In the name of the law, stop the disrespect!

The killing of George Floyd in Minneapolis USA in May 2020 raised questions about the impartiality of police officers when dealing with the public and particularly those from black and ethnic minorities.  Six years earlier, in 2014, a team of researchers from Stanford University investigated exactly this issue by using footage from police body-worn cameras to analyse the language they used during routine traffic stops in the multiethnic city of Oakland in California. 

The researchers transcribed footage from 981 traffic stops of both black and white drivers, which were conducted by 245 different officers during a period of one month. Participants in the study were given transcripts of these interactions without knowing the race, age or sex of the drivers. They were then asked to rate the respect shown by the officers through placing their language on a gradient, showing how respectful, polite, friendly and formal they were. The research team used a model based on linguistic theories of respect where respectful language includes apologising, being grateful, expressing concern for the other person and softening commands to reduce confrontation. 

The results demonstrate that, although officers used the same levels of formality for both black and white drivers, they were rated as significantly less respectful, polite or friendly to black drivers than they were to whites.  Even after controlling for the severity of the traffic offence, the length and outcome of the stop and the race of the officers themselves, interactions with white drivers were consistently more respectful. In fact, 57% of white drivers were more likely to hear an officer say one of the most respectful phrases (e.g. “sir”, “thank you”) in the transcripts whereas black drivers were 61% more likely to hear one of the least respectful (e.g. “hands on the wheel”, or use of first name). 

The researchers conclude that the racial disparities in their study are clear, however the causes of them are not.  They write that these disparities could have far-reaching effects as personal interactions with the police build a community’s opinion about them and ultimately lead to a relationship of trust or distrust. They suggest that future research could expand body camera footage beyond just text to audio features such as intonation and video features such as facial expression, to try and investigate how interactions progress and sometimes break down.  This could be invaluable in informing police officer training and to establish better relationships with the communities they serve. 

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Voigt, Rob, Nicholas Camp, Vinodkumar Prabhakaran, William Hamilton, Rebecca Hetey, Camilla Griffiths, David Jurgens, Dan Jurafsky, and Jennifer Eberhardt. 2017. Language from police body camera footage shows racial disparities in officer respect. PNAS 114 (25): 6521-6526.

https://www.pnas.org/content/114/25/6521

This summary was written by Gemma Stoyle

 

#Covid-19

The past year has affected all of us in one way or another but have you ever thought about what effect it may have had on our language?  Philipp Wicke and Mariana Bolognesi did just that in their study of thousands of tweets posted during March and April 2020.

Due to social distancing measures, people were quick to use social media platforms like Twitter to connect with others and express their feelings, sending around 16,000 tweets an hour with hashtags like #coronavirus, #Covid-19 and #Covid. The researchers wanted to explore this online discourse and were particularly interested in how the pandemic was discussed using the metaphor of war. Discourse about disease has often been found to use this metaphor and cancer patients frequently complain that they are described as being in a 'battle' with the illness, which they find negative and unhelpful. With this in mind, Wicke and Bolognesi decided to also explore other figurative ways in which Covid was being described.

They collected 25,000 tweets a day that contained at least one of eight covid-related hashtags. Retweets were not included nor were more than one tweet per user in order to gain a balanced view of language use. 5.32% of the collected tweets mentioned war, the most common words being 'fight' (29.76% of these mentions) and 'war' (10.08%), whilst 'combat', 'threat' and 'battle' were also prevalent. The researchers noted that this could reflect this early stage of the pandemic: it was a global emergency and urgent action was needed to confront the situation. Most of these examples referred specifically to the treatment of the virus and the 'frontline' workers dealing with its effects in hospital.

When they concentrated on other figurative ways in which Covid was being described they found it referred to in terms of a storm, a monster and a tsunami.  For example, the idea of the virus as a storm arose in 1.49% of the tweets and contained words like 'thunderstorm', 'rain' and 'lightning'; 1.13% of the tweets referred to a tsunami, using words like 'earthquake', 'disaster' and 'tide' and references to a monster occurred in 0.68% of the tweets with 'freak', 'demon' and 'devil' being prime examples. These negative images mainly referred to the onset and spread of the virus. It is clear, however, that the war metaphor was used significantly more than these others.

Wicke and Bolognesi conclude that their results confirm previous findings that the war metaphor is common in public discourse of disease; however, they found that it was used very particularly during the first weeks of the pandemic to refer to the initial medical response to it. They also suggest that all of these metaphors are negative and unhelpful and propose the construction of a 'Metaphor Menu', previously suggested with regards to cancer, to give the public more positive and desirable ways to talk about Covid 19 as the pandemic evolves and changes.

