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This paper identifies the 'evaluation trap' where AI benchmarks inadvertently stabilize dominant paradigms by narrowing what counts as progress, and introduces Epistematics, a meta-evaluative methodology to ensure evaluation criteria discriminate true capability from proxy behaviors.