Programme Thesis
ResearchHub Preregistration Grants fund open, preregistered research projects that advance scientific knowledge through transparent, reproducible methods. The programme exists to incentivize preregistration and open science practices, particularly within the decentralized science (DeSci) movement, by providing direct community-backed funding for hypothesis-driven studies.
Selection Criteria
- Preregistration quality: clarity of hypotheses, methods, and analysis plan; adherence to preregistration standards (e.g., OSF, AsPredicted).
- Scientific merit: novelty, rigor, and potential impact of the proposed research.
- Feasibility: realistic timeline, budget, and applicant's capacity to execute the project.
- Open science alignment: commitment to sharing data, code, and results openly; use of open-source tools.
- Community interest: demonstrated relevance to ResearchHub community; potential for crowdfunding traction.
- Eligibility: open to independent researchers, early-career researchers, and those without institutional backing; no strict affiliation requirement.
Past Winners / Cohort Profiles
ResearchHub Preregistration Grants are relatively new and crowdfunded; past winners include independent researchers and small teams working on preregistered replication studies, meta-analyses, and computational modeling projects. Named examples are not publicly listed on the main page, but typical profiles are early-career scientists (pre-PhD or postdoc) with strong open science practices and a clear preregistration plan.
Ideal Candidate Fingerprint
An early-career independent researcher with a well-defined, preregistered computational study that tests a specific hypothesis using open-source tools and publicly available data. The applicant should have a track record of open science (preprints, code repositories, preregistrations) and a clear plan for disseminating results via DOI and community engagement.
Recommended Framing
Eniola should frame the CCT model validation as a preregistered computational replication and extension of a novel pharmacological framework for addiction, emphasizing the five pre-registered hypotheses already confirmed and the open-source code (GitHub, Zenodo). Highlight the independent researcher status, the Africa/Nigeria angle (addressing addiction burden in LMICs), and the DeSci alignment (no institutional overhead, open data/code). A small grant ($5K–$15K) would fund Bayesian calibration refinement and sensitivity analysis, with a clear timeline and budget for HPC compute and publication fees.
Watch Out
None identified. Eniola meets all eligibility criteria: independent researcher, early-career, strong preregistration record, open science practices. The only potential concern is that the CCT model is already partially published (preprints, under review), so the grant must propose a distinct preregistered extension or validation step, not just rehash existing work.