Exploring Nature: Datasets and Models for Analyzing Nature-Related Disclosures
This addresses the need for large-scale assessment of corporate nature communication, particularly for stakeholders like investors and regulators, though it is incremental as it applies existing methods to new data.
The paper tackled the problem of analyzing corporate nature-related disclosures by creating expert-annotated datasets with 2,200 text samples and training classifier models for water, forest, and biodiversity dimensions, showing that such communication is more prevalent in hotspot areas and industries like agriculture and utilities.
Nature is an amorphous concept. Yet, it is essential for the planet's well-being to understand how the economy interacts with it. To address the growing demand for information on corporate nature disclosure, we provide datasets and classifiers to detect nature communication by companies. We ground our approach in the guidelines of the Taskforce on Nature-related Financial Disclosures (TNFD). Particularly, we focus on the specific dimensions of water, forest, and biodiversity. For each dimension, we create an expert-annotated dataset with 2,200 text samples and train classifier models. Furthermore, we show that nature communication is more prevalent in hotspot areas and directly effected industries like agriculture and utilities. Our approach is the first to respond to calls to assess corporate nature communication on a large scale.