# Public-private funding models in open source software development: A case study on scikit-learn

arXiv: https://arxiv.org/abs/2404.06484 · HTML: https://mlsanity.com/paper/2404.06484/

## Key facts

- Cited by 5 papers in the map (data through 14 Oct 2026).
- Builds on 9 of its 100 references that are in the map.
- First posted on arXiv 9 Apr 2024.

## Builds on (most cited first, 9 of 9)

- [Why Modern Open Source Projects Fail](https://mlsanity.com/paper/1707.02327/) (2017)
- [On the abandonment and survival of open source projects: An empirical investigation](https://mlsanity.com/paper/1906.08058/) (2019)
- [Do software firms collaborate or compete? A model of coopetition in community-initiated OSS projects](https://mlsanity.com/paper/1808.06489/) (2018)
- [Cooperation among competitors in the open-source arena: The case of OpenStack](https://mlsanity.com/paper/1612.09462/) (2016)
- [How Early Participation Determines Long-Term Sustained Activity in GitHub Projects?](https://mlsanity.com/paper/2308.06005/) (2023)
- [Are Donation Badges Appealing? A Case Study of Developer Responses to Eclipse Bug Reports](https://mlsanity.com/paper/1803.04129/) (2018)
- [Who, What, Why and How? Towards the Monetary Incentive in Crowd Collaboration: A Case Study of Github's Sponsor Mechanism](https://mlsanity.com/paper/2111.13323/) (2021)
- [Identifying Emergent Leadership in OSS Projects Based on Communication Styles](https://mlsanity.com/paper/2201.11897/) (2022)
- [Is It Enough to Recommend Tasks to Newcomers? Understanding Mentoring on Good First Issues](https://mlsanity.com/paper/2302.05058/) (2023)

## Built on by (most cited first, 5 of 5)

- [The AI Community Building the Future? A Quantitative Analysis of Development Activity on Hugging Face Hub](https://mlsanity.com/paper/2405.13058/) (2024)
- [The Future of Open Human Feedback](https://mlsanity.com/paper/2408.16961/) (2024)
- [Why Companies "Democratise" Artificial Intelligence: The Case of Open Source Software Donations](https://mlsanity.com/paper/2409.17876/) (2024)
- [Characterising Open Source Co-opetition in Company-hosted Open Source Software Projects: The Cases of PyTorch, TensorFlow, and Transformers](https://mlsanity.com/paper/2410.18241/) (2024)
- [A Cartography of Open Collaboration in Open Source AI: Mapping Practices, Motivations, and Governance in 14 Open Large Language Model Projects](https://mlsanity.com/paper/2509.25397/) (2025)

## Abstract (arXiv)

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.