Abstract
In recent years, Open Science practices such as preregistration have become more and more popular as tools to increase rigour and transparency in many fields of research. The responses to these reforms have been mixed, however: for example, within the mathematical psychology community, the adoption of preregistration in particular has been highly debated. In this talk, I will clarify current and contentious issues surrounding the application of preregistration in cognitive modelling in order to show that we need to consider different research contexts for advances in reproducibility to be widely applicable and feasible. I will argue that we need to create templates and guides specific to every field and method of research to be able to increase rigour and transparency more widely.
