The main proposal in Hoji 2009 contains the thesis in (10).

(10)If we want to discover the properties of the Computational System that is hypothesized to be at the center of the language faculty, what I call a confirmed schematic asymmetry should be considered as the minimal unit of 'facts' for such research; see also (58) below.

Much more emphasis is placed in my current work on confirmed predicted schematic asymmetries than on confirmed schematic asymmetries. The former is necessarily deduced from universal and language-particular hypotheses. But attaining the latter is not an easy task, but that would be a minimal requirement for ensuring testability.

In evaluating one's empirical claim, it is useful to distinguish two types of "data," whether is it a confirmed predicted schematic asymmetry or a confirmed predicted schematic asymmetry. One type is what has led one to one's proposal and the other is what is newly predicted by the proposal. The distinction is similar to the distinction made in:

"There is also a more subtle problem.
When you have put a lot of ideas together to make an elaborate
theory, you want to make sure, when explaining what it fits, that
those things it fits are not just the things that gave you the idea
for the theory; but that the finished theory makes something else
come out right, in addition." (From "Cargo Cult Science" by Richard Feynman, found here, for example (as of March 11, 2012)).

Answers we hear to the question about testability, i.e., the question of how one's proposal can be shown to be "wrong," typically do not distinguish the two "types" of data. While we can talk about testability with respect to how valid the accepted empirical generalizations are, it must be recognized that their validity is something basic and what should really be at stake is how the newly made predictions are borne out. If a given proposal is based on alleged generalizations that can easily be, or have already been, shown to be invalid, however, it is not clear what significance can be assigned to the results of an experiment that tests a new prediction that one has made under hypotheses that presuppose the validity of such generalizations; see some remarks under Generalizations [42423].