Building a collaborative psychological science: Lessons learned from ManyBabies 1
Article by Krista Byers-Heinlein, Liquan Liu et al. in Canadian Psychology, The article will be publicly available on 4 June 2021.
The field of infancy research faces a difficult challenge: Some questions require samples that are simply too large for any 1 lab to recruit and test. ManyBabies aims to address this problem by forming large-scale collaborations on key theoretical questions in developmental science, while promoting the uptake of Open Science practices. Here, we look back on the first project completed under the ManyBabies umbrella—ManyBabies 1—which tested the development of infant-directed speech preference. Our goal is to share the lessons learned over the course of the project and to articulate our vision for the role of large-scale collaborations in the field. First, we consider the decisions made in scaling up experimental research for a collaboration involving 100+ researchers and 70+ labs. Next, we discuss successes and challenges over the course of the project, including the following: protocol design and implementation, data analysis, organisational structures and collaborative workflows, securing funding, and encouraging broad participation in the project. Finally, we discuss the benefits we see both in ongoing ManyBabies projects and in future large-scale collaborations in general, with a particular eye toward developing best practices and increasing growth and diversity in infancy research and psychological science in general. Throughout the article, we include first-hand narrative experiences to illustrate the perspectives of researchers playing different roles within the project. Although this project focused on the unique challenges of infant research, many of the insights we gained can be applied to large-scale collaborations across the broader field of psychology.
Krista Byers-Heinlein, Christina Bergmann,Catherine Davies, Michael Frank, Kiley Hamlin, Melissa Kline, Jonathan Kominsky, Jessica Kosie, Casey Lew-Williams, Liquan Liu, Meghan Mastroberardino, Leher Singh, Connor Waddell, Martin Zettersten, Melanie Soderstrom.