We identify corporate commitments for reductions of greenhouse gas emissions - green pledges - from news articles using a large language model. About 8% of publicly traded U.S. companies have made green pledges, and these companies tend to be larger and browner than those without pledges....

We identify corporate commitments for reductions of greenhouse gas emissions—green pledges—from news articles using a large language model. About 8% of U.S. firms have made green pledges, and these companies tend to be larger and browner than those without pledges. Announcements of green...

We identify corporate commitments for reductions of greenhouse gas emissions—green pledges—from news articles using a large language model. About 8% of U.S. firms have made green pledges, and these companies tend to be larger and browner than those without pledges. Announcements of green...

We identify corporate commitments for reductions of greenhouse gas emissions - green pledges - from news articles using a large language model. About 8% of publicly traded U.S. companies have made green pledges, and these companies tend to be larger and browner than those without pledges....

Popular approaches to building data from unstructured text come with limitations, such as scalability, interpretability, replicability, and real-world applicability. These can be overcome with Context Rule Assisted Machine Learning (CRAML), a method and no-code suite of software tools that...