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arXiv 2608.15101cs.AI

作为状态转移的二阶政策效应:用于政策模拟的源关联基准

Second-Order Policy Effects as State Transitions: A Source-Linked Benchmark for Policy Simulation

Wesley Shu

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中文总结 AI 辅助

该研究提出源关联政策模拟基准,构建副作用模拟器,其平均政策效应质量优于两类基准,证明转移状态变量可提升政策模拟器对下游制度效应的敏感性。

中文摘要 AI 辅助

政策评估通常估算直接收益与成本,同时将制度环境视为固定不变。而在实际中,一项政策会改变其作用的系统:行动者会适应调整、执行能力会发生变化、负担会转移,还会围绕俘获、博弈、合规表演、不可逆性以及修复成本形成新的均衡。我们将此形式化为二阶政策效应预测,并提出一种用于政策模拟的源关联基准。该基准包含8个领域、4类平衡行动(实施、修改、试点、弃权(不执行))下的96个命名公共政策案例。每个案例都包含源定位符,以及收益、俘获、博弈、负担转移、不稳定性、不确定性、不可逆性、分配风险和执行能力的状态变量。运行器会从案例表中重新生成方法输出与汇总结果,而模拟器不会读取专家行动目标。我们报告了基于协议的转移通道审计,包含召回率、精确率、F1式效率以及选择性顶部通道压力诊断,因此不会将通用通道覆盖误判为现场验证。该副作用模拟器的平均政策效应质量为0.945,相比风险注册基准的0.838和因果循环基准的0.879更高。其优势集中在副作用召回率和汇总转移评分上;在精确政策行动选择上,它并不优于最佳结构化基准。该证据仍基于基准,但支持一个有限主张:转移状态变量能让政策模拟器对下游制度效应更敏感。

英文摘要

Policy evaluation often estimates direct benefits and costs while treating the institutional environment as fixed. In practice, a policy changes the system it enters: actors adapt, enforcement capacity shifts, burdens move, and new equilibria form around capture, gaming, compliance theater, irreversibility, and repair costs. We formalize this as second-order policy-effect prediction and present a source-linked benchmark for policy simulation. The benchmark contains 96 named public-policy cases across eight domains and four balanced action classes: implement, modify, pilot, and block. Each case includes source locators and state variables for benefit, capture, gaming, burden shift, instability, uncertainty, irreversibility, distributional risk, and implementation capacity. The runner regenerates method outputs and aggregate results from the case table, and the simulator never reads the expert action target. We report a protocol-based transition-channel audit with recall, precision, F1-style efficiency, and selective top-channel stress diagnostics, so universal channel coverage is not mistaken for field validation. The side-effect simulator achieves mean policy-effect quality of 0.945, compared with 0.838 for the risk-register baseline and 0.879 for the causal-loop baseline. Its advantage is concentrated in side-effect recall and aggregate transition scoring; it does not dominate the best structured baselines on exact policy-action choice. The evidence remains benchmark-based, but supports a bounded claim: transition-state variables make policy simulators more sensitive to downstream institutional effects.

发表机构

  • The Institute of Energetic Paradigm(能量范式研究所)

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