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Data Evaluation and Validation

In: AI for Qualitative Research

Author

Listed:
  • Diana Garcia Quevedo

    (ESCP Business School, Center of Research in Sustainability (RESET))

  • Josue Kuri

    (Principal Scientist)

Abstract

This chapter provides code examples for data evaluation and validation, introducing two approaches: traditional coding and large language model-based approaches. This chapter provides a concrete example of the limitations of large language models (LLMs), particularly in terms of reliability for numerical tasks. Researchers are advised to critically evaluate LLM outputs and consider traditional programming techniques for tasks that require numerical accuracy.

Suggested Citation

  • Diana Garcia Quevedo & Josue Kuri, 2026. "Data Evaluation and Validation," Springer Books, in: AI for Qualitative Research, chapter 7, pages 81-101, Springer.
    • Handle: RePEc:spr:sprchp:978-3-032-08872-7_7
    DOI: 10.1007/978-3-032-08872-7_7
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