Chapter 2: Language, Power, and Privilege

2.6 Linguistic Law Enforcement

In many cultures there’s a general sense that it’s rude to criticize or call attention to various kinds of social difference. In Canada, most kids learn in school that it’s impolite to stare at a person who has a visible disability, to make jokes about fat bodies, or to comment on someone’s gender-nonconforming appearance. Or at least, we learn not to express these opinions in public.

In contrast, it’s not only socially acceptable but even expected and encouraged to criticize language use that deviates from the privileged standard, calling it improper, ungrammatical, or worse. In this unit we’ll look at some of the domains where prescriptive standards of grammar get wielded like law enforcement, to keep social order.

Policing Voices

We saw in the previous unit that people who object to using they/them pronouns for non-binary people often phrase their objections not in terms of gender norms but terms of grammar, insisting that they can’t possibly be singular because that would be ungrammatical! Bradley’s (2019) work has shown that people with prescriptive views of grammar also tend to have conservative views about the gender binary — in other words, it’s not just about grammar.

Another way that people police language use to enforce gender norms is by criticizing women’s voices. When I was young, the older generation complained about uptalk? When your pitch rises? At the end of a sentence? Beginning sometime in the 2010s, the moral panic started to center on vocal fry. Chapter 3 will give us a chance to explore more about how humans make speech sounds in the vocal tract. For now, you should know that vocal fry is a way of producing speech with very low frequency vibrations of the vocal folds, so that it sounds creaky. Creak is actually one of the technical linguistic terms for this voice quality, and creak is a systematic part of the phonetics, phonology, and prosody of many spoken languages around the world (Davidson 2020).

In addition to the jobs the vocal fry does in the grammar, it also provides social cues that listeners interpret. Davidson’s (2020) review article mentions studies that found that speakers who use vocal fry are perceived as more bored, more relaxed, less intelligent and less confident, among other attributes. But even though men and women speaking English are about equally likely to creak, for some reason listeners, or at least listeners older than 40, find it wildly more irritating when women do it. Ira Glass, host of the podcast This American Life and frequent vocal fryer himself, reports that he’s received dozens of emails complaining about his female colleagues’ vocal fry, “some of the angriest emails we ever get. They call these women’s voices unbearable, excruciating, annoyingly adolescent, beyond annoying,” (Glass, 2015) but no emails complaining about his voice or those of his male colleagues. Confirming Glass’s anecdotal report, Anderson et al.[1] (2014) found that, “The negative perceptions of vocal fry are stronger for female voices relative to male voices” and they recommend that “young American females should avoid using vocal fry speech in order to maximize labor market opportunities.” Does that sound familiar? Just like the résumé study we learned about in the previous unit, this is another instance of job candidates being judged not for their qualifications and experience, but for the social cues being indexed by their voice. It’s not too likely that the pitch of your speaking voice is related to your job performance, so rather than telling job candidates to change their name or change how they use language to conform to the biases of the hiring manager, how about we train hiring committees to overcome these biases?

Policing Accents

Besides voice, another part of language use that is subject to linguistic law enforcement is accent. Everybody has an accent, but we tend to notice only the accents that are different from our own. In an earlier unit, we learned about the common belief that a standardized variety is the best or most correct way of using language. That logic extends to accents as well: a non-standard accent is often stigmatized. The accent itself is neither bad nor good, but the stigma means that people have negative attitudes and expectations about it. Where English is the majority language, people who learned English later in life often encounter that stigma. And there are also L1 varieties whose speakers experience stigma, such as Black English, the varieties spoken in the southeastern United States, and Newfoundland English.

Chapters 11 and 12 deal with how children and adults learn language in much more detail. Here, we’ll use the term first language or L1 to refer to the language(s) that you learned from birth from the people around you, and L2 for any language you learned after you already had an L1, even if it’s actually your third or fourth language.

Why do L2 users have different accents from L1 users? The short answer is that, when you learn an L2, your mental grammar for that L2 is influenced by the experience you have in your L1. (The longer answer comes in a later chapter!) So your accent in your L2 is shaped by the phonology of your L1. What this means is that if your L1 is English and you learn Japanese as an L2, your accent in Japanese is likely to be different from that of your classmate whose L1 is Korean.

For people whose accents are different from the mainstream, there can be many negative consequences. You’re less likely to get a job interview (Oreopoulos, 2011), and your boss might not recognize your skills (Russo et al., 2017). It’s harder to find a landlord who’s willing to rent you an apartment (Purnell et al., 1999; Hogan & Berry, 2011). If you have to go to court, what you say won’t be taken as seriously (Grant, 2019), and the court reporter is likelier to make mistakes in transcribing your testimony (Jones et al., 2019). Kids whose accents aren’t mainstream are disproportionately labelled with learning disabilities and streamed out of academic classrooms into special ed (Adjei, 2018; Kooc & Kiru, 2018). And probably Alexa, Siri, and Google won’t understand your requests (Koenecke et al., 2020)!

