Identifying Climate Targets in National Laws and Policies using Machine Learning

arXiv:2404.02822v1 Announce Type: cross
Abstract: Quantified policy targets are a fundamental element of climate policy, typically characterised by domain-specific and technical language. Current methods for curating comprehensive views of global climate policy targets entail significant manual effort. At present there are few scalable methods for extracting climate targets from national laws or policies, which limits policymakers' and researchers' ability to (1) assess private and public sector alignment with global goals and (2) inform policy decisions. In this paper we present …

arxiv climate cs.cl cs.cy cs.lg laws machine machine learning policies targets type