AI in qualitative research: Using large language models to code survey responses in native languages
Food systems research - and more generally, policy and development research -often relies on structured surveys, administrative data, or experiments. While these approaches yield valuable quantitative insights, they tend to miss critical qualitative dimensions. One useful qualitative approach is ope...
| Autores principales: | , |
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| Formato: | Blog Post |
| Lenguaje: | Inglés |
| Publicado: |
International Food Policy Research Institute
2025
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| Acceso en línea: | https://hdl.handle.net/10568/178199 |
| Sumario: | Food systems research - and more generally, policy and development research -often relies on structured surveys, administrative data, or experiments. While these approaches yield valuable quantitative insights, they tend to miss critical qualitative dimensions. One useful qualitative approach is open-ended interview questions. When such responses are collected in participants' native languages, they can provide rich and nuanced information-for example, on the complex local challenges smallholder farmers face. |
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