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Based on the two approaches, Bayyen provides another way of testing productivity, which is named as the 'potentiality' of a given rule. 'This potentiality measure is the quotient of the number of possible forms S and the number of actual forms V with a given affix in a sufficiently large corpus of text' (Bauer, 2001, p.24). However, although it involves the morphological rules in it, this measure has its flaws. S should be infinite, which is impossible.

Actually, the approaches discussed above do not supply probability measures but only quantifications. Now, I will turn to the probabilistic model. The essential problem of this model is to provide a large enough corpus sample. It is the base of probabilistic model. Most linguists object to take a dictionary-based approach. The British National Corpus is seen as a proper large corpus.

Two main productivity measures proposed by Bayyen are widely used now, although they still have shortcomings. One puts productivity in a narrow sense, P and the other is 'global productivity' in the broad sense, P*. P can be analyzed as: P=n1/N. It can be illustrated as the ratio of the number of hapax legomena with a given affix to the total number of tokens of all words formed by that affix. P represents 'the rates at which new types are to be expected to appear when N tokens have been sampled' (Plag, 2003, p.26). It means that P tests the probability of combining with new and unobserved types on the basis of N equals with the sample of relevant observed types. Many scholars have doubt the importance of hapx legomena. Actually, new, unobserved types are uncommon in a corpus. That is the reason. In a large enough corpus, the figure of hapax generally could half the observed word size. The number of hapax of a defined morphological process is related to the number of new words formed by the process. Therefore, hapax could refer to the indicator of productivity. Psycholinguists suggest that the proportion of new words among attested types increases with decreasing type frequency. This is because high frequency words are more likely to be stored in the mental lexicon than the low frequency words.

Now I will turn to the problem of P, which means 'with a given affix'. In order to calculate the P, it is essential to list out all words with a given affix in a certain corpus. It seems like an easy work. Actually, there are two main questions that need to be considered. The first is how to determine which word can bear the affix in question. The second is to control for cohort effects in multiple affixation. Some of the words are easy to sort out due to the low degree of lexicalization while others are not. Another problem is the sampling of multiply affixed words. Take the suffix -ize and -able for example. When we come into a word, coventionalizable, should we call it as the category of -ize or -able?

What above discussion illustrates is that even a “purely” quantitative approach cannot do without qualitative decisions.

Global productivity was initially introduced as a 'bi-dimensional' measure. P* is counted on the base of the CELEX databa本论文由英语论文网提供整理，提供论文代写，英语论文代写，代写论文，代写英语论文，代写留学生论文，代写英文论文，留学生论文代写相关核心关键词搜索。