Big tobacco focuses on the facts to hide the truth: an algorithmic exploration of courtroom tropes and taboos
Risi S, Proctor RN. Big tobacco focuses on the facts to hide the truth: an algorithmic exploration of courtroom tropes and taboos. Tobacco Control 2020;29:e41-e49.
The language used by attorneys in tobacco litigation reveals key elements of the strategies deployed by cigarette makers and their courtroom opponents. According to industry lawyers, for example, smokers ‘passed away’ but were never ‘killed’; they always had the ‘ability to quit’ but were not ‘addicted’. Jurors, tobacco attorneys claim, should focus on the individual ‘facts’ of the case but not on the larger ‘truth’ about the industry. Language is, per Bolinger, ‘a loaded weapon,’ which means that words are not innocent conveyers of meaning. There is a subtle micropolitics in human speech, expressed in the kinds of words chosen by one side or another to deploy or to avoid.
To explore this divergent use of words and phrases, we analysed closing arguments in 159 Engle progeny trials from 2008 through 2016. Using methods from corpus linguistics, we constructed tables of ‘tropes’ (frequent terms that one side uses disproportionately) and ‘taboos’ (rare terms that one side avoids scrupulously), identifying heretofore hidden rhetorical strategies of the industry while also casting light on strategies used by plaintiffs.While cigarette makers use words or phrases that tend to focus agency on the individual smoker, attorneys working for the plaintiffs (ie, injured smokers) tend to use words that refocus agency onto the industry.
To identify terms that are distinctive for plaintiffs or defendants, we used corpus comparison methods that, while originally developed in computational linguistics, have recently become popular in the field of digital humanities. Conducting a ‘distant’, quantitative reading of a corpus of texts can be used for many different purposes. Connelly, for example, has used statistical methods to identify patterns of document destruction in State Department communications, while Underwood has used ‘distant reading’ to explore how time elapses in novels and how literary prestige leaves linguistic traces.
Scholars have shown how cigarette makers use rhetorics of freedom, choice and personal responsibility to blame smokers for their injuries. A broad scholarly literature also details how cigarette makers falsely claim that smoking’s harm and addictiveness have long been ‘common knowledge’. Computational methods offer an important complement to this literature, allowing us to show, for example, that it is family members—the husband who warned his wife about smoking, the daughter who asked her father to give up cigarettes—who put the common in the ‘common knowledge’ defence. Another strength of these new methods is that they allow us to investigate what is not said: the verbal taboos that only become visible by comparing large bodies of defence rhetoric against arguments deployed by plaintiffs. Tobacco defence teams will not talk about the companies’ ‘customers’, for example, but rather only about ‘smokers.’ They may acknowledge that someone has ‘passed away’ but will never use the word ‘killed’. Computational techniques allow detection of broad, sometimes subtle, patterns of language that might otherwise escape notice—like divergent usage of pronouns—patterns that help us better understand the industry’s courtroom strategy.