From Popper to Lakatos: A Case for Cumulative Computational Modeling

An important problem with several modeling enterprises in psycholinguistics is that they are not cumulative, unlike successful experimental research. For example, in the field of language production, quite a few models focus on a few findings only instead of trying to account simultaneously for a wide range of data. Even worse, some investigators treat their models like their toothbrushes by using them only for their own data. There is no guarantee that these micromodels can be integrated into a single comprehensive macromodel, because micromodels are often mutually incompatible. Moreover, experimental tests of models developed by others are often conducted in the world of a misinterpreted Popper, where testing models is like skeet shooting. 1 The aim is to shoot down