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 "identifier": "kaal:position:2026-07-31-7750",
 "additionalType": "https://wulfkaal.github.io/positions/schema.json#AffirmedPositionClaim",
 "name": "Streaming Shield Decentralization For Safe Reinforcement Learning In General Parti E79E067B0C",
 "text": "Shield Decentralization for Safe Reinforcement Learning in General Partially Observable Multi-Agent Environments presents the following source proposition: Most real-world tasks do not satisfy this strong assumption. This proposition is pertinent to Kaal's source-bound claim that The unusual multi-millennial stability of Ancient Egypt and Imperial China, despite their strong political hierarchies, is explained by protocol decentralization rather than by any feature of their political centralization. The proposed response is an extension: the relationship should remain limited to the retrieved source proposition and the mapped Kaal claim unless fuller source review supports a broader conclusion.",
 "author": {
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  "name": "Wulf A. Kaal",
  "identifier": "https://orcid.org/0009-0008-7840-1847"
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 "dateModified": "2026-07-31",
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  "External evidence level: abstract indexed.",
  "Mapping review tier: moderate-confidence claim review.",
  "Primary mapping confidence: 0.3531.",
  "The source-to-claim mapping remains explicitly ambiguous and is published with that limitation."
 ],
 "currentDebate": {
  "name": "Shield Decentralization for Safe Reinforcement Learning in General Partially Observable Multi-Agent Environments",
  "url": "https://doi.org/10.65109/vaar1124"
 },
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  "identifier": "kaal:claim:3782193-004",
  "url": "https://wulfkaal.github.io/claims/3782193-004",
  "citation": "Craig Calcaterra, Wulf A. Kaal, Historical Sketches of Centralization vs. Decentralization (2021). SSRN: https://ssrn.com/abstract=3782193",
  "paper": "Craig Calcaterra, Wulf A. Kaal, Historical Sketches of Centralization vs. Decentralization",
  "authors": [
   "Wulf A. Kaal"
  ],
  "year": "2021",
  "ssrn": "https://ssrn.com/abstract=3782193",
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 },
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   "name": "Shield Decentralization for Safe Reinforcement Learning in General Partially Observable Multi-Agent Environments",
   "url": "https://doi.org/10.65109/vaar1124"
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 "recordTypeNote": "Dated commentary position extending a scholarly corpus claim. Not a verbatim claim extracted from the paper.",
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 "mappingMethod": "idf-weighted multi-field mapping v1",
 "mappingWhyRelevant": "Shared high-information concepts: decentralization, multi, strong. Scope: comparison against contemporaneous civilizations that rose and fell.",
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  "queryId": "concept:a2c487c0792c",
  "queryText": "autonomous agent accountability",
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  "workAuthors": [
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    "whyRelevant": "Shared high-information concepts: decentralization, learning, tasks. Scope: conditioned on a reliable and high reputation score worker completing the tasks.",
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    "whyRelevant": "Shared high-information concepts: decentralization, most, real, not. Scope: applies to existing decentralized systems generally.",
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