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Wicke P., M. M. Bolognesi (2020) Framing COVID-19: How we conceptualize and discuss the pandemic on Twitter. PLoS ONE 15(9): e0240010. 

https://doi.org/10.1371/journal.pone.0240010

This summary was written by Gemma Stoyle

The shifting tipping point - one metaphor, many uses

To understand what a metaphor is, let’s start by considering a real world example. For tipping point, we might imagine an object that should be kept upright, such as a vase of flowers, at risk of falling when it loses its centre of gravity. As the tipping point is not the vase’s natural state, we assume something has caused the unbalance e.g. a curious cat, or an earthquake. We also realise that there will be consequences when this tipping point is reached, and we expect these will be negative. The glass is likely to smash, causing danger to bare feet, and destroying the vase. The contents will also spill onto the floor, possibly spreading water and causing further damage, or possibly partly retrievable if some of the flowers can be rescued. But we recognise that reaching the tipping point is very unlikely to have many positive outcomes, as it takes us from our pretty vase of flowers, to an undesirable mess on the floor.

The job of a metaphor is to map the knowledge we have from these real-world examples, onto something else. But whereas the source domain of a metaphor relates to concrete entities (such as the unlucky vase), the target domain will be a more abstract and complex phenomenon. Therefore, how the metaphor is used - the linguistic and discursive context - will help to shape how we conceptualise this target.

From the 1960s onwards, tipping point was regularly mapped onto moments of social change, most popularly in the early 2000s to describe the sudden spread of a new trend or idea in society. Conventionally, tipping point came to be used as an everyday expression meaning a time of important, often uncontrollable, things happening that lead to change. It was most often applied to an individual, reaching a personal tipping point and joining a wider group or process in society. Notably, the more negative interpretations were largely removed, and the metaphor was seen as more exciting than threatening. Over time, the metaphorical mapping had therefore become somewhat ‘bleached’ of its source domain.

But from 2004 scientists began to use this metaphor in relation to the world’s climate, and it is now common to hear and read about ecological tipping points in the media. Van der Hel, Hellsten & Steen (2018) examined 326 articles from major world newspapers, and 301 scientific articles, to see how this metaphor developed and was used from 2005-2014. They looked for both the discursive context of the metaphor (Who is using the phrase? What is it being used to refer to?) and the linguistic characteristics of its use (How is the phrase combined with different parts of speech and punctuation? Is the use of the phrase deliberately metaphorical?) From this study they tracked the changing use and meanings of tipping point in both the media and science.

The metaphor was first used by scientists as an attempt to explain to the media their complex research into abrupt changes in the climate system. Use of the phrase at this time drew attention to its metaphorical meaning, rather than the conventional one, by also expressing related ideas of falling, danger and irreversibility. By making explicit references to the source domain in this way, the metaphorical meaning is more ‘deliberate’, and actively encourages us to reflect more on the concrete meaning of the expression. Therefore the metaphor highlighted the serious and threatening nature of a tipping point and, by extension, the catastrophic issue of climate change.

Until this time tipping point in climate change news articles had mainly been used in the conventional sense, to refer to changes in individual social attitudes towards the environment. But from 2005-2007 the phrase began to appear more frequently in inverted commas, to note its increasing, and unfamiliar, use by scientists. The phrase also began to be used in reference to humanity as a whole, in contrast to the previous convention of usually referring to an individual in society. This use of punctuation and the new collocations again serve to focus attention on the metaphorical status of the phrase. In doing so, a reader may be encouraged to draw deeper on their source domain knowledge, and reconsider the metaphor’s meaning.

Within the scientific community, use of the metaphor continued to increase from 2008. But whereas it may have begun as a rhetorical device, it subsequently became a mainstream scientific concept, and a theoretical tool. The imagery of a tipping point largely replaced some earlier metaphors (e.g. thresholds), and studies explored what the causes and outcomes of different potential tipping points might mean in various climate contexts. This suggests an inspirational role for the metaphor, through capturing the imagination of scientists, and opening new directions for studies.In contrast, the media used the metaphor less after 2007, but it re-emerged from 2011 in news reports from political speeches at international climate conferences. In these reports, it was increasingly tied to specific locations (e.g. the Amazon) and events, and was often still expressed using inverted commas. However the phrase also began to be used for other, non-climate related changes, such as sudden policy shifts. This suggests that the tipping point metaphor in the media had become more flexible, again incorporating the conventional expression of a drastic change.

