Multidimensional signals and analytic flexibility: Estimating degrees of freedom in human speech analyses

Recent empirical studies have highlighted the large degree of analytic flexibility in data analysis which can lead to substantially different conclusions based on the same data set. Thus, researchers have expressed their concerns that these researcher degrees of freedom might facilitate bias and can lead to claims that do not stand the test of time. Even greater flexibility is to be expected in fields in which the primary data lend themselves to a variety of possible operationalizations. The multidimensional, temporally extended nature of speech constitutes an ideal testing ground for assessing the variability in analytic approaches, which derives not only from aspects of statistical modeling, but also from decisions regarding the quantification of the measured behavior. In the present study, we gave the same speech production data set to 46 teams of researchers and asked them to answer the same research question, resulting insubstantial variability in reported effect sizes and their interpretation. Using Bayesian meta-analytic tools, we further find little to no evidence that the observed variability can be explained by analysts’ prior beliefs, expertise or the perceived quality of their analyses. In light of this idiosyncratic variability, we recommend that researchers more transparently share details of their analysis, strengthen the link between theoretical construct and quantitative system and calibrate their (un)certainty in their conclusions

Reproducible research practices and transparency across linguistics

Scientific studies of language span across many disciplines and provide evidence for social, cultural, cognitive, technological, and biomedical studies of human nature and behavior. By becoming increasingly empirical and quantitative, linguistics has been facing challenges and limitations of the scientific practices that pose barriers to reproducibility and replicability. One of the proposed solutions to the widely acknowledged reproducibility and replicability crisis has been the implementation of transparency practices, e.g. open access publishing, preregistrations, sharing study materials, data, and analyses, performing study replications and declaring conflicts of interest. Here, we have assessed the prevalence of these practices in randomly sampled 600 journal articles from linguistics across two time points. In line with similar studies in other disciplines, we found a moderate amount of articles published open access, but overall low rates of sharing materials, data, and protocols, no preregistrations, very few replications and low rates of conflict of interest reports. These low rates have not increased noticeably between 2008/2009 and 2018/2019, pointing to remaining barriers and slow adoption of open and reproducible research practices in linguistics. As linguistics has not yet firmly established transparency and reproducibility as guiding principles in research, we provide recommendations and solutions for facilitating the adoption of these practices

Transparency in Linguistics

The project aims to at estimate the prevalence of transparent research practices in the field of linguistics before and after what has been referred to as the replication crisis

Reproducible research practices and transparency across linguistics

Scientific studies of language span across many disciplines and provide evidence for social,  cultural, cognitive, technological, and biomedical studies of human nature and behavior. As it becomes increasingly empirical and quantitative, linguistics has been facing challenges and limitations of the scientific practices that pose barriers to reproducibility and replicability. One of the  proposed solutions to the widely acknowledged reproducibility and replicability crisis has been the implementation of transparency practices,  e.g., open access publishing, preregistrations, sharing study materials, data, and analyses, performing study replications, and declaring conflicts of interest. Here, we have assessed the prevalence of these practices in 600 randomly sampled journal articles from linguistics across two time points. In line with similar studies in other disciplines, we found that 35% of the articles were published open access and the rates of sharing materials, data, and protocols were below 10%. None of the articles reported preregistrations, 1% reported replications, and 10% had conflict of interest statements. These rates have not increased noticeably between 2008/2009 and 2018/2019, pointing to remaining barriers and the slow adoption of open and reproducible research practices in linguistics. To facilitate adoption of these practices, we provide a range of recommendations and solutions for implementing transparency and improving reproducibility of research in linguistics