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Model reputation as counterparty assurance gradient across four tiers

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Add research on the journey from gamable opinion signals (reviews, ratings)
through observed metrics (PAYDEX, SLA stats), financial commitments (bonds,
escrow), and adjudicated outcomes (arbitration, courts). Resolve OpenQuestions:
no Reputation entity; use Reputation Signal, Performance Evidence, Commercial
Commitment, and Adjudication Outcome with Counterparty Assurance Gradient pattern.
This commit is contained in:
Bernd Worsch
2026-06-21 22:57:28 +02:00
parent 0741a2e3a5
commit bd272151af
10 changed files with 383 additions and 11 deletions
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@@ -126,4 +126,9 @@ later explicit package is extracted.
- Link registry identifiers for the same entity via Synonymity Assertion when
multiple registries describe one Organization/Legal Entity.
- Separate CRM Account and Stripe Customer as Commercial Records; never merge with login Account.
- Use qualified credentials (eIDAS seal, VC) as Evidence for Commercial Commitment where applicable.
- Use qualified credentials (eIDAS seal, VC) as Evidence for Commercial Commitment where applicable.
- Map reviews and star ratings to Reputation Signal (opinion tier); never merge with credit scores or legal outcomes.
- Map PAYDEX, SLA metrics, and credit bureau data to Performance Evidence (observed tier).
- Map bonds, escrow, and signed SLAs to Commercial Commitment (committed tier).
- Map arbitration awards and court judgments to Adjudication Outcome (adjudicated tier).
- Trust Relationship projections must cite assurance_basis tier; weight opinion weak by default.