Making This Year Better Than the Last

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The first step in analyzing this data was for a professional translator fluent in the languages of Paraguay — Spanish and Guarani — to convert the audio files to text. Then, Daryl’s team used a two-stage Natural Language Processing (NLP) method to detect key topics and phrases to unpack the meaning of the women’s responses. Using these methods, we identified three to four topics and patterns in each of the 10 responses. It is important to emphasize that this method allowed for spontaneous responses from women, rather than a pre-determined and closed-ended set of responses. We then used speech signals extracted directly from the audio files. These speech signals (such as pitch, duration of responses and voice modulation) told us whether the woman responding was engaged in her responses, when she was unsure, and when she gave us a “canned response” — i.e., telling us what she thought we wanted to hear. The NLP process told us korea whatsapp number data what women were saying while the speech signals told us how they were saying it.

Together, we were able to generate segments of responses that unpacked the “grey areas” of each of the 10 topics. For example, the chart below shows some of the responses to a question about child labor. If we were to ask the question in a closed-ended way using a Likert scale, most would have agreed that children should not work. We therefore would have concluded that attitudes towards child labor were no longer an issue in Paraguay. However, using these other methods, we were able to produce a more nuanced set of responses. Just under half the women interviewed had extraordinarily strong responses — not only did their speech signal strong engagement, but they also would name three to four varied reasons why they thought the way they did. But a sizable group gave a “canned response,” which suggested that their true feelings were uncertain. Another small group was uncertain about the ages where different work was appropriate, including whether children helping mothers in their businesses or jobs can be categorized as child labor. These tended to be older women, which makes sense as the labor laws in Paraguay have changed in the past decade. A final group was defensive: They often suggested that their children wanted to work and they, as mothers, had no control over them. These results suggested to us that we could make changes in our messaging to be clearer about age-appropriate tasks and child labor.