International Journal For Multidisciplinary Research

E-ISSN: 2582-2160   •   Impact Factor: 9.24

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Volume 8 Issue 5
September-October 2026

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Knowing with the Machine: Towards an Epistemology of Research Augmented by Large Language Models in the Social Sciences

Author(s) Dr. Rachid Maghniwi
Country Morocco
Abstract The entry of large language models (LLMs) into social science research practices, such as interview coding, literature reviews, hypothesis generation and the simulation of respondents, is usually discussed from a technical or ethical standpoint. This paper offers an epistemological reading. It argues that an LLM is neither a neutral instrument nor a "co-researcher", but an interpretive mediator whose probabilistic and opaque outputs affect the criteria of rigour differently depending on the paradigm adopted. By confronting LLM uses with the positivist, critical realist, interpretivist and constructivist paradigms, the paper shows that each paradigm calls for specific safeguards. It then proposes a protocol for comparing human and algorithmic coding, followed by a five-dimension rigour framework (traceability, reproducibility, reflexivity, adversarial validation and interpretive accountability) specified for each paradigm. The contribution is twofold. Theoretically, the paper brings generative AI into the debate on the foundations of knowledge in the social sciences. Methodologically, it provides researchers and reviewers with a tool to assess the legitimacy of AI-assisted research.
Keywords epistemology, large language models, generative artificial intelligence, research methodology, validity, reflexivity, social sciences, epistemological positioning, research rigour
Field Sociologie > Philosophie / Psychologie / Religion
Published In Volume 8, Issue 5, September-October 2026
Published On 2026-09-30
DOI https://doi.org/10.36948/ijfmr.2026.v08i05.88606
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CrossRef DOI prefix of IJFMR is 10.36948/ijfmr

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