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Inter-rater reliability in Learner Corpus Research

Tove Larsson, Magali Paquot, Luke Plonsky

2020International Journal of Learner Corpus Research22 citationsDOIOpen Access PDF

Abstract

Abstract In Learner Corpus Research (LCR), a common source of errors stems from manual coding and annotation of linguistic features. To estimate the amount of error present in a coded dataset, coefficients of inter-rater reliability are used. However, despite the importance of reliability and internal consistency for validity and, by extension, study quality, interpretability and generalizability, it is surprisingly uncommon for studies in the field of LCR to report on such reliability coefficients. In this Methods Report, we use a recent collaborative research project to illustrate the pertinence of considering inter-rater reliability. In doing so, we hope to initiate methodological discussion on instrument design, piloting and evaluation. We also suggest some ways forward to encourage increased transparency in reporting practices.

Topics & Concepts

Generalizability theoryInterpretabilityReliability (semiconductor)Inter-rater reliabilityComputer scienceTransparency (behavior)Coding (social sciences)Internal consistencyConsistency (knowledge bases)Natural language processingPsychologyArtificial intelligenceStatisticsMathematicsPsychometricsRating scalePower (physics)Quantum mechanicsComputer securityPhysicsNatural Language Processing TechniquesInterpreting and Communication in HealthcareTopic Modeling
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