Abstract
AbstractMany of us, especially in the more experimental tradition, are used to doing it all ourselves: we don't know better than to collect our own data for every new study. We invest considerable amounts of time and resources in designing experiments, ethical review applications, participant recruitment, finding and training measuring assistants, and writing data management plans. And after all the hard work we end up with a sample size that hardly ever meets current standards. What if we could skip, or outsource some of these study aspects, allowing us to devote more of our time, energy, expertise, and experience to data analysis, reading, writing, and theory development? We argue that sharing data, expertise, and infrastructure could contribute to improving the credibility of research results, and to practicing more sustainable developmental science. In addition, we discuss several reasons that we believe may (currently) dissuade researchers from considering such sharing.
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