This study shows that in science and the media, a metaphor can help explain complex ideas, and encourage new ways of thinking about a phenomenon. It also demonstrates their versatility: tracing how a metaphor that had become an everyday expression was mapped onto a new target domain, leading to a restructured understanding. By examining the linguistic and discursive contexts of tipping point, Van der Hel, Hellsten & Steen (2018) highlight the numerous and changing roles that metaphors can play, and how they can help scientists and journalists in public debates on important topics.

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van der Hel, S., Hellsten, I. and Steen, G., 2018. Tipping points and climate change: Metaphor between science and the media. Environmental Communication, 12(5), pp.605-620.

This summary was written by Sarah Kirk-Browne

Why we use emoji: Written gestures in online writing

When we talk to each other, we don’t just rely on words. Emotion is embodied, and our expressions, our body language, our tone of voice are all used to convey our feelings and affect how our words are interpreted. But for online written communication, we can’t rely on these details. As discussed in the previous post, punctuation can be helpful to represent tone of voice, but often there is still something missing. In the fifth chapter of her pop linguistics book Because Internet, Gretchen McCulloch explores how emoji became popular as a way of replicating gestures in online communication.

Emoji cannot be considered a language: there is a limit to what can be expressed, and most languages can handle meta-level vocabulary about language, which emoji cannot. But they clearly do something. However, many popular emoji use hand and facial gestures, which, McCulloch says, inspired her to begin treating them as gesture.

There are two types of gesture which emoji can represent: the first are called emblems. These are nameable gestures, and have precise forms and stable meanings, and are often culturally specific, such as winking, giving a thumbs up, and obscene hand gestures. Many of these have directly equivalent emoji, for example, fingers crossed 🤞, rolling eyes 🙄, or a peace sign ✌️. Some emoji are more metaphorical, such as the eggplant emoji as a phallic symbol, but, with knowledge of internet norms, they still have fixed meanings. Emoji are not the only way to express emblems online: reaction gifs and images are also used to express specific moods or actions, many of which we can refer to by name (for example, most internet-literate people will know what I mean by Michael Jackson Eating Popcorn.gif).

The second type of gesture with corresponding emoji are illustrative or co-speech gestures. These gestures are dependent on surrounding speech, and highlight or reinforce the topic. You often make these without realising, and at times when they make little sense, such as waving your hands around when on the phone and your conversational partner can’t see you. These gestures don’t have specific names but can be described. Think of the way you move you your hands when giving somebody directions or describing the size of something. These gestures are also represented in emoji. The example McCulloch uses is the range of emojis possible in a ‘Happy Birthday’ message, perhaps a combination of the following 🎂🍰🎁🎊🎉🎈🥳. In these contexts, the order doesn’t matter, these emoji aren’t telling a story, they are adding to the current one. Illustrative emoji are also more likely to be taken at face value, and don’t necessarily require knowledge of internet culture that, for example the eggplant emoji might require. If emblems are for the benefit of the listener, then illustrative gesture are for the benefit of the speaker, used to help them get their message across.

McCulloch also examines common sequences of emoji, finding that, unlike words, emoji are often repeated, both as a straightforward sequence of the same emoji multiple times (the most common being 😂), and sequences of different emoji that are linked thematically, such as the series of birthday related emoji above, or a series of love emoji such as 💕💓😍💗🥰💖. This is another reason why emoji can be considered gesture: repetition does not generally occur in our words, but does occur in hand gestures.

Repetitive gestures are known as beat gestures: they are rhythmic, and if you stutter while you speak, your gestures also do the same. Emoji also do this: we type 👍👍👍 to represent a sustained or repeated thumbs up gesture in real life. We can even repeat emoji which don’t have a literal gesture attached, because, as a whole, emoji can be repeated. The ‘clap back’ is a common beat gesture among African American women, and this is often represented through emoji as a form of emphasis: 👏 WHAT 👏 ARE 👏 YOU 👏 DOING 👏

Emoji serve an important purpose in informal written communication, filling in for expression and gesture which otherwise are hard to convey. For more from McCulloch on the topic of emoji and gesture, Episode 34 of her podcast Lingthusiasm with Lauren Gawne, discusses the content in this chapter, and provides several further links on the topic of emoji and gesture.

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McCulloch, Gretchen. 2019. Because Internet: Understanding the New Rules of Language. New York: Riverhead Books.

This summary was written by Rhona Graham

“ok” “ok.” and “ok!” How we use punctuation to convey tone online.

As a result of technology, many of our casual, everyday conversations now take place online, in written form. This has in turn changed how we write informally, which is the topic of Gretchen McCulloch’s 2019 book Because Internet. This book focuses on how the internet is changing language and is written for a general audience. Chapter 4 discusses how we convey our emotions through written language, and the history of these conventions. Conversational writing has caused us to find innovative ways of replicating our speech in our writing, both our words, and our tone, which McCulloch calls typographical tone of voice.

