Word of the Week: floccinaucinihilipilificationism

ML learned a new word upon reading the newspaper: floccinaucinihilipilificationism. According to the New York Times now, the late Senator Patrick Moynihan prided himself on coining the 32-letter mouthful, by which he meant “the futility of making estimates on the accuracy of public data.”

Some brief history:

Sometime around 1981, Moynihan invented the word by adding “ism” to an older, 29-letter English word, floccinaucinihilipilification – defined as “the action or habit as estimating as worthless” in a 1971 edition of the Oxford English Dictionary:

from the Oxford English Dictionary (1971)

You can find an open discussion of the roots of floccinaucinihilipilificationism on Wiktionary, which includes hard-to-decipher, clickable audiofiles – just in case you want to try saying the word out loud. Moynihan used the word in the title of his 1981 New Yorker review of a book by economist John Kenneth Galbraith.

More accessible is a somewhat dull, but worth-a-listen clip of the Moynihan discussing the word’s history in a debate on the budget deficit in July, 1999, on C-SPAN. From the Congressional Record:

“Floccinaucinihilipilification is now the second longest word in the Oxford Dictionary. It is from a debate in the House of Commons in the 18th century meaning the futility of budgets. They never come out straight…I added “ism” to refer to the institutional nature of this, so it became floccinaucinihilipilificationism. It is no joke. One never gets it right. It is not because one cannot, one does not try…

It seems to me the term, which was intended for the realm of economics, and projections in that, might bear also on the intricacies of vast amounts of data in science and health, data mining, and understanding the limitations of medical studies and related analyses. But I’m extrapolating here, for sure.

As I read the late Senator’s words, about his word, it seems maybe he’s suggesting that we could “get it right,” i.e. sort out data in a way that has real value, if we try harder to do so.

But who knows?

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