You're pledging to donate if the project hits its minimum goal and gets approved. If not, your funds will be returned.
The Omega Framework is a scoring instrument built on three domain-agnostic axioms drawn from thermodynamics: all viable systems maintain low entropy through energy investment, all systems have critical thresholds below which recovery is impossible, and all systems follow either damping recovery or spiraling collapse dynamics. Because these axioms describe the same mathematical structure across all complex adaptive systems — not metaphorically, but structurally — the framework applies identical 26-factor measurement logic to any system that processes information and maintains coherence over time.
This universality claim has been tested, but the testing to date has been conducted independently by the framework's developer, applying the methodology to 60+ real-world subjects and systems across 23 distinct domains — including romantic relationships, organizations, leadership dynamics, therapeutic processes, AI agents, consciousness states, neurodivergent cognition, coercive control dynamics, food systems, and geopolitical structures. A subset of these analyses has been published openly on WordPress as the framework's public track record. No external, blinded, or independently-run trials have been conducted yet — that gap is precisely what Phase 0 funding is intended to close.
Novel structural findings emerged as a byproduct of this internally-conducted testing process: the discovery that some entropy is constitutive rather than pathological (explaining why standard tools misclassify neurodivergent systems as disordered), the identification of a hidden collapse precursor the framework calls "Dead Calm" in apparently stable systems, and the formal separation of architectural from agentive harm as categories requiring different interventions. These findings are internally consistent and axiomatically grounded, but they remain unvalidated by any party other than the framework's creator — which is the honest and central limitation this funding round exists to address.
In June 2026, the framework was applied to itself using the same self-conducted methodology. The result was a score of 8.27 out of 10 — in the Thriving range — with all safety checks passing. The self-analysis produced a candid structural map: the framework's coherence currently depends entirely on its creator, with no institutional or independent validation buffering it. It calculated the cost of resolving that vulnerability at $10,000–$20,000 for a Phase 0 inter-rater reliability study — the first step toward independent, external confirmation.
The framework is fully built and deployed as a working application (web and Android). Selected published analyses are available at https://omegaframework.wordpress.com. This funding request covers Phase 0: the first step toward moving the framework's evidence base from single-author testing to independently verified results.
Primary goal: Move the framework's evidentiary base from internally-conducted analysis to externally-validated results. Specifically, establish inter-rater reliability of r ≥ 0.70 among independent raters with no prior involvement in the project — the standard first gate for validating any new measurement instrument. This is the step that has not yet happened: everything to date has been one person applying the framework and publishing selected results, and Phase 0 is designed specifically to test whether other people, using the same protocol, arrive at consistent conclusions.
Secondary goal: Produce Tier 1 rapid-assessment training materials that allow practitioners to apply the framework accurately without direct guidance from its creator — necessary groundwork for the independent raters in the primary study to succeed, and for any future adoption beyond the developer.
How we get there:
Recruit 15–20 independent raters through an established participant platform who have no prior exposure to the framework or its creator
Provide standardized training materials derived from the published v24.0 specification
Score a shared set of 10–15 subjects or systems across at least two domains, comparing rater results against each other (not against the developer's prior published scores)
Run inter-rater reliability analysis (Cohen's kappa, intraclass correlation coefficient)
Publish results as an open-access pre-print (arXiv or OSF) — the framework's first externally-generated evidence, distinct from the internally-conducted analyses published to date
Apply ablation testing to confirm each construct's necessity using the new independently-collected data, rather than the developer's own retrospective scoring
This funding covers Phase 0: an inter-rater reliability study establishing whether independent raters, using standardized training, produce consistent results when applying the framework.
Budget breakdown:
Ethics review board (required for human subjects research): $1,500–$3,000
Participant recruitment and compensation (15–20 raters, ~3 hrs each at $15/hr): $675–$900
Survey and data collection platform: $400–$800
Expert rater compensation (domain specialists, ~10 hrs each): $2,000–$4,000
Part-time research assistant (data processing and statistical analysis): $2,000–$4,000
Statistical review consultation (1–2 sessions): $500–$1,500
Pre-print publication and open-access fee: $0–$500
Phase 0 total: $7,075–$14,700
With the minimum funding of $10,000, the core validation study is fully executable. With the full goal of $50,000, the secondary goal is also funded: approximately six months of development time to build practitioner training materials and begin planning a follow-up construct validity study with an external research partner.
