A Classification Bias and an Exclusion Bias Jointly Overinflated the Estimation of Publication Biases in Bilingualism Research

Abstract

A publication bias has been argued to affect the fate of results in bilingualism research. It was repeatedly suggested that studies presenting evidence for bilingual advantages are more likely to be published compared to studies that do not report results in favor of the bilingual advantage hypothesis. This work goes back to the original claim and re-examines both the dataset and the classification of the studies that were employed. We find that the exclusion of published works such as doctoral dissertations, book chapters, and conference proceedings from the original dataset significantly inflated the presumed publication bias. Moreover, the estimation of the publication bias was affected by a classification bias that uses a mega-category that consists of both null and negative outcomes. Yet finding evidence for a bilingual disadvantage is not synonymous with obtaining a result indistinguishable from zero. Consequently, grouping together null and negative findings in a mega-category has various ramifications, not only for the estimation of the presumed publication bias but also for the field’s ability to appreciate the insofar hidden correlations between bilingual advantages and disadvantages. Tracking biases that inflate scientific results is important, but it is not enough. The next step is recognizing the nested Matryoshka doll effect of bias-within-bias, and this entails raising awareness for one’s own bias blind spots in science.