Doctoral Dissertation Research: Digital Farming Technologies, Traditional Knowledge, and Agrarian Livelihoods

博士论文研究：数字农业技术、传统知识和农业生计

• 批准号: 2115365
• 负责人: Brian Silverstein
• 金额: $ 1.69万
• 依托单位: University of Arizona
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-02-01 至 2023-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2115365&HistoricalAwards=false
• 关键词: Doctoral; Dissertation; Research; Digital; Farming

This award is funded in whole or in part under the American Rescue Plan Act of 2021 (Public Law 117-2). Population shifts and shrinking agricultural land are increasing pressure on agricultural production, leading to food insecurity and economic, social and political instability in many regions. A range of private and public institutions aim to increase efficiency (more food from less land) by integrating digital farming technologies that provide farmers with algorithm-generated recommendations to predict and manage their farming (soil, plants, inputs, timing), finances (budgeting, credit) and insurance. They also seek to revive and incorporate farmers’ traditional knowledge and practices into the digital applications to promote agricultural innovation in food and enhance socio-economic welfare. This research project investigates the everyday experiences of the farmers with digital farming technologies and the impacts of these technologies on their farming knowledges, practices and income. In addition to providing funding for the training of a graduate student in anthropology in the methods of empirical, scientific data collection and analysis, the findings of this research will be disseminated to governmental and non-governmental organizations with the aim of improving social, economic, and ecological conditions of farmers and democratizing access to digital platforms and data in food systems. This research project examines what traditional knowledge and practices of farmers are being revived and retained and/or abandoned by digital farming technologies and what the effects are on farmers’ farming practices and income. To answer these questions, the researcher conducts archival research, analyzes digital datasets, and interviews, participates in and observes the work of farmers who are engaging in the digital farming projects and farmers who are not scientists, engineers and public officials. This research enhances scientific understanding of how emergent technologies and longstanding know-how interact in the production of food, contributing to ethnographic work on the technopolitics of food systems.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.

该奖项全部或部分根据2021年美国救援计划法案（公法117-2）资助。人口转移和农业用地减少给农业生产带来越来越大的压力，导致许多地区粮食无保障以及经济、社会和政治不稳定。一系列私人和公共机构旨在通过整合数字农业技术来提高效率（用更少的土地生产更多的粮食），这些技术为农民提供算法生成的建议，以预测和管理他们的农业（土壤，植物，投入，时间），财务（预算，信贷）和保险。他们还寻求恢复农民的传统知识和做法，并将其纳入数字应用程序，以促进粮食方面的农业创新，提高社会经济福利。该研究项目调查了农民使用数字农业技术的日常经验，以及这些技术对他们的农业知识，实践和收入的影响。除了为人类学研究生提供实证科学数据收集和分析方法的培训提供资金外，这项研究的结果将传播给政府和非政府组织，目的是改善农民的社会，经济和生态条件，并使粮食系统数字平台和数据的获取民主化。该研究项目探讨了数字农业技术正在恢复和保留和/或放弃哪些传统知识和农民的做法，以及对农民的农业做法和收入的影响。为了回答这些问题，研究人员进行了档案研究，分析了数字数据集，并采访，参与和观察了从事数字农业项目的农民和非科学家，工程师和公职人员的农民的工作。该研究增强了对新兴技术和长期专有技术在食品生产中如何相互作用的科学理解，为食品系统技术政治学的民族志工作做出了贡献。该奖项反映了NSF的法定使命，并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。