This is Mark Twain’s humorous advice for jargon-prone writers who fail to “employ a simple and straightforward style.”* In case you’re wondering, “surplusage” means “unnecessary or irrelevant language.” This obscure term is mainly used by the legal profession. Isn’t that ironic?
Here are some promising developments for citizens in English-speaking countries who suffer from surplusage at the hands of their lawyer-riddled governments:
- The Plain Language bill now coming to a final vote by the New Zealand Parliament may make simple-English training mandatory for their public servants.**
- Twelve years ago this month, the USA enacted the Plain Writing Act of 2010 establishing that Government documents issued to the public must be written clearly.
- A recent Labradorian-commissioned comparative study of “ordinary” versus “plain” English showed significant improvements in reading speed, understanding, retention and appreciation.**
- The 2022 Ig Nobel Prize for Literature was awarded to the authors (Martinez, et al) of Poor writing, not specialized concepts, drives processing difficulty in legal language (not at all ignoble—lawyers should be held accountable for incomprehensible contracts).
“Contracts contain “startlingly” high proportions of difficult-to-process (“complex psycholinguistic) features including low frequency jargon, centre-embedded clauses, passive voice structures, and non-standard capitalisation.”
Eric Martinez and Edward Gibson at the Massachusetts Institute of Technology (MIT) and Francis Mollica at the University of Edinburgh
Poor writing is not confined to government or legal communications. Those of us who work in the scientific arena must work mightily to decipher reports intended to provide “accessibly erudite progressive rigor” (the first phrase that came up for me at this Academic B.S. Generator). I found some hope from these studies:
- A randomized, controlled study on thousands of subjects “indicating the detrimental effects of providing too many details on statistical concepts.”***
- A call**** by statistician Karen Grace-Martin to work on reducing four major sources of confusion for terminology rising to a level of “absurdity”:
- “Single terms with multiple meanings,” e.g., alpha and beta used for linear-model coefficients as well as to symbolize risk versus power.
- “Terms with colloquial meanings in English and technical definitions in statistics,” e.g., “error” (supposedly early statisticians got so much criticism from managers about too many errors that they started calling these “residuals).
- “Similar terms with nuanced meanings,” e.g., General Linear Model and Generalized Linear Model (being an engineer-only, I have trouble with this distinction).
- “Multiple terms with one basic meaning,” e.g., a long list of synonyms for “mixed models”.
Down with bureaucratic language, legalese and technical jargon!
*See rules #14 #18 (speaking plainly) in Fenimore Cooper’s Literary Offenses
**The Effectiveness of Plain Language Proven by Data, 2020
***Kerwer, et al, How to Put It Plainly? , 2021.