Social Context and Revenue Measures

社会背景和收入措施

• 批准号: 1823821
• 负责人: Isaac Martin
• 金额: $ 35万
• 依托单位: University of California-San Diego
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-08-15 至 2023-01-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1823821&HistoricalAwards=false
• 关键词: Social; Context; Revenue; Measures

In this project, new computational methods are applied to the texts of more than 3,000 local revenue measures that were subject to voter referendums in more and less diverse places. These data are used to investigate how tax policy characteristics may moderate the known effects of diversity on voters' willingness to pay for public spending. The results will yield new insights into what makes for a sustainable revenue source. This is crucial for enabling American society to meet the fiscal challenges of the future, and thus for the health, prosperity and welfare of American society as well as for national security. The project involves the assembly and digitization of revenue measures presented to local voters since 1986. Supervised and unsupervised machine learning techniques then are applied to classify these measures and to identify features of the text that mediate the observed associations between diversity and reported election outcomes. The most general goal of the project is to identify institutional mechanisms that moderate associations between social context and public spending. A more specific goal is to identify the causes of the well-known negative association between diversity and public spending on health, welfare, and other social transfers and services. The project thereby advances theoretical understanding of the dimensions of policy that affect voting behavior. It also analyzes institutional mechanisms that yield one of the most important observed patterns in fiscal sociology.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.

在这个项目中，新的计算方法被应用于3,000多个地方税收措施的文本，这些措施在不同的地方进行了全民投票。 这些数据被用来调查如何税收政策的特点可能缓和已知的影响，选民的意愿支付公共支出的多样性。 结果将产生新的见解，什么是可持续的收入来源。 这对美国社会应对未来的财政挑战至关重要，因此对美国社会的健康、繁荣和福利以及国家安全至关重要。该项目涉及自1986年以来向当地选民提交的税收措施的汇编和数字化。然后，应用有监督和无监督的机器学习技术对这些指标进行分类，并识别文本的特征，这些特征介导了多样性和报告的选举结果之间观察到的关联。该项目最一般的目标是确定调节社会背景与公共支出之间联系的体制机制。一个更具体的目标是查明众所周知的多样性与卫生、福利和其他社会转移和服务方面的公共开支之间的负相关的原因。因此，该项目推进了对影响投票行为的政策维度的理论理解。该奖项反映了NSF的法定使命，通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

项目成果

Racial Context and Political Support for California School Taxes

加州学校税的种族背景和政治支持

• DOI: 10.1111/ssqu.12869
• 发表时间: 2020
• 期刊: Social Science Quarterly
• 影响因子: 1.9
• 作者: Nations, Jennifer M.;Martin, Isaac W.
• 通讯作者: Martin, Isaac W.

Policy design and local tax elections: News from the search for a popular tax

政策设计和地方税收选举：寻找受欢迎的税收的新闻

• 发表时间: 2019
• 期刊: Annual Meetings of the American Sociological Association
• 作者: Martin, Isaac William;Harper, Heather M.
• 通讯作者: Harper, Heather M.