It’s Nobel Prize season! Each morning last week brought new accolades for a great and important human endeavor: in physiology and medicine; in chemistry; in physics; in literature; and in peace (the prize for economics will be announced sometime after I’ve written this page, but before it’s been published).
A phrase caught my ear last Monday when the first prize was being reported in the press. It’s worth a short post. Take a quick look at this paragraph (it’s easier to hear the flaw when it’s read aloud, but we’ll make do with text on the page):
British researcher John Gurdon and Shinya Yamanaka
of Japan have won this year’s Nobel Prize in medicine or
physiology. They won for the discovery that mature cells
can be reprogrammed into stem cells.
I broke that first line where I did to help make the point of how faulty parallelism can throw a reader off. How many of you reading this thought at first glance that the phrase “British researcher” was meant to refer to both Gurdon and Yamanaka? The next two words (“of Japan”) might then have made you pause for a second to re-parse the words you’d just read, or maybe even to re-read the entire sentence.
On the other hand — and here’s one of the subtle things about parallelism problems — you might have had no problem with this wording at all. Or at least think that you didn’t. Solid data would be hard to come by, but from past observations I’d guess that at least half of listeners (readers) would sense something wrong with that line immediately; for this particular construction, that figure is probably closer to 80%, maybe higher. But some won’t notice it at all. The odd thing is that while most people will see (or hear) the flaw if you ask them about it, in practice they might just stumble over it briefly, then quickly and mentally correct the intended meaning, then move along.
This kind of flaw in writing is very common. It’s not often fatal to the writing. In fact, I haven’t yet referred to it as an “error,” but only as “faulty parallelism” and with good reason. (You might find it referred to by other names, but “faulty parallelism” is the term I prefer.)
Writers get a lot of leeway with the language. Although there are plenty of traditions and generally accepted ‘rules’ that they follow most of the time, there are circumstances in which just about any rule can be broken. The parallelism of a structure is one of those, although most writers will still stick to certain predictable rhythmic and stylistic (and grammatical) patterns. They’re simply easier for readers to follow.
When writing anything expository — non-fiction, academic essays, and so on — it’s definitely best to stick more closely to the rules, and in most cases not to dodge them at all. You want to keep your structures as strictly parallel as possible. The goal of this type of writing is to communicate clearly, to transmit information as effectively as possible. With that idea foremost, just about the last thing you’d want to do is bring the reader up short and have to spend extra time re-reading what they’ve read a moment before (or spending extra time thinking about what they’ve just heard).
You might think something like this isn’t all that big a deal, but in high quality writing it really matters. You might also think that the example I used above (from NPR, by the way) isn’t a particularly good one, in need of no correction. Based on indirect evidence, I’ll strongly argue the opposite: although this faulty (or “weakly”) parallel structure was repeated several times during the morning news updates, by later in the day it had been corrected. As additional prizes were announced during the week, a more strict parallel structure was chosen. This was undoubtedly deliberate, after the first structure had grated on a few editorial ears.
Parallelism continues to be one of my favorite writing topics, as an instructor, as an editor, and even as a writer. I’ve posted on it before here, and I’ll almost certainly post on it again. There are so many variations to it, with new (and sometimes very complex) examples appearing all the time. There’s always more to learn about parallelism, and it never seems to get old.