Why do these things happen? Well, in the case of Alexa, it’s because the training data doesn’t include enough variation in dialects and accents. But the rest of these situations arise from people’s expectations, and their expectations come from their experiences and their attitudes. Two linguists at the University of British Columbia conducted a matched-guise study with UBC students as listeners (Babel & Russell, 2015). They recorded the voices of several people who had grown up in Canada and had English as their L1. When they played these recordings to the listeners, they presented them either as audio-only, with a picture of the face of a white Canadian person, or with a picture of a Chinese Canadian person. For any given voice, the listeners rated the talker as having a stronger accent when they saw a Chinese Canadian face than when they saw a white Canadian face, and they were also less accurate at writing down the sentences the talker said. Apparently the faces influenced how well the listeners understood the talkers.

The researchers interpret their results as a mismatch of expectations. In Richmond, BC, where they conducted their study, more than 40% of the population speaks either Cantonese or Mandarin. If you live in Richmond, you have a greater chance of encountering L1 Chinese speakers in your daily life than L1 English speakers. So when you see a face that appears Chinese, you have an expectation, based on your daily experience, that that person’s English is going to be Chinese-accented. If the person’s accent turns out to be that of an L1 English speaker, the mismatch with your expectations makes it harder to understand what they say.

So we’ve seen that people’s expectations, their experiences and their attitudes can lead to stigma for language users with accents that are different from the mainstream. And that stigma can have serious, real-life consequences on people’s employment and housing and education. In addition to the consequences for the person producing an unfamiliar accent, there can also be consequences for the person trying to understand an unfamiliar accent. Those consequences can be pretty serious if you’re finding it difficult to understand the person giving you medical advice (Lambert et al., 2010), or teaching you differential equations (Ramjattan, 2020; Rubin, 1992). Accent “neutralization” is big business and L2 English speakers experience a lot of pressure to “reduce” their accents (Aneesh, 2015). As we’ll see in more detail in Chapter 12, it’s hard to change your accent after childhood, because your L2 grammar is shaped by your L1 experience. And your accent is part of who you are — it’s part of your story and your community. As linguists, let’s resist the narrative that pressures everyone to conform to some arbitrary standard accent. Luckily enough, psycholinguistic research shows us that it’s much easier to change your comprehension of unfamiliar accents than it is to change your L2 production.

Just as our experience and our expectations can lead to stigma, our experience also influences our perception. The more experience we have paying attention to someone, the better we understand them: this is called perceptual adaptation. Perceptual adaptation was first shown for a single talker: the longer people listened to an unfamiliar talker, the more they understood of what the talker said (Nygaard, 1994). Extensions of that research have also shown that experience listening to several speakers with a particular accent makes it easier to understand a new speaker with that same accent (Bradlow & Bent, 2008). And it turns out that listening to a variety of unfamiliar accents then makes it easier to understand a new talker with a completely different accent (Baese-Berk et al., 2013). In short, the more experience we have paying attention to someone, the more familiarity we have with the way they produce language, and the more familiarity we have, the better we’ll understand what they’re saying.

So if you want to better understand someone whose accent is different from yours, the best way to accomplish that is to pay attention to them for longer. Likewise, if someone thinks your accent is hard to understand, you can just tell them to pay attention!


[self-test questions coming soon]


References

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Anderson, R. C., Klofstad, C. A., Mayew, W. J., & Venkatachalam, M. (2014). Vocal Fry May Undermine the Success of Young Women in the Labor Market. PLOS ONE, 9(5), e97506.

Aneesh, A. (2015). Neutral accent: How language, labor, and life become global. Duke University Press.

Babel, M., & Russell, J. (2015). Expectations and speech intelligibility. The Journal of the Acoustical Society of America, 137(April), 2823–2833.

Baese-Berk, M. M., Bradlow, A. R., & Wright, B. A. (2013). Accent-independent adaptation to foreign accented speech. The Journal of the Acoustical Society of America, 133(3), EL174–EL180.

Bradley, E. D. (2019). Personality, prescriptivism, and pronouns. English Today, 1–12.

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Cooc, N., & Kiru, E. W. (2018). Disproportionality in Special Education: A Synthesis of International Research and Trends. The Journal of Special Education, 52(3), 163–173.

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Gillon, C., & Figueroa, M. (Hosts.) (2017). Uppity Women [Audio Podcast Episode]. In The Vocal Fries. 

Glass, I. (Host). (2015). Freedom Fries | If You Don’t Have Anything Nice to Say, SAY IT IN ALL CAPS [Audio podcast episode.] In This American Life. WBEZ Chicago. 

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Lambert, B. L., Dickey, L. W., Fisher, W. M., Gibbons, R. D., Lin, S.-J., Luce, P. A., McLennan, C. T., Senders, J. W., & Yu, C. T. (2010). Listen carefully: The risk of error in spoken medication orders. Social Science & Medicine, 70(10), 1599–1608.

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Ramjattan, V. A. (2020). Engineered accents: International teaching assistants and their microaggression learning in engineering departments. Teaching in Higher Education, 1–16.

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  1. No relation to the Anderson of this textbook!

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Essentials of Linguistics, 2nd edition by Catherine Anderson; Bronwyn Bjorkman; Derek Denis; Julianne Doner; Margaret Grant; Nathan Sanders; and Ai Taniguchi is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License, except where otherwise noted.

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