SUN IN SEAD

Data platforms frequently promise that the same input will produce the same output. The promise is attractive, but often false because “the same input” is defined too narrowly. A computation depends not only on source records but on code, configuration, reference data, library versions, execution engines, clocks, seeds, policies, and hidden environmental state. This essay distinguishes repetition, determinism, reproducibility, replicability, and auditability. It formalises a data computation as a function over an extended state space, examines sources of non-determinism in distributed and temporal systems, and proposes an evidence model for reproducible outputs. The philosophical question is one of identity through time: when are two executions instances of the same computation, and when is a numerically equal result merely accidental? The essay argues that reproducibility is not achieved by rerunning code but by preserving the computational world in which a claim was produced.