Myth: Great discoveries come from brilliant individuals working alone in their labs.
Reality: Every "breakthrough" paper rests on hundreds of prior contributions—methods developed by postdocs in other labs, datasets collected by field researchers, software written by graduate students who never became professors, reagents optimized by technicians whose names appear nowhere in the acknowledgments.
Yet our funding system still operates on the lone genius model. Grants go to principal investigators. Awards celebrate individual names. Tenure committees count first-author and last-author publications. The entire apparatus assumes science is a series of individual achievements rather than a collective, cumulative process.
This creates a perverse incentive structure. Researchers optimize for visible, individual contributions rather than foundational work that enables others. Why spend three years building a dataset that fifty other labs will use when you could publish six incremental papers with your name in bold?
The problem compounds over time. Foundational contributions—the methods, tools, datasets, and negative results that make future discoveries possible—remain chronically underfunded because they do not fit the individual achievement model. Meanwhile, researchers who build on that foundation receive credit (and funding) for "novel" discoveries that would have been impossible without the invisible infrastructure beneath them.
Consider CRISPR. The headlines celebrated Doudna and Charpentier (rightly so). But the underlying biology depended on decades of obscure research into bacterial immune systems by scientists who never made the news. The funding system rewarded the final step, not the thousand steps that made it possible.
What if we could track scientific contribution the way we track software dependencies? What if funding could flow not just to the visible breakthrough but to the foundational work that enabled it—proportionally, transparently, based on actual demonstrated dependency rather than retrospective narrative?
This is what alternative research funding models attempt to solve: shifting from individual achievement to network contribution, from visible outputs to enabling infrastructure, from rewarding who crossed the finish line to sustaining everyone who built the track.
Discussion question: What foundational work in your field made your research possible but will never receive adequate recognition or funding under the current system? And what would change if we could properly value and fund that kind of contribution?
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