Why is it so much scarier to receive a text saying “ok.” than “ok”? In online messaging, we tend to use line or message breaks, rather than full stops, to convey the end of an utterance. Full stops are associated with falling intonation (in the same way that a question mark indicates rising intonation), which doesn’t often occur in actual speech, and many of our messages are designed to replicate speech. In some contexts (like “ok.”), implied falling intonation can be interpreted as passive-aggressive or angry, which has been noticed in the media since 2013.

Some conventions, particularly those for strong emotion, have been around a lot longer than the internet. For example, YOU ARE PROBABLY SHOUTING THIS SENTENCE IN YOUR HEAD, because for at least a century, capital letters have been a way of expressing strong emotion. Another is repeating letters, particularly in emotive words, such as “yayyy” or “nooo”. This also predates the internet, with the earliest example coming from 1848, and gaining popularity throughout the 20^th century in sounds such as “ahhh” or “hmmm”. In a 2011 study of Twitter, sentiment words were the most common to be lengthened in this way: examples being “ugh” “lmao” “damn” and “nice”.

McCulloch also discusses the ways in which we soften a message, to come across as friendly or approachable. The exclamation point has progressed from signifying ‘excitement’ to being associated with ‘warmth’ and ‘sincerity’, which is why most younger people would prefer to receive a text saying “ok!” than “ok”. ‘lol’, rather than meaning that you are actually laughing out loud, has taken on the function of polite laughter, and smiley faces (i.e., emoticons/ emojis) have the same impact, tempering the tone of a message, making it appear friendlier.

One area of interest is how we indicate that we are being sarcastic without outright saying #sarcasm (which, after all, would defeat the point of being sarcastic). In speech, sarcasm is conveyed through tone of voice and facial expressions: in written text, we need a way to signify these additional meanings, without explicitly stating that we’re making a joke. While many options have been officially suggested, these don’t tend to stick. One that has is the sarcasm tilde (~), which McCulloch argues derives from the mid-2000s days of MySpace ‘sparkle punctuation’, where users used punctuation marks for aesthetic purposes. Now, using ~ in a message indicates that it isn’t serious, which we then, based on context, can interpret as irony or sarcasm: McCulloch calls this ‘sparkle sarcasm’. The sarcasm tilde also can also be seen as a literal representation of the way in which your tone rises and falls when being sarcastic.

A Tumblr post from 2016

Ironic emphasis is also an interesting area to examine. The Tumblr post above, a screenshot from 2016, shows just some of the ways in which emphasis was conveyed. Unexpected capital letters, spacing out letters, using hashtags or ^TM are all used by the author to add emphasis.

However, it is interesting to note that the rest of this sentence is devoid of punctuation: there is no full stop, ‘tumblr’ is uncapitalized, and neither is ‘i’ at the beginning of the sentence. McCulloch calls this lack of punctuation ‘minimalist typography’ and discusses how this is used to convey tone of voice, particularly in the current era of smartphones. With predictive text, writing a sentence without capitalising the first word, or even writing ‘i’ requires extra effort: even while writing this post, my word processor automatically capitalises a single i, and I have to go back to retype it. This extra effort conveys meaning to the reader through absence: the capital letters in an otherwise uncapitalized sentence indicates that the author has used these typographic forms for some specific reason. McCulloch describes minimalist punctuation as “an open canvas, inviting you to fill in the gaps”.

These are just some of the ways in which we reflect our tone in typed speech, from caps lock, to passive aggressive punctuation. Given the developments that have occurred in the last twenty years alone, it is highly likely that these conventions will continue to change, and generations to come will develop their own conventions for irony, passive aggression, and humour. Because Internet is a fascinating snapshot of how language is being used on the internet currently, and I do recommend it as an enjoyable and interesting read.

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McCulloch, Gretchen. 2019. Because Internet: Understanding the New Rules of Language. New York: Riverhead Books.

This summary was written by Rhona Graham

#BlackLanguageMatters: Can linguistics change the course of justice?

The 2013 trial of George Zimmerman for the murder of unarmed Black teenager Trayvon Martin is well-known as the court case that sparked the #BlackLivesMatter movement in the USA. 17-year-old Martin was shot dead by Zimmerman, who claimed he was acting in self-defence and was eventually acquitted of all charges. The outcome of the trial caused outrage among the Black community over racial profiling, police brutality and inequality in the criminal justice system, and prompted the founders of #BlackLivesMatter to use the hashtag for the very first time.

