This is “Reliability in Unobtrusive Research”, section 11.5 from the book Sociological Inquiry Principles: Qualitative and Quantitative Methods (v. 1.0). For details on it (including licensing), click here.
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This final section of the chapter investigates a few particularities related to reliability in unobtrusive research projects (Krippendorff, 2009)Krippendorff, K. (2009). Testing the reliability of content analysis data: What is involved and why. In K. Krippendorff & M. A. Bock (Eds.), The content analysis reader (pp. 350–357). Thousand Oaks, CA: Sage. that warrant our attention. These particularities have to do with how and by whom the coding of data occurs. Issues of stability, reproducibility, and accuracy all speak to the unique problems—and opportunities—with establishing reliability in unobtrusive research projects.
StabilityIn terms of reliability, refers to the extent to which the results of coding vary across different time periods. refers to the extent to which the results of coding vary across different time periods. If stability is a problem, it will reveal itself when the same person codes the same content at different times and comes up with different results. Coding is said to be stable when the same content has been coded multiple times by the same person with the same result each time. If you discover problems of instability in your coding procedures, it is possible that your coding rules are ambiguous and need to clarified. Ambiguities in the text itself might also contribute to problems of stability. While you cannot alter your original textual data sources, simply being aware of possible ambiguities in the data as you code may help reduce the likelihood of problems with stability. It is also possible that problems with stability may result from a simple coding error, such as inadvertently jotting a 1 instead of a 10 on your code sheet.
ReproducibilityThe extent to which one’s coding procedures will garner the same results when the same text is coded by different people., sometimes referred to as intercoder reliability (Lombard, Snyder-Duch, & Campanella Bracken, 2010),Lombard, M., Snyder-Duch, J., & Campanella Bracken, C. (2004). Practical resources for assessing and reporting intercoder reliability in content analysis research projects. Retrieved from http://astro.temple.edu/~lombard/reliability is the extent to which one’s coding procedures will result in the same results when the same text is coded by different people. Cognitive differences among the individuals coding data may result in problems with reproducibility, as could ambiguous coding instructions. Random coding errors might also cause problems. One way of overcoming problems of reproducibility is to have coders code together. While working as a graduate research assistant, I participated in a content analysis project in which four individuals shared the responsibility for coding data. To reduce the potential for reproducibility problems with our coding, we conducted our coding at the same time in the same room, while sitting around a large, round table. We coded at the same time in the same room so that we could consult one another when we ran into problems or had questions about what we were coding. Resolving those ambiguities together meant that we grew to have a shared understanding of how to code various bits of data.
Finally, accuracyThe extent to which one’s coding procedures correspond to some preexisting standard. refers to the extent to which one’s coding procedures correspond to some preexisting standard. This presumes that a standard coding strategy has already been established for whatever text you’re analyzing. It may not be the case that official standards have been set, but perusing the prior literature for the collective wisdom on coding on your particular area is time well spent. Scholarship focused on similar data or coding procedures will no doubt help you to clarify and improve your own coding procedures.