Reproducibility, replicability, and robustness in corpus linguistics

Abstract This introduction to the special issue Reproducibility, Replicability, and Robustness in Corpus Linguistics calls for more transparent and robust research practices in the field. It situates the discussion within the broader replication crisis in the life and social sciences and explores its relevance for corpus linguistics. The article identifies key areas for improvement — data management, workflows, and reporting — and showcases tools and principles such as FAIR/CARE, version control, reproducible notebooks, and open repositories. It highlights how corpus linguistics can build on open science infrastructures to enhance methodological rigor. Practical challenges, including data sensitivity and skill gaps, are addressed with actionable strategies. The issue brings together contributions that clarify core terminology, test the robustness of established methods, and suggest concrete ways forward. Together, these articles offer conceptual and practical guidance for making corpus linguistic research more open, verifiable, and aligned with broader scientific standards.