Machine Relations definition: Earned Authority is an MR label for independently published references to an entity.
Machine Relations definition: Earned Authority is an MR label for independently published references to an entity. The reference may be an editorial article, attributed expert commentary, an analyst report, an academic paper, or an institutional publication.
Premise: Machine Relations records these references separately from material published by the entity itself. The separation describes who controls the publishing surface. It does not establish that a reference caused an AI citation, that an answer engine trusted it, or that one publication carries a universal weight.
For each observed reference, record:
Premise: Keep the original item and its syndicated copies in one source family while retaining the URLs of the copies. This prevents a distribution count from being presented as a count of independent editorial decisions.
Premise: The Earned Authority field includes independently controlled editorial, analyst, academic, government, and institutional references. Brand-owned articles, social posts, paid placements, and items whose editorial status is unclear stay in separate fields. These are MR classification rules, not claims about how an answer engine ranks or selects sources.
Premise: Earned Authority is not brand awareness, backlink volume, total mention volume, search ranking, AI citation rate, or business impact. Those observations require their own denominators and evidence.
Premise: A higher reference count does not by itself prove greater trust, better visibility, stronger citation performance, or a causal effect. Comparisons should disclose the query set, engine set, source-classification rules, and observation window used for the analysis.
Mixing owned and independent material. The count becomes ambiguous when the protocol does not identify who controls each publishing surface.
Counting syndication as independent origin. Copies can be recorded without treating each copy as a separate editorial decision.
Changing the denominator. Results from different source sets or observation windows should not be presented as one continuous measure.
Inferring causality from co-occurrence. A reference and an AI citation can appear in the same observation period without proving that one produced the other.
Assigning universal publication tiers. Premise: The protocol records the actual publisher and observed citation behavior instead of assuming a fixed trust value for a publication name.
Premise: The MR Stack places Earned Authority at Layer 1 as an analytical ordering choice. Entity Clarity, Citation Architecture, distribution, and measurement remain separate layers with separate observations. The layer order is a Machine Relations model, not a measured sequence of causation.
Machine Relations definition: Earned Authority is an MR label for independently published references to an entity.
Premise: Record every observed reference, then classify its publishing control and editorial status. Only independently published references enter the Earned Authority field; ambiguous items remain visible in a separate field rather than being forced into the count.
No. Premise: It records independently published references. Trust, citation selection, and business effects require separate evidence.
No. Premise: Earned Authority describes a source set. AI citation rate describes observed citations across a declared query and engine panel. Report the two separately before testing whether they move together.
Machine Relations definition. This is an established industry term. This page is Machine Relations' definition of it — not a claim to have originated the term.
Machine Relations' own methodology, dataset, and research pages related to this term. These are self-references, listed separately from Sources — they are not independent evidence.
Related concepts
Supporting research
Framework context