It’s less well-known that the case also served as a ‘call to action’ among linguists. John Rickford and Sharese King of Stanford University studied the court proceedings closely, focusing on the testimony of one particular witness, Rachel Jeantel. A close friend of Martin, Jeantel was on the phone to him just moments before his death. As such, she represented an important ‘ear-witness’ and testified for over 6 hours in court, but her testimony was completely disregarded by the jury, who found her to be unintelligible and ‘not credible’.

What does this have to do with linguistics? Jeantel is a speaker of African American Vernacular English (AAVE), also known as African American Language (AAL): a variety of English spoken by many Black Americans. AAVE has been studied extensively by linguists, who have shown that it is a systematic and rule-governed dialect of English like any other. Nevertheless, like most ‘non-standard’ vernaculars, AAVE is often stereotyped by non-linguists as uneducated and broken. Jeantel’s speech is no exception: Rickford and King note that she was ridiculed on social media throughout the trial, labelled as ‘inarticulate’ and ‘the perfect example of urban ignorance’.

As well as being lampooned online, Jeantel’s testimony was overlooked by the jury in their decision-making. Commenting after the case, one juror said that Jeantel was ‘hard to understand’, and another reported that ‘no one mentioned Jeantel in [16+ hour] jury deliberations. Her testimony played no role whatsoever in their decision’ (Juror Maddy, as reported in Bloom 2014) despite the fact that she was on the phone to the defendant moments before the shooting took place.

In their paper, Rickford and King set out to investigate linguistic reasons for why this happened. They start by closely analysing over 15 hours of Jeantel’s recorded speech, to see how it compares to that of other AAVE speakers. They found her speech to be ‘a systematic exemplification of the grammar of AAVE’. In other words, it displays patterning in lexicon, grammar and phonology that is typical of AAVE, and also reflects the possible influence of Jeantel’s Haitian mother and Anglophone Caribbean Creole-speakers living in Miami. Given these findings, the possibility that Jeantel was not understood because her speech was incoherent – or, as one commentator described it, ‘the blather of an idiot’ – is clearly ruled out. Why, then, did the jury neither understand Jeantel nor consider her testimony to be important in their deliberations? Rickford and King look at two possibilities in their paper: the influence of social bias and the issue of dialect unfamiliarity.

It is likely that social bias had an effect on jurors’ ability to understand Jeantel as well as their assessment of her credibility. Rickford and King cite several studies that show that ‘speech perception is influenced by listeners’ stereotypes of speaker characteristics’ – in other words, if White listeners believe that a speaker is Black, their comprehension actually decreases. Importantly, the Zimmerman trial jury was primarily White, middle-aged and suburban, with no African American members.

Considering dialect unfamiliarity as a factor, Rickford and King list a number of other court cases in which vernacular language has been misheard or mistranscribed. Part of the problem, they explain, is that courtrooms do not provide interpreters for dialects, but only for ‘foreign languages’. In other words, an interpreter would be provided for a Spanish or Vietnamese-speaking defendant, for example, but not offered to a speaker of Bajan Creole or AAVE. Depending on the dialect in question, this can lead to dangerous misunderstandings: Rickford and King give the example of a police interview in which a Jamaican Creole speaker’s words, given verbatim in (a), were first transcribed as in (b).

(a) wen mi ier di bap bap, mi drap a groun an den
when I heard the bap bap [the shots], I fell to the ground and then
mi staat ron.
I started to run.
(b) When I heard the shot (bap, bap), I drop the gun, and then I run.

As this example shows, the distinction between ‘languages’ and ‘dialects of a language’ is not always clear-cut, and listeners are likely to have difficulties with comprehension if they are not familiar with the variety being spoken. In the Zimmerman case, Rickford and King show that Jeantel used several preverbal tense-aspect markers in her speech, such as stressed BIN, completive done, and habitual be. The authors point out that these features of AAVE have been mis-transcribed by non-AAVE speakers in other cases, meaning that it is very likely they were misunderstood in this case too.

Rickford and King conclude that AAVE was, in a way, ‘found guilty’ in the Zimmerman trial, since responses to Jeantel’s dialect unfairly prevented her testimony from being heard or properly understood, and undoubtedly affected the outcome of the case. In light of this, they argue that courtrooms are in serious need of expert linguistic input and dialect interpretation, and strongly urge linguists to help make courtrooms fairer places. More broadly, Rickford and King point out that language prejudice affects outcomes not only in the criminal justice system, but also in education, employment and healthcare, and call on linguists to dispel myths about speech and language in all domains of life.

