Beacon Labs(prev Fracton Research) is an R&D institution for a positive sum world through exploring inclusive coordination design. We will bring plural funding mechanisms reflected plural values into a public goods space. We enable funding based on diverse value systems through a statistical approach. Current public goods funding makes a decision based on a single value framework, even though public goods has different outcomes which they would like to achieve. We envision a future where each public good receives funding optimized for its own unique goals, and we aim to build protocols that support Ethereum to thrive sustainably. We reflect the diversity of values they embody through evaluating and measuring the impact of public goods and funding mechanisms. While impact evaluation / measurement has been developed in recent years, most progress has focused on measuring the impact of OSS(open-source software). In contrast, there is a lack of evaluating non-technical activities such as educational influence and contributions to local communities. We envision a future where public goods can grow sustainably toward their respective goals by using outcome metrics tailored to each project. By pursuing funding mechanisms that reflect plural values and provide a greater sense of fairness and persuasion, we bring new light to the Ethereum ecosystem.
Past activities(excerpt):
Digital public goods have various value, so it is generally difficult to measure the value. That's why they don't pursuit their profit, but also pursuit different outomes. On the other hand, public goods funding mechanism is less though these outcomes and values are different. Beacon Labs aims to fill the gaps left by current public goods funding and to foster a world that respects diverse values. Specifically, by honoring the different outcomes of each project and by evaluating and measuring the impact of digital public goods and funding mechanisms, we set and apply outcome metrics optimized for each case, building protocols for funding that is fairer and more broadly trusted. This will enable all public goods to grow sustainably in line with their own visions and help secure the enduring prosperity of digital public goods.
Public goods funding is crucial for sustainably providing and maintaining public goods. Currently, in the public goods space, there is growing interest in how to provide funding for public goods fairly and effectively. However, questions such as "which projects (public goods) should receive more funding?" and "were these projects (public goods) truly effective for certain ecosystem?" should be investigated, but remain largely unaddressed.
For effective funding distribution, led by projects like Optimism, there is a trend toward retrospective funding based on past achievements rather than funding based on future expectations, as this is considered more reliable. However, the earlier questions still remain unanswered. To address these questions, there is increasing focus on effect verification and impact evaluation, with many projects beginning to work in this area.
Outputs are often easier to measure and thus more commonly tracked. However, to truly assess an intervention's effectiveness, one must prioritize outcomes, which often require gathering and analyzing more complex information. Formulating logic models (hypotheses about how your outputs lead to specific outcomes), then collecting data to test those hypotheses, is crucial. If the hypothesis is validated, allocating additional resources may be warranted; if it is disproven, a rethink is required. By iterating through a PDCA (Plan-Do-Check-Act) cycle, you can deepen your understanding of impact. In other words, evidence-based practice (EBP) is nessesary.
Evidence is needed in order to make a logic model. However, there is less "evidence communication" though there are many "evidence production"(EBP is often described as encompassing three stages: production, communication, and utilization of evidence. In other words, evidence must be generated—using methods such as randomized controlled trials or propensity score matching—and then applied to decision-making in a given context). We support "evidence communication" for bridging between evidence production and evidence utilization.
A solution of us is MUSE(Modular Stack of Evidence). MUSE is an EBP support system designed specifically for Digital Public Goods. While DPGs play a crucial role in addressing social challenges and advancing the Sustainable Development Goals (SDGs), their adoption of EBP faces three persistent barriers: fragmented and insufficient evidence, a disconnect between planning and execution, and the high cost and complexity of data collection and analysis.
MUSE addresses these challenges by seamlessly integrating three core functions: 1. evidence curation, 2. evidence citation, and 3. evidence improvement. It curates global evidence into standardized, reusable “evidence cards” that structure interventions, indicators, and outcomes. It then enables practitioners to easily combine these cards into logic models, linking evidence directly to project design and execution. Finally, MUSE strengthens evidence over time by feeding back real-world implementation data, enabling continuous improvement and the creation of new insights through meta-analysis.
3 Core Functions of MUSE:
As an open-source code, interoperable platform, MUSE connects with other open data infrastructures and tools, creating an ecosystem hub for impact-driven projects. Its design fosters accountability, transparency, persuasion and efficiency in digital public goods initiatives. For example, MUSE is used as the followings:
By lowering the barriers to EBP and embedding it into the fabric of digital public goods, MUSE empowers practitioners to maximize social impact and ensures that successful practices are rapidly shared and scaled across communities and domains.
