RCN: Coordinating and Advancing Analytical Approaches for Policy Design

有效的治理取决于个人如何解释和回应公共政策，这些政策由精心设计的语言组成，传达谁可以做什么、何时做什么以及如何做。充分理解公共政策设计和行为之间的联系需要两个相辅相成的进步。首先，科学家必须促进就研究政策设计的普遍和可靠方法的发展进行智力交流。其次，这些科学家必须与其他人协调，这些人专注于评估行为是如何响应政策设计的，或者有时是伴随着政策设计出现的。在前一种情况下，政策设计学者面临着一种取舍，一种是详细的小样本案例研究，捕捉特定背景下的细微差别，另一种是大样本研究，后者未能抓住细微差别，但对政策和背景进行概括。在后一种情况下，行为科学家面临着一系列不同的挑战。行为科学家对个体如何解释和回应嵌入在政策设计中的特定指令有了深入的理解，但对不同指令组合的行为反应，或者政策设计和行为是如何共同进化的，提供的见解很少。与专注于描述公共政策语言特征的政策设计学者交流见解，使行为科学家能够有效地应对此类问题。这个研究协调网络(RCN)发起了一个由政策设计学者和行为科学家组成的跨学科和国际网络，以利用和整合他们的见解，以更好地理解政策设计和行为之间的相互作用。为支持这一目标，区域协调网络参与者分享和协调与以下方面有关的科学贡献：(1)制定一种广泛适用的方法来剖析公共政策的内容，称为制度语法(IG)；(2)制定用于评估政策设计的理论上知情的衡量标准；以及(3)评估受政策管辖的环境中的实际和模拟行为。RCN的贡献来自协作发展所围绕的三个关键重点领域：(1)IG-提取：在开源软件上开发方法，自动从富文本(如政策文件)中提取规则，并将其格式化为IG结构化数据库；(2)IG-分析：确定用于衡量政策设计和评估根据IG编码的政策质量的理论上知情的指标；以及(3)IG-Behavior：探索如何利用IG来支持博弈论、基于代理的建模和大n观察研究，特别关注策略设计如何影响实际和模拟的行为，以及行为如何相对于策略演变。通过RCN开发的工具和技术基于基于公地的同行生产(CBPP)原则，该原则强调使用协作平台和创新许可来吸引具有共同知识兴趣的学者参与科学问题解决。作为一揽子计划，区域协调委员会有助于理解机构分析如何独立地或与行为评估结合起来用于政策和治理的研究。归根结底，区域协调委员会为在广泛的政策领域进行更有效的治理提供指导。这一指导对于负责构建公共政策语言以成功实现政策目标的政策设计者来说是有价值的。这一奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

Effective governance hinges on how individuals interpret and respond to public policies, which are comprised of carefully designed language that conveys who can do what, when, and how. Adequately understanding the link between the design of public policies and behavior requires two complementary advancements. First, scientists must promote intellectual exchange on the development of generalizable and reliable approaches for studying policy designs. Second, these same scientists must coordinate with others focused on assessing how behavior emerges in response to, or sometimes alongside, policy designs. In the former case, policy design scholars confront a trade-off between detailed small-sample case studies that capture nuance in particular contexts, and large-sample studies, which fail to pick up on nuance but generalize across policies and contexts. In the latter case, behavioral scientists confront a different set of challenges. Behavioral scientists have advanced understanding of how individuals interpret and respond to specific instructions embedded in policy designs, but offer few insights about behavioral responses to different combinations of instructions, or how policy design and behavior co-evolve. Exchanging insights with policy design scholars focused on characterizing the language of public policy allows behavioral scientists to effectively respond to such issues. This Research Coordination Network (RCN) initiates an interdisciplinary and international network of policy design scholars and behavioral scientists to harness and integrate their insights to better understand the interplay between policy design and behavior. In support of this objective, RCN participants share and coordinate scientific contributions relating to: (1) theoretical and methodological development of a broadly applicable approach for dissecting the content of public policies, called the Institutional Grammar (IG); (2) development of theoretically informed metrics for evaluating policy designs; and (3) assessments of actual and simulated behavior in policy governed settings. RCN contributions derive from three key focal areas around which the collaboration evolves: (1) IG-Extract: Development of methods on open source software to automatically extract rules from rich text (such as policy documents) and format them into an IG structured database; (2) IG-Analytics: Identification of theoretically-informed metrics for measuring policy designs and evaluating the quality of policies coded in accordance with the IG; and (3) IG-Behave: Exploration of how the IG can be leveraged to support game theoretic, agent based modeling, and large-n observational research, focusing specifically on how policy designs influence actual and simulated behavior, and how behavior evolves in relation to policies. Tools and techniques developed through the RCN are based on principles of Commons-Based Peer Production (CBPP), which emphasizes the use of collaborative platforms and innovative licensing for engaging scholars with common intellectual interests in scientific problem solving. As a package, the RCN contributes understanding regarding how institutional analysis, independently or coupled with behavioral assessments, can be used in the study of policy and governance. Ultimately, the RCN offers guidance for more effective governance in a wide array of policy domains. This guidance is valuable for policy designers responsible for constructing the language of public policies for successfully achieving policy objectives.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.