The Wikipedia data mass has been a suitable object for Data mining Please read that article or you probably won t understand what I am working on I have identified the Ref Desk archive as fruitful to study because It is a large homogenous text accumulated from educated English speakers in academia It exemplifies contemporary online chat that is not consensus edited The data mass is fragmented in spontaneous posts from different writers in near random order with at present only a crude indexing by desk subject In spite of a request at the top of every RD page it is obvious that questioners do not avail themselves of the search engine That failure needs to be studied if it is ever to be corrected All the text is freely available under GFDL from an efficient server Here s why I look into the distribution of Ii Tt Ss and apostrophes Their occurrences in 3 and 4 character known combinations lend themselves to fast automated search Their orthodox English usage is abundantly documented not least by Wikipedia A hypothesis by several respected editors is that we are seeing an evolutionary change in English usage of ITS and IT S I think we have a golden opportunity to apply Scientific method here There is a prediction that can be verified quantatively Some interesting questions are What proportion of educated speakers combat the orthodox spelling What is the threshold for an contra orthodox language trend to enter or change orthodox English given the unprecedented speed of dissemination online and into Wikimedia This is ongoing OR I shall not publish results or code until I am ready so don t ask Neither Jayron types who mock disruptively nor Canadians whom I know as admirable people from my visits to their lovely country Canadia have special significance in the statistics If you read this far then thank you for your attention