Semantics and words matter for analyzing gender and social inclusivity in development projects

The Agrobiodiversity Index and the Enhancing Sustainability Across Agricultural Systems of the Water Land and Ecosystems (WLE FG5) program team have been puzzled by how to capture efforts that are hard to quantify or “invisible”. For example, how do you measure commitments towards something? We set out to test the usefulness of text mining and artificial intelligence to reveal the power of words. What we found was a powerful tool to bring our discipline to task and progress more equitably.

Text mining is a relatively simple technique. It consists of automatically extracting any word, paragraph, or sentence from digital texts in several formats (PDFs, scanned documents, or Word documents). The challenge is defining “what to extract” and “how to analyze” it.

The identification of “what to extract” requires a lot of back and forth among researchers, practitioners, and policymakers. We often talk about the same things although we may do it using different words which impedes understanding and cross-collaboration.