Hackathon Judges Score Same Project Twice, Show 1.11 Point Average Self-Disagreement

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An analysis of hackathon judging data revealed three judges scored the same project twice under different IDs. The judges' scores for the identical project differed by an average of 1.11 points. This self-disagreement exceeds the 0.68-point variation predicted by the authors' statistical noise model. The data came from a sample set for the fictional DOGFOOD 2026 hackathon platform competition. The finding raises questions about the consistency of subjective judging in such competitions.

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