Ernest Jacob (Jake) Hahn — independent developer and researcher based in Caldwell, Idaho. Professional background in full-stack software development, with experience building and deploying production web and mobile applications. The Omega Framework was designed and built over approximately two years, developed in sustained collaboration with an AI language model — a fact disclosed openly because it is part of the project's story rather than something to hide.
Relevant track record:
Designed, built, and shipped the Omega Framework as a working application available on web and Android
Conducted more than 60 internally-run domain analyses across 23 distinct domains, with selected results published publicly at https://omegaframework.wordpress.com
Produced a 48,000-word self-assessment document in which the framework was applied to its own architecture, identifying its strengths, weaknesses, and the specific steps needed to resolve them
Conducted academic outreach to researchers at Harvard, Wharton, Stanford, MIT, Carnegie Mellon, UCL, and the Santa Fe Institute regarding academic validation pathways
Received a substantive response and phone consultation from Dr. Jennifer Feitosa at Claremont McKenna College's METRICS Lab — the framework's first external academic engagement to date
There are two categories of failure risk here: what happens to this specific project, and what the broader cost of the unsolved problem looks like if tools like this one don't get built and validated.
If this project specifically fails:
The framework's self-assessment identified the primary internal failure mode accurately: every piece of evidence generated so far — the 60+ domain analyses, the WordPress publications, the self-analysis itself — was produced by one person. There is currently no external confirmation that independent users applying the same protocol would reach consistent conclusions. That gap cannot be closed without the inter-rater reliability study this funding enables. Without it, the framework cannot be cited academically, cannot attract institutional co-authors, and cannot make credible claims to the researchers and practitioners most equipped to use and extend it.
The project does not disappear if this round fails. The application, specification, and published analyses remain publicly accessible. But the ceiling on its impact stays low until that evidentiary gap is closed, and the longer it remains a single-author system, the more fragile it becomes.
What the unsolved problem actually costs:
The deeper failure is not the project disappearing. It is the world continuing to operate without a mathematically grounded, domain-agnostic instrument for measuring ethical alignment and structural viability — in human institutions and AI systems alike. That gap has a measurable price tag across every sector this framework addresses:
Poor management and organizational dysfunction costs the U.S. economy over $500 billion annually in turnover and lost productivity alone, with excess bureaucracy estimated to account for more than $3 trillion in lost economic output — approximately 17% of GDP. These are not abstract losses. They are the direct result of organizations operating without reliable early-warning systems for structural collapse.
Misaligned and unsecured AI systems cost the global economy an estimated $1.2 trillion in 2025 through data breaches, operational failures, and regulatory non-compliance. Nearly every large company that has deployed AI has incurred initial financial losses, with combined reported losses across surveyed firms reaching $4.4 billion in a single EY study.
AI safety researchers have publicly documented that the gap between AI capabilities and the ability to verify alignment is widening, not closing — and that current alignment techniques optimize for stated preferences rather than the full scope of human values. The field lacks a standardized measurement instrument that treats ethical alignment as a structural property of a system's architecture rather than a behavioral checklist.
Job stress costs American employers more than $300 billion annually. Poor employee mental health costs an additional $47.6 billion in lost productivity. Relationship dissolution, coercive control dynamics, and therapeutic failure each carry their own economic and human costs that existing tools consistently fail to predict in advance.
What all of these numbers share is a common structural cause: the absence of a validated, universal instrument that can detect entropy accumulation, identify collapse trajectories, and distinguish architectural from agentive harm before a system fails — whether that system is a company, a relationship, a therapeutic process, or an AI agent.
The Omega Framework is the first instrument built from first principles to address all of these simultaneously using identical measurement logic. Phase 0 validation costs $10,000–$20,000. The measurable annual cost of the problems it is designed to predict and prevent runs into the trillions. The asymmetry between those two numbers is the most important thing in this application.
No external funding has been raised. The project has been entirely self-funded through independent software contracting and personal income. This Manifund application is the first formal funding request submitted anywhere.