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Bloom, L. (2014). Suspicion nation: The inside story of the Trayvon Martin injustice and why we continue to repeat it. Berkeley, CA: Counterpoint.

Rickford, J. R., and King, S. (2016). Language and linguistics on trial: Hearing Rachel Jeantel (and other vernacular speakers) in the courtroom and beyond. Language 92/4, 948-988.

This summary was written by Rosemary Hall

"Thanks, no problem, pleasure, don't mention it, thanks"

I once heard that how someone treats a waiter can say a lot about their character. What about the way a waiter responds? Researcher Larssyn Rüegg thinks that there may be differences in how waiters respond to their customers’ thanks, based on the kind of restaurant they are in.

While previous research has looked into how various languages may differ in this pragmatic function of the thanks response, none so far has looked into how thanks response might vary within a single language. Rüegg's research is based in part on a previous work by Klaus Schneider who typified different forms of thanks responses. An example is the welcome type which include a spoken phrase such as 'you're welcome', or even just 'welcome'. Other types include okay, anytime, no problem, pleasure, don't mention it, thanks, yeah, sure, and don't worry about it. Rüegg extends this study by asking what influences these types of response. She identifies two potential factors: socio-economic setting and the type of favor.

It is strongly supported by research that service staff tend to select a style of speech deemed appropriate to their clientele, so their speech would therefore reflect social stratification. Based on this, Rüegg decided to use a corpus of naturally occurring talk in restaurants of different price ranges to exemplify different socio-economic settings. This corpus, the Los Angeles Restaurant Corpus (LARC) contains three categories, LARC-up, LARC-mid, and LARC-low, each reflecting their price range.

The first finding from this study is as we would expect: thanks responses in LARC-up and LARC-mid were 50% more frequent than that of LARC-low. Yet, even the frequency of thanks responses in LARC-up and LARC-mid are quite low, with expressions of thanks being responded to less than 25% of the time.

The form of thanks responses also differs across the socio-economic categories. For example, the most common response types in LARC-up and LARC-mid, such as welcome and thank you, are not found in LARC-low. Furthermore, customers in the LARC-low restaurants use thanks responses that are not present in both LARC-up and LARC-mid, such as yeah, and absolutely. Interestingly, LARC-mid display the most variation in types of thanks responses.

The type of act which waiters are thanked for shows distinctive patterns as well. A non-verbal service act elicits the most thanks responses in LARC-up and LARC-mid. Such acts include clearing or setting the table, or perhaps bringing the bill. Interestingly, such acts never elicit a thanks response in LARC-low. Enquiries by the service staff about the guests' well-being do not elicit a thanks response in LARC-low either. Serving food or drinks is correlated with socio-economic setting, with customers in LARC-up giving the most thanks responses, and those in LARC-low the least. On the other hand, verbal offers of service such as Do you need more wine? Anything else? more consistently generate thanks responses across all categories.

Through this research, we can see that thanks responses in English are not very frequent on the whole. This is in contrast to some other languages. In addition, the sensitivity of thanks responses to socio-economic setting suggest that they are a subtle form of cultural encoding, with common responses in LARC-up and LARC-mid restaurants possibly signalling formality. Furthermore, thanks responses do not appear to be very standardized, with a wide range of forms being used, especially in LARC-mid and LARC-low. The fact that the type of service performed elicits differing thanks responses across the different socio-economic settings reinforces the sense that these small linguistic acts are actually a rich form of interactional management and cultural signalling.

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Rüegg, Larssyn. 2014. Thanks responses in three socio-economiuc settings: A variational pragmatics approach. Journal of Pragmatics 71: 17-30

doi. https://doi.org/10.1016/j.pragma.2014.07.005

This summary was written by Darren Hum Chong Kai 

The Power of Babble

"Ma-ma, ba-ba, da-da" - you probably associate sounds such as these with babies, in particular the babbling that babies make when they're first acquiring language. But what do these sounds do? And why do babies babble? This is a question that some recent research has addressed.

In their recent research report, Elminger, Schwade and Goldstein examined the function of babbling in infants’ language development.  They explored the idea that a caregiver’s response to their child’s vocalizations is key to the beginnings of communication and found that infants themselves may actually be in charge of this process.  By 5 months old, babies will babble and expect their adult caregiver to reply and by 9 months, they will begin to produce more speech-like noise once the adult responds to them.  Previous research has suggested that parents’ speech will match the child’s current age, changing as the child grows.  A baby’s most varied ‘pre-speech’ repertoire of sounds is between 9-10 months and this is when a parent’s speech is most sensitive to their child’s vocalizations.

