[论文解读] The fallacy of evidence based policy

Andrea Saltelli, Mario Giampietro|RePEc: Research Papers in Economics|May 25, 2015

Complex Systems and Decision Making被引用 7

一句话总结

本文批判了基于证据的政策是一种 flawed（有缺陷的）方法，其根源在于过度简化的科学叙事，这些叙事歪曲了复杂的社会与环境挑战。本文提出以‘稳健政策’（robust policy）替代基于证据的政策——一种在多个规范性与系统性维度上评估可行性、可行性和可取性的框架，以增强在不确定性面前的韧性。

ABSTRACT

The use of science for policy is at the core of a perfect storm generated by the insurgence of several concurrent crises: of science, of trust, of sustainability. The modern positivistic model of science for policy, known as evidence based policy, is based on dramatic simplifications and compressions of available perceptions of the state of affairs and possible explanations (hypocognition). This model can result in flawed prescriptions. The flaws become more evident when dealing with complex issues characterized by concomitant uncertainties in the normative, descriptive and ethical domains. In this situation evidence-based policy may concur to the fragility of the social system. Science plays an important role in reducing the feeling of vulnerability of humans by projecting a promise of protection against uncertainties. In many applications quantitative science is used to remove uncertainty by transforming it into probability, so that mathematical modelling can play the ritual role of haruspices. This epistemic governance arrangement is today in crisis. The primacy of science to adjudicate political issues must pass through an assessment of the level of maturity and effectiveness of the various disciplines deployed. The solution implies abandoning dreams of prediction, control and optimization obtained by relying on a limited set of simplified narratives to define the problem and moving instead to an open exploration of a broader set of plausible and relevant stories. Evidence based policy has to be replaced by robust policy, where robustness is tested with respect to feasibility (compatibility with processes outside human control); viability (compatibility with processes under human control, in relation to both the economic and technical dimensions), and desirability domain (compatibility with a plurality of normative considerations relevant to a plurality of actors).

研究动机与目标

• 挑战基于证据的政策主导范式，因其过度简化，无法充分应对复杂的社会与环境问题。
• 揭示将科学知识简化为可量化证据的过程，如何在规范性、描述性与伦理不确定性面前削弱政策的韧性。
• 主张当前的科学服务于政策的模式，助长了对预测模型与概率框架的错误信任，加剧了系统的脆弱性。
• 倡导从预测与优化转向对多种可能叙事的开放性探索。
• 建立一种新的政策框架——稳健政策，该框架基于在多元利益相关者视角下对可行性、可行性和可取性的综合评估。

提出的方法

• 围绕三个维度重构政策制定：可行性（外部不可控过程）、可行性（人类可控的经济与技术过程）和可取性（多元规范性价值）。
• 拒绝将概率建模作为真实理解的仪式性替代品，尤其是在高不确定性的情境中。
• 引入‘伪认知’（hypocognition）概念——即无意识地将复杂现实简化为狭窄而易处理的叙事。
• 倡导一种多元化的政策设计方法，纳入多种非量化的叙事，而非优先考虑统计证据。
• 运用哲学与系统理论，批判将科学视为政策决策唯一仲裁者的认识论治理模式。
• 通过在多个韧性标准下系统评估政策选项，推动从基于证据的政策向稳健政策的转型。

实验结果

研究问题

• RQ1 为何基于证据的政策无法应对复杂政策领域中的系统性不确定性？
• RQ2 将科学知识简化为证据的过程如何导致政策脆弱性？
• RQ3 在政策决策中，使用概率建模管理不确定性的局限性是什么？
• RQ4 如何使政策具备稳健性，而非依赖预测准确性或优化？
• RQ5 评估可行性、可行性和可取性领域中政策稳健性所需的准则是什么？

主要发现

• 基于证据的政策依赖于伪认知——过度简化的叙事——这扭曲了复杂现实，加剧了系统性脆弱性。
• 科学在政策制定中的主导地位因当前科学可信度、信任度与可持续性的危机而受到削弱。
• 定量科学常常以概率替代不确定性，通过仪式化的建模制造出虚假的控制感。
• 稳健政策必须在三个维度上进行评估：可行性（外部过程）、可行性（内部人类控制的系统）和可取性（多元价值）。
• 从基于证据的政策转向稳健政策，需要放弃对预测与控制的幻想，转而探索更广泛的一系列可能叙事。
• 所提出的框架通过在统一评估过程中整合多元规范性、技术性与经济性考量，增强了政策的韧性。