Selivan explains Trump speech similarities. No pigs seen flying


Leo Selivan has a rather off-hand way of treating research findings in corpus linguistics: he often uses undefined terms and blurred summaries to support his own particular view of ELT, which, let’s not forget, includes the breath-taking injunction “Never teach single words”. In his most recent post, Selivan repeatedly uses the term “chunks” without defining it, he misrepresents Pawley and Syder’s 1983 paper, and he then examines an excerpt from Melania Trump’s recent speech to the Republican party in order to demonstrate that “chunks”, not blatant plagiarism, explain the similarities with M. Obama’s 2008 speech.


1.  “Chunks”

Selivan says:

corpus research …. has shown that language is highly formulaic, i.e. consisting of recurring strings of words, otherwise known as “chunks”. What makes them chunks is the fact that they are stored in and retrieved from memory as ‘wholes’ rather than generated on a word-by-word basis at the moment of language production. 

Two comments are in order.

a)  What makes recurring strings of words “chunks” is not how they’re memorised, but rather their form.

b) It is not “a fact” that chunks are stored in and retrieved from memory as ‘wholes’. The hypothesis suggested by Pawley and Syder is that certain  types of strings of words are memorised and recalled in a certain carefully described way. By definition, this hypothesis is not true – it is a tentative theory which attempts to explain a problem.


2. Pauley and Syder

Selivan says:

The formulaic nature of language was first brought to the fore in a seminal paper by Australian linguist Andrew Pawley and and his colleague Frances Syder, who pointed out that competent language users have at their disposal hundreds of thousands of ready-made phrases (Pawley and Syder 1983).

Pawley and Syder’s paper was a lot more nuanced than Selivan suggests. They argued that control of a language entails knowledge of more than just a generative grammar, and that ‘memorized sentences’ and ‘lexicalized sentence stems’ (not “ready-made phrases”) were important additional parts of linguistic competence, useful in explaining the two puzzles of “nativelike selection” and fluency. As they say:

The terms refer to two distinct but interrelated classes of units, and it will be suggested that a store of these two unit types is among the additional ingredients required for native control (Pawley and Syder, 1983, p. 204).

When discussing ‘lexicalized sentence stems’, Pawley and Syder make it clear that these stems often include parts which can be transformed in various ways. They also admit that there are many problems in the treatment of lexicalized sentence stems.

How is a lexicalized sentence stem defined? How do you tell it apart from non-lexicalized sequences? There is no simple operation for doing this. The problem is essentially the same as in distinguishing any morphologically complex lexical item from other sequences; the question is what is ‘lexicalization’? What makes something a lexeme? ….  An expression may be more or less a standard designation for a concept, more or less clearly analysable into morphemes, more or less fixed in form, more or less capable of being transformed without change of meaning or status as a standard usage, and the concept denoted by the expression may be familiar and culturally recognized to varying degrees. Nor is there a sharp boundary between the units termed here ‘sentence stems’ and other phraseological units of a lower order (Pawley and Syder, 1983, p. 207).


3. The Speech

With regard to Melania Trump’s speech, Selivan looks at one of the copied parts and comments on the common uses of “impress upon”, and  the ubiquity of the phrases “work hard” and “keep promise” (sic). As a clincher, Selivan says

Looking at “treat people with respect” which is supposedly copied from Michelle Obama’s “treat people with dignity and respect”, you will see that “dignity” and “respect” are two of the very highly likely collocates here.

From this carefully assembled evidence, Selivan concludes:

If Melania’s faux pas indeed constitutes plagiarism, the text of her speech was no more plagiarized than an academic paper containing “Recent research has shown that” or “The results are consistent with data obtained in…”

Apart from the sentence being very badly constructed, and the claim being a ridiculous non-sequitur, can you imagine anybody seriously saying that the use of  “Recent research has shown that” or “The results are consistent with data obtained in…” by an academic in a published paper constitutes plagiarism? Likewise, who but Selivan and his Humpty-Dumpty use of “chunks” could seriously offer the analogy in order to defend Melanie Trump from the accusation of plagiarism?

Here’s an extract from the recent speech:

M Trump: Because we want our children in this nation to know that the only limit to your achievements is the strength of your dreams and your willingness to work for them.

And here’s an extract from the 2008 speech:

M. Obama: Because we want our children — and all children in this nation — to know that the only limit to the height of your achievements is the reach of your dreams and your willingness to work for them.

To attempt to explain the “similarities” between the two texts by appealing to “recurring sequences” is an indication of how far a little knowledge can lead one astray.


Pawley, A., & Syder, F.H. (1983) Two puzzles for linguistic theory: nativelike selection and nativelike fluency in Richards, J.C. & Schmidt, R.W. (eds) Language and Communication, London; New York: Longman, pp 191 – 225. *

*As Selivan usefully points out, this article is available online at


2 thoughts on “Selivan explains Trump speech similarities. No pigs seen flying

  1. I notice that Scott Thornbury left a comment on Selivan’s blog saying “Nice try”. Well it isn’t a nice try, as the rest of Scott’s text makes clear. It’s an absurd argument.


Leave a Reply

Fill in your details below or click an icon to log in: Logo

You are commenting using your account. Log Out /  Change )

Google photo

You are commenting using your Google account. Log Out /  Change )

Twitter picture

You are commenting using your Twitter account. Log Out /  Change )

Facebook photo

You are commenting using your Facebook account. Log Out /  Change )

Connecting to %s