The researchers focused on this age group and were interested in further investigating the relationship between the adults’ and infants’ vocalizations by closely examining adult speech in response to infant babble. They used three measures to assess the type of speech parents used to respond to babbling:  Firstly, they counted the number of different types of words that were used; secondly, they counted the average number of words in the responses and thirdly, they calculated how many of these responses were just a single word.  There were thirty mother-infant pairs who participated in the study and they were recorded in a naturalistic environment, as the child played, over two thirty minute sessions.  The researchers split the adult responses into two different categories: ‘contingent’ which were immediate, direct responses to the child’s babble and ‘non-contingent’ which did not occur within two seconds of the babbling.

Overall, the investigation showed that the mothers produced less contingent than non-contingent speech and that the contingent speech consisted of significantly shorter utterances with simpler words.  They also found that there were more single-word contingent utterances than non-contingent. So, in general, it seems that parents may simplify the whole structure of their speech in response to their child’s babble, suggesting that infant babbling really does influence the adult response. It may be that this immature, pre-speech babble is actually engineered by the child to create language learning opportunities through eliciting simplified, easy-to-learn responses from their caregiver.  In fact, it seems that infant babbling in general is indicative that learning is happening:  It has previously been found that infants more accurately remember the features of objects at which they have babbled than those that have been looked at and handled but not babbled at.  So, when an adult responds vocally to babbling, the already alert child will quickly learn the patterns of their speech. 

Overall, these results show that children learn to recognise language much more quickly when the information they need to do so is presented immediately on babbling.  During the first year of their life, infants associate their babbling with a response from their caregiver which will guide their learning and speech development.  So, unlike the Tower of Babel,  fabled to have been built to divide people linguistically, in this study the power of babble is shown to rely on infant and caregiver closely working together.

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Elmlinger S.L.; J.A. Schwade & M.H. Goldstein. 2019. The Ecology of prelinguistic vocal learning: parents simplify the structure of their speech in response to babbling. Journal of Child Language. 16:1-14.

This summary was written by Gemma Stoyle

doi: 10.1017/S0305000919000291

Accent Bias: Voices at Work

Continuing our series of posts related to the 'Accent Bias in Britain' project, in this blog post we discuss some findings from our research which investigated current attitudes to accents in Britain.

In our last blog post, we explored some of the findings of the second part of our study which investigated how the UK public evaluated 5 different accents in mock interviews. The third part of our study, detailed here, investigated whether people in positions of power such as recruiters would exhibit the same type of accent biases. 

Our study focuses on a profession that has been previously described as lacking diversity, Law. We were interested in examining whether accent bias interferes with judgements of professional skill. In other words, would a candidate with, say a Multicultural London English accent, be perceived as less professional or competent as their Received Pronunciation speaking peers? 

To investigate this question, we played the same mock interviews as described in our last blog post to 61 legal professionals.We prepared 10 short mock interview answers, varying between ‘good’ and ‘poor’ quality. Before we conducted the experiment, these answers were independently judged as 'good' or 'poor' by a group of 25 legal professionals otherwise unrelated to the project.

To create the mock interviews, we had 10 speakers (2 of each accent) record 10 good and 10 poor interview responses. This resulted in 100 recordings. The accents we tested were: Multicultural London English (MLE), Estuary English (EE), Received Pronunciation (RP), General Northern English (GNE), and Urban West Yorkshire English (UWYE). 

From the 100 recordings, our 61 legal professionals heard a random selection of 10 interview answers. They were then asked to evaluate whether they thought the answer was a 'good' answer or a 'poor' answer. They were asked to indicate this on a 10-point scale, responding to the following questions:

1. “How would you rate the overall quality of the candidate’s answer?”
2. “Does the candidate’s answer show relevant expertise and knowledge?”
3. “In your opinion, how likely is it that the candidate will succeed as a lawyer?”
4. “Is the candidate somebody that you personally would like to work with?”
5. “How likely would you be to recommend hiring this candidate?”

When we analysed our data, we identified a surprising effect. Whilst the general public displayed a great deal of accent bias in judging the competency of a job candidate, the lawyers did not follow this pattern. In fact, the professions did not show significant preferences for Received Pronunciation (RP) or General Northern English (GNE), nor did they show a consistent dispreference for working class or non-white accents. Instead, they showed a consistent ability to judge the quality of an answer as 'good' or 'poor' regardless of the accent the answer was presented to them in. Their answers very closely matched the answers given by the group of professionals who rated the quality of the written answers. 

