研究与政策的联系:来自印度农业经济研究的经验证据

Balaji Sj, S. Babu, S. Pal
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摘要

发展中国家的决策过程往往继续在缺乏证据的情况下运作。在本研究中,我们探讨了印度农业经济研究系统(AERS)和农业政策系统(APS)之间的研究-政策联系。具体来说,我们审查了国会两院——人民院(Lok Sabha)和邦议会(Rajya Sabha) ——向农业和农民福利部提出的问题,并对APS面临的关键问题进行筛选。此外,我们利用两家主要国家农业经济学期刊上发表的研究文章列表,研究了AERS在解决紧迫政策问题方面的一致性。我们使用了2014 - - 2018年期间议会选举代表提出的6,465个问题和377篇研究文章。我们使用机器学习技术进行信息检索,因为所需的信息被隐藏为非数字文本。使用标签云(按频率排列的单词列表),我们确定了APS关注的问题与AERS研究重点之间的关键分歧,并探讨了它们之间的联系。为了扩大我们的理解,我们采用了潜在的狄利克雷分配,这是一种自然语言处理技术,可以识别关键问题并在适当的集群下自动分类,以检查研究和政策系统之间的协同作用。结果显示AERS和APS之间存在显著的一致性,证明两群落假说无效。我们确定了政策领域中持续存在的问题,这些问题需要研究系统的支持,以及研究系统重组的潜在领域。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Research-Policy Linkages: Empirical Evidence From Agroeconomic Research in India
Policy-making processes in developing countries often continue to operate devoid of evidence. In this study, we explore the research-policy linkages between the agroeconomic research system (AERS) and the agricultural policy system (APS) in India. Specifically, we examine questions directed to the Ministry of Agriculture and Farmers’ Welfare in the two houses of the national parliament—the House of the People (Lok Sabha) and the Council of States (Rajya Sabha)—and filter them for key issues that confront the APS. In addition, using the list of research articles published in two major national agricultural economics journals, we examine the alignment of the AERS toward addressing pressing policy issues. We use 6,465 questions raised by elected representatives in the parliamentary houses and 377 research articles, both during the period 2014–2018. We use machine learning techniques for information retrieval because the required information is hidden as non-numerical text. Using tag clouds (lists of words by frequency), we identify key divergences between the concerns of the APS and the research focus of the AERS, and explore their linkages. To broaden our understanding, we employ latent Dirichlet allocation, a natural language processing technique that identifies crucial issues and automates their classification under appropriate clusters, to examine synergies between the research and policy systems. Results show remarkable alignment between the AERS and the APS, invalidating the two-communities hypothesis. We identify persistent issues in the policy domain that require the support of the research system, as well as potential areas for research system realignment.
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