Extension: Algorithmic Reputation Equivalence (ARE): A Methodology for Developing AI Decision-Stage Equivalents of Human Brand Reputation Measurement Frameworks
Algorithmic Reputation Equivalence reports that high human-perception reputation scores do not predict high AI decision-stage reputation scores and treats the two instruments as measuring categorically distinct phenomena. This provides a separate AI-facing example of why a single undifferentiated reputation measure can lose material information, extending Kaal's multidimensional-reputation requirement. It does not validate the WDAG design or transfer the brand-purchase result to dataset quality.
Affirmed commentary position. This record extends a source-bound scholarly claim but is not a verbatim paper claim.
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reputationgovernance-designhistorical-responsescholarly-literaturecrossref
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