Every method counts

In this study we explore the concurrent, combined use of three research methods, statistical corpus analysis and two psycholinguistic experiments (a forced-choice and an acceptability rating task), using verbal synonymy in Finnish as a case in point. In addition to supporting conclusions from earlier studies concerning the relationships between corpus-based and ex- perimental data (e. g., Featherston 2005), we show that each method adds to our understanding of the studied phenomenon, in a way which could not be achieved through any single method by itself. Most importantly, whereas relative rareness in a corpus is associated with dispreference in selection, such infrequency does not categorically always entail substantially lower acceptability. Furthermore, we show that forced-choice and acceptability rating tasks pertain to distinct linguistic processes, with category-wise in- commensurable scales of measurement, and should therefore be merged with caution, if at all.

Comparing type counts

This work is a case study of applying nonparametric statistical methods to corpus data. We show how to use ideas from permutation testing to answer linguistic questions related to morphological productivity and type richness. In particular, we study the use of the suffixes -ity and -ness in the 17th-century part of the Corpus of Early English Correspondence within the framework of historical sociolinguistics. Our hypothesis is that the productivity of -ity, as measured by type counts, is significantly low in letters written by women. To test such hypotheses, and to facilitate exploratory data analysis, we take the approach of computing accumulation curves for types and hapax legomena. We have developed an open source computer program which uses Monte Carlo sampling to compute the upper and lower bounds of these curves for one or more levels of statistical significance. By comparing the type accumulation from women’s letters with the bounds, we are able to confirm our hypothesis.