MESI) and CSA portfolio share is close to zero and imprecisely estimated (AME = -0.003; 95% CI: -0.175 to 0.169). However, MESI relationships differ jointly across the seven practices, nonlinear specifications suggest possible non-monotonicity, and results vary with the definition of mining pressure. Gradient Boosting predicts complete portfolios with a mean ROC-AUC of 0.907, while community context contains substantially more predictive information than MESI alone. Overall, the evidence supports a portfolio-based, practice-specific, and place-sensitive interpretation of adaptation rather than a universal positive or negative relationship between mining pressure and CSA adoption.","本研究考察了加纳塔克瓦恩苏阿姆（Tarkwa Nsuaem）和普雷斯蒂亚胡尼谷（Prestea Huni Valley）485个农户中，采矿相关环境压力与气候智能型农业（climate-smart agriculture, CSA）组合的广度和构成之间的关联。我们构建了一个适应悖论框架，其中环境压力可能强化采取风险缓解措施的激励，而严重退化则可能同时降低预期收益和实施能力。由于样本中CSA采用几乎普遍存在，分析聚焦于组合广度、七项实践完全采用以及实践构成，而非近乎退化的采用者\u002F非采用者结果。实证策略结合了分数响应估计、堆叠实践层面logit模型、非线性设定、替代暴露测量、小聚类稳健性检验、双重机器学习以及重复嵌套交叉验证。在纳入社区固定效应的完全调整分数logit模型中，核心采矿外部性严重程度指数（Mining Externality Severity Index, MESI）与CSA组合份额之间的平均边际关联接近于零且估计不精确（AME = -0.003；95% CI：-0.175至0.169）。然而，MESI关系在七项实践之间联合存在差异，非线性设定提示可能存在非单调性，且结果随采矿压力定义的不同而变化。梯度提升（Gradient Boosting）预测完整组合的平均ROC-AUC为0.907，而社区背景所包含的预测信息显著多于仅MESI。总体而言，证据支持基于组合、实践特定且地点敏感的适应解释，而非采矿压力与CSA采用之间存在普遍正向或负向关系。",null,"Preprints.org","2026-09-14T00:00:00Z","论文",10,false,60,{"impact":17,"substance":18,"depth":19,"authority":20,"freshness":21,"relevant":22,"comment":23},8,20,17,6,9,1,"方法扎实、结论审慎的加纳矿区农户CSA组合研究，但属境外微观实证，公共影响有限，适合主题聚合而非每日精选。",[25],{"name":10,"url":6},[27,28,29,30,31],"机器学习","气候智慧型农业","加纳","采矿影响","农户适应",0,"10.20944\u002Fpreprints202609.1089.v1",{"doi":33,"openalex_id":35,"authors":36,"venue":10,"cited_by_count":32,"oa_url":6,"card":39,"direction":45,"ingested_from":46},"W7212844665",[37],{"name":38,"orcid":9},"Isaac Dasmani",{"tldr":40,"method":41,"finding":42,"direction":43,"opportunity":44},"研究加纳矿区农户气候智慧型农业组合的广度与构成，发现采矿压力与CSA组合无统一关系。","485户调查，分数响应、堆叠logit、双机器学习与梯度提升。","MESI与CSA组合份额关联近零，但各实践间关系异质且可能非线性，社区背景预测力更强。","农业绿色发展与碳","可探究环境压力下CSA组合的非线性阈值与社区情境调节机制，发展实践特定适应理论。","智慧农业 \u002F 农业物联网","openalex","2026-09-15T23:30:08.672095Z"]