Using Machine Learning and Disambiguated Author Identifiers to Improve Record Linkage for Funding Program Evaluation

Summary

This conference paper examines how machine learning and disambiguated author identifiers can improve record linkage in large-scale funding program evaluation. The goal is to reduce linkage error in publication and administrative data so that evaluation pipelines can recover research outputs and downstream impact more accurately.