read the research.
Papers published by Bucket Foundation on the research-atlas graph and the canon. Each is free to read, born with a real DOI via Zenodo, and fully reproducible — every headline number pinned by a test suite. For the education-reform research corpus, see the education-atlas.
The structure of public research funding, 2015–2025: concentration, cross-funder co-funding, and the funding→output relationship in a reconciled NIH/NSF/EC/UKRI grant graph
We assemble a reconciled graph of the global public-research economy — 887,016 grants from the U.S. National Institutes of Health (NIH), the U.S. National Science Foundation (NSF), the European Commission (EC, via CORDIS), and UK Research and Innovation (UKRI), 2015–2025 — in which recipient organizations are merged on ROR identifiers, investigators on ORCID, and 156,877 research outputs are linked to the grants that funded them through 285,604 OpenAlex acknowledgement edges.
The transformer paper-recommendation advantage is real at the head of the impact distribution and decays to null across the broad literature: a 4-checkpoint, all-26-field convergence study of SPECTER vs TF-IDF
A companion single-subfield study showed that SPECTER (a transformer pre-trained on the scientific-paper citation graph) beats a TF-IDF baseline at held-out citation prediction in High-Energy Physics (+15.4% relative MAP, p = 0.0005) — a large win, measured on the citation-dense top-cited slice of one subfield. The natural question — the one a practitioner faces when reaching for a neural paper-recommender — is whether that advantage generalizes.
What each funder funds: specialization, complementarity, and the surprising temporal stability of funder field-portfolios in a reconciled NIH/NSF/EC grant→output graph
Paper 01 in this series characterized who gets research grants (institutional concentration), who shares the resulting papers (co-funding), and how much output accompanies a dollar (the funding→output rate). It did not ask what is, structurally, a prior question: what does each funder actually fund, and how distinctively?
Public funding and researcher careers: funder portfolios, career-stage composition, and why the funded-vs-unfunded productivity gap is mostly selection, not effect
Papers 01–03 in this series studied the funding graph without ever touching the people side: a grant's principal investigator (PI) was a name-only node with no ORCID, so funding could not be joined to careers at all. A new conservative resolver closes that gap, producing a grant_pi_person bridge that links 528,570 of the 1,740,326 PI edges (30.4%) to 59,180 distinct canonical researchers (490,839 edges carry an ORCID).