Responsiveness Without Error: Proxy Success and Delayed Correction in Scientific Evaluation Systems

ABSTRACT Scientific and technical systems are increasingly evaluated through proxies: benchmarks, validation sets, rankings, indicators, and other standardized performance criteria. These proxies are necessary for coordination, comparison, and accountability. They also create a risk: a system can remain successful by its evaluative measure while becoming less sensitive to the target phenomenon the measure was intended to represent. This Research Note reframes that risk as responsiveness without error. Error correction refers to adjustment after an error has been registered within an evaluation system. Responsiveness refers to the prior capacity of that system to notice, weight, and act on target‐domain feedback before it appears as a formal anomaly or failed score. The note does not claim that proxy distortion, feedback failure, or metric gaming are new phenomena. Its contribution is a narrower temporal and diagnostic distinction: proxy‐coupled systems can lose responsiveness during the interval in which their measured performance still appears adequate. The paper defines this pre‐error interval, distinguishes it from Goodhart/Campbell effects, cybernetic feedback theory, Kuhnian anomaly, Lakatosian programme appraisal, shortcut learning, and responsible‐metrics research, and proposes a practical checklist for identifying responsiveness loss. The checklist is applied to a worked case from medical‐imaging shortcut learning and then extended briefly to research evaluation metrics and machine‐learning benchmarks. The note concludes that some failures of scientific and technical evaluation are not failures to correct known errors, but failures to keep evaluative channels coupled to the phenomena they claim to assess.