Much empirical legal research relies on turning unstructured text into structured variables. In corporate governance research, this step has typically been done by humans, a process that can be slow and resource-intensive.
A new paper on arXiv introduces DECODEM, a set of enhanced methods for data extraction from corporate organizational documents. The approach is designed to automate the translation of text into structured data, potentially reducing the burden of manual coding.
The abstract highlights the traditional reliance on manual coding but does not provide details on the method's performance or implementation. The paper's contribution lies in addressing a key bottleneck in empirical legal research.