Are Whitepaper Claims Reflected in Market Structure? A Contamination-Aware Pipeline and a Power-Limited Null

Abstract

Do the functional narratives in cryptocurrency whitepapers correspond to how their tokens behave in markets? We develop a content-verified, contamination-aware pipeline for measuring structural correspondence between project narratives and market structure, and report two results. The first is cautionary: an apparent entity-level alignment signal in an earlier corpus was entirely an artefact of corpus contamination — roughly a quarter of the documents were failed-download stubs or wrong-document whitepapers — and does not survive content verification. The second is an honest null: combining zero-shot NLP classification of 43 content-verified whitepapers with seven cross-sectional market-structure statistics, aligned via Procrustes rotation and Tucker's congruence coefficient, we do not detect significant claims–market alignment (dimension-matched φ = 0.303, non-significant). A positive-control and power analysis shows the binding constraint is the low reliability of the text instrument. The contribution is a method plus a cautionary tale for text-based studies of narrative–market correspondence, which routinely operate below an unstated detectability floor.