Applied linguists have turned increasingly in recent years to meta-analysis as the preferred means of synthesizing quantitative research. The first step in the meta-analytic process involves defining a domain of interest. Despite its apparent simplicity, this step involves a great deal of subjectivity on the part of the meta-analyst. This article problematizes the importance of clearly defining and operationalizing meta-analytic domains. Toward that end, we present a critical review of one particular domain, corrective feedback, which has been subject to 18 unique meta-analyses. Specifically, we examine the unique approach each study has taken in defining their domain of interest. In order to demonstrate the critical role of this stage in the meta-analytic process, we also examine variability in summary effects as a function of the unique subdomains in the sample. Because different techniques used to identify candidate studies carry assumptions about the type of research that falls within the domain of interest (e.g. published vs. unpublished), we also include a brief review of search techniques employed in a set of 81 meta-analyses of second language research. Building on the work of In'nami and Koizumi (2010) and Oswald and Plonsky (2010), the results for this phase of the analysis show that L2 meta-analysts generally rely on a stable but very limited set of search strategies, none of which is likely to yield unpublished studies. Based on our findings related both to domain definition and search techniques employed by L2 researchers, we make specific recommendations for future meta-analytic practice in the field.