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15 years of collostructions


 This paper discusses a variety of potential shortcomings of most of the most widely-used association measures as
 used in collocation research and collostructional analyses. To address these shortcomings, I then discuss a research program
 called tupleization, an approach that does away with the usual kinds of information conflation by keeping
 relevant corpus-linguistic dimensions of information – e.g. frequency, association/contingency, dispersion, entropy, etc. –
 separate and analyzing them in a multidimensional way; I conclude with pointers towards how these dimensions could, if deemed
 absolutely necessary, be conflated for the simplest kinds of of rankings as well as strategies for future research.