Governments are increasingly funding open source software (OSS) development to support software security, digital sovereignty, and national competitiveness in science and innovation, amongst others. However, little is known about how OSS developers evaluate the relative benefits and drawbacks of governmental funding for OSS. This study explores this question through a case study on scikit-learn, a Python library for machine learning, funded by public research grants, commercial sponsorship, micro-donations, and a 32 euro million grant announced in France's artificial intelligence strategy. Through 25 interviews with scikit-learn's maintainers and funders, this study makes two key contributions. First, it contributes empirical findings about the benefits and drawbacks of public and private funding in an impactful OSS project, and the governance protocols employed by the maintainers to balance the diverse interests of their community and funders. Second, it offers practical lessons on funding for OSS developers, governments, and companies based on the experience of scikit-learn. The paper concludes with key recommendations for practitioners and future research directions.

翻译：各国政府正日益通过资助开源软件开发来支持软件安全、数字主权、国家在科学与创新领域的竞争力等目标。然而，开源软件开发者如何看待政府资助对开源软件的相对利弊，目前所知甚少。本研究以scikit-learn（一个用于机器学习的Python库）为案例，通过公共研究经费、商业赞助、小额捐赠以及法国人工智能战略中宣布的3200万欧元资助等多种方式探索这一问题。通过对scikit-learn维护者与资助者的25次深度访谈，本研究做出两大贡献：首先，首次提供了关于公共与私人资助对一个重要开源项目利弊影响的实证发现，以及维护者为平衡社区与资助者多元利益而采用的治理协议；其次，基于scikit-learn实践经验，为开源开发者、政府及企业提供了关于经费机制的实用教训。本文最后为从业人员提出关键建议并指出未来研究方向。