Global Risks Forum 2025
Micro-production Model (MPM)

Bounties

Bounties are precision-scoped, performance-based tasks that support the open-source development of critical components across the Nexus Platform. Contributors tackle specialized challenges in HPC modeling, parametric finance, AI-based early warning, or data harmonization—earning pCredits for validated outputs. Governed under GRA’s technical and RRI review structures, Bounties power modular, auditable risk tools deployable at national and global scale. As the core engine of the Nexus Micro-Production Model (MPM), Bounties align expert contribution with operational needs—bridging innovation with impact in disaster risk reduction, financing, and intelligence

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Bounties are targeted, higher-value tasks that require specialized skills and a tangible outcome—like refining a parametric finance script or developing advanced analytics for hazard data. Unlike Quests (which often focus on smaller on-ramp tasks), Bounties typically have structured outputs, robust peer reviews, and integration paths that demand more thorough domain knowledge

Any recognized contributor—from institutional members to domain specialists—can propose a Bounty if they identify a significant challenge in DRR, DRF, or DRI that benefits from open collaboration. The Bounty must pass a short approval cycle, ensuring alignment with RRI, strategic objectives, and data ethics guidelines

Bounties are modular development units. Each Bounty defines its scope, deliverables, and RRI constraints. By working in these discrete, trackable chunks, contributors can efficiently tackle real-world challenges (e.g., verifying risk finance triggers, building new dashboards) without losing synergy across the larger open innovation ecosystem

Bounties may involve data ingestion improvements, advanced analytics, geospatial model validations, parametric instrument expansions, or integration of domain knowledge (such as local hazard references). They often require coding, data science, design thinking, or policy expertise to yield high-impact outputs for risk management or finance solutions

Each Bounty is reviewed and governed under RRI guidelines. Technical tasks must include disclaimers or ethical reflections (e.g., potential biases in data sets or local sovereignty issues), while policy-centric tasks often require multi-stakeholder feedback. Participants document these considerations to ensure the solution remains transparent, inclusive, and socially responsible

Successful Bounty completion yields participation credits (pCredits) or partial validation credits (vCredits) if the task demands advanced review. Contributors also gain visibility, an enhanced reputation across Nexus Platforms, and deeper engagement rights (like proposing further expansions or leading certain Build sprints)

Bounties typically require multi-phase approval: (1) a technical review by domain colleagues to confirm solution quality, (2) an RRI oversight check for data or policy compliance, and (3) possible local stakeholder feedback if relevant to parametric triggers or cross-border governance. Final acceptance triggers the awarding of pCredits or partial vCredits

Yes. If new data emerges or local conditions shift, existing Bounties can be repeated with updated parameters (e.g., new climate data sets). Bounties can also be extended to incorporate larger tasks or forked by domain subgroups who adapt the deliverable for another region or hazard type, thereby fostering iterative open development

Bounties are building blocks for multi-stakeholder “Builds.” Teams may compose multiple Bounties into a cohesive pipeline—e.g., verifying hazard polygons, refining parametric logic, and building real-time dashboards. Once completed, these Bounties collectively yield a final deployable module or cross-regional initiative that addresses a critical risk problem

Depending on the scope, Bounties may yield data pipelines, parametric contract code, advanced risk dashboards, or domain-focused reports for policymaking. Each deliverable is version-controlled, documented with disclaimers, and integrated into the open environment to ensure it remains scalable, ethically valid, and adaptable for local or global DRR, DRF, and DRI needs

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