Doctoral Dissertation Research: Forest engineers, bureaucrats, and the constitution of information

Columbia University, New York NY

Investigators

Abstract

The production of accurate and reliable information about rainforests and other difficult-to-survey environments constitutes an enduring challenge for state bureaucrats, scientists, and engineers. Yet the grounded processes through which key environmental information is produced have received little study. The research supported by this award takes up this problem through an anthropological investigation of the technical and bureaucratic practices through which state environmental information is created, transmitted, and applied. The research will be carried out by Columbia University doctoral student, Eduardo Romero Dianderas, with oversight from Dr. Elizabeth A. Povinelli. The researcher will focus on the work of engineers and bureaucrats in the Amazonia region of Loreto, Peru, as a case study. He will collect data at multiple points in the chain of information production and application. In the field, he will document how engineers conduct research to generate technical data about the region. In state and associational offices, he will follow the engineering data as they are communicated to bureaucrats and as bureaucrats deploy them for technical judgments and public decisions. Research methods will include participant observation, analysis of paper and digital documents, and semi-structured interviews. This approach will shed light on what technical and bureaucratic environmental information includes and what it excludes, such as the knowledge and perspectives of indigenous inhabitants of these environments. It will also clarify the relevant communicative and technological infrastructures. Findings from this research will help policy makers determine the potentials and limitations of the data on which they base their policies. The research also will contribute to building more robust theories of the production, communication, and comprehension of scientific data. 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.