Replication crises have shaken the scientific landscape during the last decade. As potential solutions, open science practices were heavily discussed and have been implemented with varying success in different disciplines. We argue that computational-x disciplines such as computational social science, are also susceptible for the symptoms of the crises, but in terms of reproducibility. We expand the binary definition of reproducibility into a tier system which allows increasing levels of reproducibility based on external verfiability to counteract the practice of open-washing. We provide solutions for barriers in Computational Social Science that hinder researchers from obtaining the highest level of reproducibility, including the use of alternate data sources and considering reproducibility proactively.

翻译：过去十年间，可重复性危机撼动了学术界的根基。作为潜在解决方案，开放科学实践被广泛讨论，并在不同学科中以各自方式得以实施，但成效各异。我们认为，计算社会科学这类计算交叉学科同样面临危机症状的威胁，主要体现在可重复性层面。我们将可重复性的二元定义扩展为分层体系，通过引入基于外部可验证性的递进式可重复性层级，以对抗"开放洗白"行为。针对计算社会科学中阻碍研究者实现最高可重复性层级的障碍，我们提供了解决方案，包括利用替代数据源以及主动将可重复性纳入研究设计。