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 "name": "Streaming Trustworthy Ai For Data Governance Explaining Compliance Decisions Using F92Edf17De",
 "text": "Trustworthy AI for Data Governance: Explaining Compliance Decisions Using SHAP and Causal Inference presents the following source proposition: Integrating new technologies into data governance calls for a deep look at how compliance, transparency, and user trust all work together in AI systems. This proposition is pertinent to Kaal's source-bound claim that Because the CHARITYxDAO records governance on distributed ledger technology, all governance votes and endowment allocation decisions are fully publicly visible, auditable by the public at will, and immutable once on chain. 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.",
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  "identifier": "https://orcid.org/0009-0008-7840-1847"
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  "Primary mapping confidence: 0.3605.",
  "The source-to-claim mapping remains explicitly ambiguous and is published with that limitation."
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  "url": "https://doi.org/10.36948/ijfmr.2025.v07i04.51762"
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  "citation": "Wulf A. Kaal, How Decentralized Autonomous Organizations Optimize Charitable Giving (2021). SSRN: https://ssrn.com/abstract=3981021",
  "paper": "Wulf A. Kaal, How Decentralized Autonomous Organizations Optimize Charitable Giving",
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