![]() ![]() If the methodology is followed correctly, the scientist will arrive at an empirically motivated theory to describe the phenomena under consideration. ![]() This theory is derived from the data by inductive processes. ![]() Following ( Dougherty's, 1994) characterization, we can say that in an inductive model there exists a certain set of procedures and operations with which the scientist uses the data to develop a theory to adequately describe the phenomena under investigation. The relationship between data and theory in science is different depending on whether an inductive or a deductive methodology is employed. The How Many Languages do We Need to Formulate a Theory of the Faculty of Language? section discusses ways in which the two theoretical models diverge markedly in their conceptions of the object of study, using an analogy with research on the role of environmental stimuli in language acquisition to justify my claim that the two models have different “tolerance thresholds” regarding data on linguistic variation. In the following section Introduction: Two Ways of Relating Data and Theory consider how these models are instantiated in contemporary theories of linguistic diversity. The remainder of this section deals with the specific senses in which I use the expressions inductive model and deductive model and how both models are related in general to the data that they use. My goal is to show that the degree of the impact of these new sources of information will be different depending on the type of linguistic theory involved: the impact can be notable for linguistic traditions based on the inductive method, but will surely have a more modest effect (although not necessarily an irrelevant one) for traditions that adopt a deductive methodology. I do not intend in to question this general statement in any way, yet I would like to qualify it in the context of contemporary linguistic theory. In principle, it seems safe to say that obtaining new evidence can only be beneficial for any science. ![]() It is impossible to predict whether the rapid development of new sources of data on linguistic variation, as a result of the expanding breadth and scope of information technologies, will have a comparably large impact on linguistic theory (and especially on syntactic theory). Introduction: Two ways of Relating Data and Theory Hence, the expectation of progress that new sources of data on language variation can provide for linguistic theory should be modulated according to the objectives and assumptions of each language theory. That is, the two types of theory have a different “tolerance threshold” regarding the sparseness of data. My aim is to show that the type of data that can falsify a certain linguistic theory is different depending on whether the theory is deductive or inductive. I propose that the two main types of current linguistic theory (functionalism and formalism) correlate broadly to different scientific methods: the inductive one (which proceeds from languages to language) and the deductive one (which proceeds from language to languages), respectively. Moreover, the type of linguistic theory itself depends on the way in which the object of study is conceived. Using as a model the perennial question of how many languages should be considered to formulate a general theory of language, I will show that discussions about the type and amount of data needed for linguistic theorizing cannot be fruitful without taking into account the type of linguistic theory and its goals. The present contribution addresses a different but related issue, that of the amount of data on variation in languages needed by a linguist to develop a theory of language. Yang's (2016) Tolerance Principle describes with incredible precision how many exceptions the mechanisms of child language acquisition can tolerate to induce a productive rule, and is a notable advance in the long-standing controversy as to the amount of data necessary for the acquisition of language. Department of General and Hispanic Linguistics, University of Zaragoza, Zaragoza, Spain. ![]()
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