# Framework limitations `kaal:entity:framework-limitations` **Status.** derived This node is assembled mechanically from the 7 claims that carry the concept tag `framework-limitations`. It is a roster of what the corpus says under this term. It is **not** an adjudicated definition: no single statement here has been ruled canonical, and no first-appearance call has been made. Read the claims and judge for yourself. ## Every claim under this term 7 claims across 1 works, 2026 to 2026. **2026** - [6192998-007](https://wulfkaal.github.io/claims/6192998-007) [empirical/argued] *(failure mode)* -- The Calcaterra, Kaal, and Andrei 2018 framework satisfied manipulation resistance, autonomous operation, and computational tractability, but struggled with capturing nuanced quality, attributing value across cumulative contributions, and incentivizing knowledge sharing; existing frameworks achieve at most two or three of the six properties at once. > The Calcaterra-Kaal-Andrei framework (2018) achieved properties 1, 5, and 6 but struggled with 2, 3, and 4. Existing frameworks achieve at most 2-3 of these properties simultaneously. Wulf A. Kaal, Evolution of Domain-Specific Reputation Systems From Binary Validation to Citation-Weighted Knowledge Attribution (2026). SSRN: https://ssrn.com/abstract=6192998 - [6192998-010](https://wulfkaal.github.io/claims/6192998-010) [failure/argued] *(failure mode)* -- The two times corruption cost bound of the 2018 framework is conditional, not general: subsequent analysis shows it holds only under specific conditions that may not obtain in practice. > However, subsequent analysis reveals this bound applies only under specific conditions that may not hold in practice. This is a limitation we address in Section IV.F. Wulf A. Kaal, Evolution of Domain-Specific Reputation Systems From Binary Validation to Citation-Weighted Knowledge Attribution (2026). SSRN: https://ssrn.com/abstract=6192998 - [6192998-011](https://wulfkaal.github.io/claims/6192998-011) [failure/argued] *(failure mode)* -- The 2018 system produces only binary accept or reject outcomes, so it has no way to express intermediate assessments such as good but not great, or excellent innovation with poor execution. > Problem 1: Binary validation only. The system produces only binary outcomes (accept/reject). No mechanism exists to say "good but not great" or "excellent innovation, poor execution." Wulf A. Kaal, Evolution of Domain-Specific Reputation Systems From Binary Validation to Citation-Weighted Knowledge Attribution (2026). SSRN: https://ssrn.com/abstract=6192998 - [6192998-012](https://wulfkaal.github.io/claims/6192998-012) [failure/argued] *(failure mode)* -- Selecting a single agent per job by weighted random draw sacrifices quality assurance for efficiency, reflecting a broader pattern in DAO governance where efficiency optimization crowds out quality. > Problem 2: Single agent selection. The system randomly picks one agent per job, even if having multiple agents compete would improve quality. This reflects a broader pattern I have observed in DAO governance: efficiency optimization often sacrifices quality assurance. Wulf A. Kaal, Evolution of Domain-Specific Reputation Systems From Binary Validation to Citation-Weighted Knowledge Attribution (2026). SSRN: https://ssrn.com/abstract=6192998 - [6192998-013](https://wulfkaal.github.io/claims/6192998-013) [failure/argued] *(failure mode)* -- Without a working attribution mechanism, an agent whose foundational insight another agent builds upon receives no credit when the derivative work is validated. > Problem 3: No citation/attribution mechanism. If Alice creates foundational insight that Bob builds on, Alice receives no credit when Bob's work gets validated. Wulf A. Kaal, Evolution of Domain-Specific Reputation Systems From Binary Validation to Citation-Weighted Knowledge Attribution (2026). SSRN: https://ssrn.com/abstract=6192998 - [6192998-014](https://wulfkaal.github.io/claims/6192998-014) [failure/argued] *(failure mode)* -- The 2018 framework contained a citation graph concept, but its mathematics were underdeveloped and no game theoretic analysis established incentives for honest citation. > included a citation graph concept,37 but the mathematics were underdeveloped and no game-theoretic analysis established incentives for honest citation. Wulf A. Kaal, Evolution of Domain-Specific Reputation Systems From Binary Validation to Citation-Weighted Knowledge Attribution (2026). SSRN: https://ssrn.com/abstract=6192998 - [6192998-015](https://wulfkaal.github.io/claims/6192998-015) [failure/argued] *(failure mode)* -- The recursive post valuation formula in the original framework suffered from potential instability and provided no mechanism ensuring that citations reflect actual contribution rather than strategic manipulation. > However, the recursive formula presented suffered from potential instability and provided no mechanism ensuring citations reflect actual contribution rather than strategic manipulation. Wulf A. Kaal, Evolution of Domain-Specific Reputation Systems From Binary Validation to Citation-Weighted Knowledge Attribution (2026). SSRN: https://ssrn.com/abstract=6192998 ## Verify Every claim above resolves to a record carrying a verbatim source quote, the sha256 of the source PDF, and a preformatted citation. Nothing here asks to be taken on trust. curl -s https://wulfkaal.github.io/entities/framework-limitations.md | sha256sum **Canonical form.** This markdown file is the canonical hashed representation of this entity node. Its sha256 is the content hash.