Looking at Geoff's post on machine-translated phishing scam messages, the message certainly does come across as very similar to the English output we in the biz frequently see coming out of statistical machine translation of Chinese. This includes Chinese-specific issues like recovering correct determiners from a language that does not express them overtly (I hope that the [not this] letter meets you in good spirits), as well as the ubiquitous phenomenon of sentences that are locally coherent — thanks to phrase-level translations and good statistical language-models for English — but globally nonsensical. I don't claim to know what makes a text poetic, but it seems to me that this combination of local coherence and larger-scale disconnectedness must be at least partly responsible for what Geoff describes as the "strange poetry" of machine translationese.
For some very recent work on human translationese, see Moshe Koppel and Noam Ordan's nice discussion of Translationese and its Dialects at the recent Association for Computational Linguistics Conference in Portland. They used text categorization methods to tease apart interference from the specific source language from more general effects of the translation process itself. Koppel is applying text categorization ideas in a lot of interesting areas: he's also the also the lead author of the paper Mark wrote about the other day in Biblical scholarship at the ACL.