Grassroots Big Team Science (BTS) refers to large-scale, research collaborations that are researcher-initiated and sustained without the backing of a central institution or dedicated funding body. Emerging in response to the replicability crisis in the behavioural and social sciences, early efforts such as the Open Science Collaboration and ManyLabs demonstrated that coordinated, multi-site research could address some of the primary issues related to the robustness of scientific findings (e.g., Klein et al., 2014). This model has since proliferated into a growing ecosystem of networks, including ManyBabies, ManyPrimates, ManyBirds, FORRT, and the Psychological Science Accelerator. The sheer scale of these ambitious projects necessitates support for many functions, including staff, novel research infrastructures, and funding for the operating costs of a number of sites. Yet, unlike top-down, institutionally supported team science initiatives, these grassroots networks operate under conditions that the broader science of team science community has rarely examined: near-total funding insecurity (Baumgartner et al., 2023; Forscher et al., 2023). As a result, BTS initiatives currently rely entirely on patchy funding and extensive volunteerism. This in turn poses additional barriers to participation for already under-resourced researchers, institutions, and world regions.

To examine these challenges, we are collaborating with several established BTS networks and have adopted a two-pronged approach to data generation. First, information about successful and unsuccessful funding attempts across multiple networks, along with any available reviewer comments, will provide information on BTS funding efforts to date. Second, qualitative data collection with network leads, alongside published papers and opinion pieces documenting BTS networks' funding experiences (e.g., Coles et al., 2024; ManyPrimates et al., 2022), will capture experiences seeking, securing, and managing BTS funding. Thematic analysis of qualitative data will be used to identify recurring structural barriers across the full lifecycle of BTS funding.

Preliminary data analyses reveal that several major BTS networks have zero identified funding, and that networks with funding typically have a hodgepodge of small, inconsistent amounts from disparate and indirect sources. This precarity reflects deep structural misalignments: despite many funders identifying BTS as a key priority in theory, existing mechanisms remain oriented toward individual PIs, and funders generally favour easily identifiable short-term impacts over more diffuse long-term benefits likely to stem from BTS. Even when direct funding has been secured, distributing it internationally introduces numerous additional challenges, including incompatible overhead systems, restrictions on cross-border transfers, and administrative burden (Matthews et al., 2020). These challenges disproportionately affect researchers in under-resourced regions, exacerbating global inequalities in who can participate in and lead large-scale science.

Data collection is ongoing, and this talk will present findings from both quantitative and qualitative strands. We will discuss how structural misalignments limit the effectiveness and progress of BTS, highlight successful funding cases, and share practical guidance for existing networks. Finally, we will offer recommendations to funding agencies on how to better support grassroots BTS without jeopardizing support for traditional research. This work speaks directly to the science of team science community's interest in understanding the structural conditions that enable or constrain collaborative research at scale.