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An Intro to Hypercerts

A new method for funding public goods

TLDR: Hypercerts are a new way of rewarding and funding positive impact.

First proposed by David Dalrymple in March of 2022 in his talk on Interoperable mechanisms for non-rival goods (Hypercerts), hypercerts provide a stable model for financing public goods. Though the idea of impact certificates has been around longer, the novel approach powered by smart contracts provides a sustainable, transparent mechanism for implementation.

The Hypercerts Foundation, the org behind hypercerts, is supported by Protocol labs and has partnered with Gitcoin to provide certificates for the Gitcoin Alpha Round. Their goal is three fold:

  1. Provide recurring income for public goods

  2. Encourage the pursuit of high impact public goods

  3. De-risk the funding of impactful public goods

Hypercerts accomplish these goals by enabling retrospective funding for the most impactful goods, incentivizing projects to maximize their potential impact without worrying about risks. Funders can allocate their money with more certainty, as hypercerts provide evidence of a project's impact.

Hypercerts strive to be a single, open, shared, and decentralized database, enabling the interoperability of funding mechanisms. No matter the funding mechanism, either now or at some point in the future, hypercerts can reward both the funders and projects that have strived for significant impact.

More technically, a hypercert is a ERC-1155 semi-fungible token, where each unique token represents fractionalized ownership of a full hypercert, summing to 100% ownership. These tokens will be implemented multi-chain, and are designed to be transferred once, from the project to their contributors, and will then be soul-bound.

The interplay between funders, creators, and evaluators is depicted above, along with a potential dynamic system for hypercert implementation. Though it is early days for The Hypercerts Foundation, they have made great progress already. The current implementation uses NFT specs but there are further discussions around a custom ERC designed specifically for hypercerts.

The Hypercerts Foundation’s work is helping fuel the increasingly impactful new mechanisms for funding public goods, a cause we care about greatly at Atom!

For more reading, see some of the sources below and follow The Hypercerts Foundation on Twitter!

Fundwww.bmj.com/content/343/bmj.d4797ing grant proposals for scientific research: retrospective analysis of scores by members of grant review panelFuObjective To quantify randomness and cost when choosing health and medical research projects for funding. Design Retrospective analysis. Setting Grant review panels of the National Health and Medical Research Council of Australia. Participants Panel members’ scores for grant proposals submitted in 2009. Main outcome measures The proportion of grant proposals that were always, sometimes, and never funded after accounting for random variability arising from differences in panel members’ scores, and the cost effectiveness of different size assessment panels. Results 59% of 620 funded grants were sometimes not funded when random variability was taken into account. Only 9% (n=255) of grant proposals were always funded, 61% (n=1662) never funded, and 29% (n=788) sometimes funded. The extra cost per grant effectively funded from the most effective system was $A18 541 (£11 848; €13 482; $19 343). Conclusions Allocating funding for scientific research in health and medicine is costly and somewhat random. There are many useful research questions to be addressed that could improve current processes.ndwww.bmj.com/content/343/bmj.d4797ing grant proposals for scientific research: retrospective analysis of scores by members of grant review panel

Objective To quantify randomness and cost when choosing health and medical research projects for funding. Design Retrospective analysis. Setting Grant review panels of the National Health and Medical Research Council of Australia. Participants Panel members’ scores for grant proposals submitted in 2009. Main outcome measures The proportion of grant proposals that were always, sometimes, and never funded after accounting for random variability arising from differences in panel members’ scores, and the cost effectiveness of different size assessment panels. Results 59% of 620 funded grants were sometimes not funded when random variability was taken into account. Only 9% (n=255) of grant proposals were always funded, 61% (n=1662) never funded, and 29% (n=788) sometimes funded. The extra cost per grant effectively funded from the most effective system was $A18 541 (£11 848; €13 482; $19 343). Conclusions Allocating funding for scientific research in health and medicine is costly and somewhat random. There are many useful research questions to be addressed that could improve current processes.