JOB MARKET PAPER
How Do Researchers Communicate with Policymakers?
The project employs natural language processing and machine learning methods to analyse the communication of academics with their peers and practitioners. This research leverages different outputs from researchers, including research papers, publications, policy briefs, blog posts, and reports. The application of content analysis algorithms allows to differentiate between the substance and thematic elements of academic-oriented versus policy-oriented outputs. By examining these variations, the project seeks to identify patterns and features linked to higher rates of evidence adoption by policymakers, thus shedding light on the most effective ways of communicating research findings in policy-relevant formats.
Understanding Selection Committee Decisions in Research Grant Awards
This project investigates the decision-making processes of selection committees that award research grants, focusing on their ability to predict academic and policy outcomes. This analysis utilizes two unique data sources: detailed records of the internal deliberations of selection committees, which include assessments of research proposals by individual committee members and minutes from board meetings, and data on the academic and policy impacts of the selected projects. The preferences of committee members and their ability to predict research outcomes are estimated through a model of assessment behaviour, which allows to compare results across individual characteristics, such as whether members are academics or practitioners.
Learning or Herding? Mechanisms of Policy Diffusion among Practitioners
Economics for Public Policy (EC230) at LSE, 2018-2021
(taught by Mohan Bijapur and Daniel Sturm)
LSE Excellence in Education School Award, 2021
(Nominated) LSE Students Union Teaching Award for Excellent Feedback and Communication, 2021
LSE Department of Economics Class Teacher Award, 2020 and 2021
© Alix Bonargent 2023