The article "Intercoder Reliability in Qualitative Research: Debates and Practical Guidelines" discusses the importance and practical aspects of intercoder reliability (ICR) in qualitative research. ICR is a measure of agreement between different coders when coding the same data, which is crucial for improving the systematicity, communicability, and transparency of the coding process. The article reviews common arguments for and against incorporating ICR in qualitative analysis, highlighting its benefits such as enhancing reflexivity and dialogue within research teams and increasing the trustworthiness of the analysis. However, it also addresses objections that ICR may contradict the interpretative nature of qualitative research and introduce false precision. The article provides practical guidelines for performing ICR assessments, including the use of manual or electronic methods, the number of coders, the proportion of data to be multiply coded, and the level of independence required. It emphasizes the importance of segmenting data units, the number of codes, and the interpretative depth of coding. The article also discusses various measures of ICR, such as Krippendorff’s alpha, and how to present and interpret the results. Finally, it offers a suggested procedure for conducting an ICR assessment, emphasizing the need to tailor the approach to the specific research context and aims.The article "Intercoder Reliability in Qualitative Research: Debates and Practical Guidelines" discusses the importance and practical aspects of intercoder reliability (ICR) in qualitative research. ICR is a measure of agreement between different coders when coding the same data, which is crucial for improving the systematicity, communicability, and transparency of the coding process. The article reviews common arguments for and against incorporating ICR in qualitative analysis, highlighting its benefits such as enhancing reflexivity and dialogue within research teams and increasing the trustworthiness of the analysis. However, it also addresses objections that ICR may contradict the interpretative nature of qualitative research and introduce false precision. The article provides practical guidelines for performing ICR assessments, including the use of manual or electronic methods, the number of coders, the proportion of data to be multiply coded, and the level of independence required. It emphasizes the importance of segmenting data units, the number of codes, and the interpretative depth of coding. The article also discusses various measures of ICR, such as Krippendorff’s alpha, and how to present and interpret the results. Finally, it offers a suggested procedure for conducting an ICR assessment, emphasizing the need to tailor the approach to the specific research context and aims.