Score contribution per author:
α: calibrated so average coauthorship-adjusted count equals average raw count
We review key stages in the development of general‐to‐specific modelling (Gets). Selecting a simplified model from a more general specification was initially implemented manually, then through computer programs to its present automated machine learning role to discover a viable empirical model. Throughout, Gets applications faced many criticisms, especially from accusations of ‘data mining’—no longer pejorative—with other criticisms based on misunderstandings of the methodology, all now rebutted. A prior theoretical formulation can be retained unaltered while searching over more variables than the available sample size from non‐stationary data to select congruent, encompassing relations with invariant parameters on valid conditioning variables.