A fundamental hypothesis in generative grammar includes the existence of the language faculty, understood as an algorithm whose input is a set of items taken from the mental Lexicon of the speaker and whose output is a pair of mental representations – one underlying 'meaning' and the other 'sounds'. The main goal of generative grammar can thus be understood as demonstrating the existence of such an algorithm and discovering its properties. Construed in this way, it is not language as an external 'object' but the language faculty that constitutes the object of inquiry. In the terms of the distinction made by Chomsky in the 1960s, generative grammar is concerned with competence rather than with performance. *******The data in actual research activities in generative grammar, however, is based on acceptability judgments on a given sentence, whether they are introspective judgments by the researchers or their informants or observation of various other types of reactions by 'subjects' in an experimental setting. I.e., what we deal with in an attempt to discover the properties of the speaker/hearer's competence (the Computational System) is his/her performance (i.e., language use, in a broad sense). This makes it crucial, in the context of generative grammatical inquiry as construed above, to articulate how we can extract from performance data evidence for a hypothesis about the properties of the Computational System. The absence of a minimally satisfactory articulation of how to do this is likely to lead to a situation where different (groups of) researchers base their proposals about the Computational System on different sets of speaker judgments, collected in a variety of ways, that are not necessarily uniform or robust, being subject to a great deal of fluctuation and variation not only among speakers but also within a single speaker. This makes it difficult to evaluate competing proposals in a reliable and objective manner. Recent debates in leading journals (e.g., Language, Lingua and Natural Language and Linguistic Theory) about what should qualify as data, about the use of introspective judgments as crucial evidence for or against a theory, etc. seem to suggest that we have not yet developed a means to evaluate the empirical bases of hypotheses in generative grammar that is compelling enough to the majority of the practitioners. An evaluation of a given hypothesis thus tends to have an arbitrary aspect to it, influenced by such factors as whether or not the terms and concepts utilized are of a theory currently in fashion and whether or not it endorses the standard view concerning the validity of alleged empirical generalizations, regardless of how much or how little 'repeatability' obtains in regard to the predicted speaker judgments on the crucial sentences. *******My research objective is to overcome the problem just noted, by articulating a concrete means to evaluate (not to arrive at) hypotheses in generative grammar, making specific reference to Japanese as its empirical basis for an illustration of its methodological point. The methodological aspects of its results should be applicable to research on other languages, as long as it deals with interpretations that are claimed to be based crucially on properties of the Computational System. *******When one aims at discovering the properties of the language faculty as construed above, one must recognize the following: the Computational System's yielding something as its output does not guarantee that the speaker finds it (more precisely, finds its surface manifestation) to be acceptable; after all, non-grammatical as well as grammatical factors must contribute to the ultimate acceptability judgment by the speaker on a given sentence form under a specified interpretation (e.g., one's knowledge about the world, one's belief system, and the like). The Computational System's failure to yield something as its output, on the other hand, should necessarily mean that the 'sentence form' corresponding to such a 'failed representation' should be judged unacceptable under the specified interpretation. If something is predicted to be impossible due to the hypothesized formal properties of the Computational System under discussion, how can some pragmatic adjustment save it? Only by taking this point to heart and by putting forth a hypothesis so as to yield a negative prediction (the prediction that something is impossible (under a specified interpretation)), do we have a hope of making generative grammar an empirical science or of making it a progressive research program in the sense of Lakatos 1970.

Hypothesis testing and methodology in generative grammar, philosophy of science and generative grammar, Japanese syntax