The graph above shows this effect. The high quality answers are in yellow and the lower quality answers are in green. As you should be able to see, across the five different accents (see the x-axis on the bottom), the ratings remain relatively the same. At the same time, however, it is worth noting that EE & MLE receive the lowest ratings of all the accents. 

Note, however, that RP is also lower rated than some of the other accents. This is surprising given that RP was evaluated as the most prestigious accent in the label study. It's possible that this ranking might be related to the association of RP with a higher level of education, so there is a greater expectation of these individuals. 

It is also interesting to note that some of the social factors seen to effect the general public's responses do not seem to influence the professional's judgements. The age and regional origin of  legal professionals did not affect how they responded to job candidates, unlike what we found among the general public. Their Motivation to Control a Prejudiced Response (MCPR) - a psychological factor that had a strong effect on how listeners behaved in our public survey - also did not effect their ratings. 

Our findings therefore suggest that when legal professionals are asked to judge the suitability of a candidate, they are able to switch off biases and attend very well to the quality of an answer, judging the competency of the individual independently of their accent. 

Of course, however, the current study simulates just one small part of hiring candidates. It doesn't look at accent bias in other aspects of professional life, like informal interaction during the interview or everyday experiences on the job. So, it's possible that accent bias might influence the candidate's progression later on down the line. 

At least in terms of hiring though, it looks like it's relatively good news for speakers of regional and 'non-standard' accents! 

This summary was written by Christian Ilbury

Accent Bias: Responses to Voices

Continuing our series of posts related to the 'Accent Bias in Britain' project, in this blog post we discuss some findings from our research which investigated current attitudes to accents in Britain.

In the most recent blog post, we explored the findings of the first part of our study which investigated attitudes to accent labels. The second part of our study, detailed here, investigated how people responded to recordings of speakers with different accents to see if the same accent bias exists in speech. 

To examine these questions, we recorded 10 speakers of 5 different accents (2 speakers each). These accents were Multicultural London English (MLE), Estuary English (EE), Received Pronunciation (RP), General Northern English (GNE), and Urban West Yorkshire English (UWYE). Speakers of these accents were recorded reading scripted mock interview answers. 

These recordings were then played to over 1,100 participants aged between 18-79 from across the country. The sample of participants was balanced for both ethnicity and gender. 

For each of the 10 mock interview answers the participants heard, they were asked to evaluate the candidate's performance, knowledge, suitability, and hireability for a job. Participants were asked to rate the candidate on a 10-point scale - where 10 is the highest. They were asked to respond to questions such as:

1. “How would you rate the overall quality of the candidate's answer?”
2. “Does the candidate's answer show expert knowledge?”
3. “How likely is it that the candidate will succeed as a lawyer?”
4. “Is the candidate somebody that you personally would like to work with?”
5. “How would you rate the candidate overall?”

The participants also provided information on their age, social background, and education. 

When we analysed the results, we found a significant effect of the listener's age. Older listeners generally rated the two southern accents (MLE and EE) lower than all of the other accents. Younger participants, however, did not show this pattern. 

You can see this effect in the graph below. On the right are the older participants and on the left, the younger participants. The higher the line, the more positive the evaluation. As one can see, the ratings drop when you move from the younger respondents to their older peers. 

Is accent bias decreasing or is this just 'age-grading'?

This could mean one of two things. It could be that general attitudes to accents are changing, such that younger listeners will continue to exhibit the same accent preferences later on in life. On the other hand, it's possible that this could be evidence of age-grading. This is where young people might be more tolerant of accent diversity in their early years but become more critical as they get older.

A second finding of this study was that people's evaluations of accents in the responses to the interview questions depends on the type of question being answered. In questions that require a degree of technical or specialist knowledge, like those questions which asked specific details about law, all accents were rated more favourably. In more general questions, such as those which asked personal details or the work experience of the candidate, the accents were downrated much more.

Degree of expertise and accent rating

The effect of the 'expertise' required is shown in the graph above. The yellow line indicates 'expert' answers and the green line indicates 'non-expert' answers. As you should be able to see, all accents are rated much lower when the answer is a 'non-expert' answer than for an 'expert' answer. 

We also asked participants a series of questions aimed to test how prejudiced they were. We proposed that the more prejudiced people were, the lower their ratings of the different accents would be. In fact, this is exactly what we find. See the graph below. 

More prejudiced listeners were more likely to downrate all of the accents  

Those who reported they were more likely to be prejudiced towards different accents showed much lower ratings than those who were more likely to control their prejudice. The graph above shows ratings depending on MCPR (Motivation to Control a Prejudice Response). The blue line is those who reported that they are not prejudiced towards different accents, whereas the green line is those who report exhibiting more prejudice. 

What these results suggest is that there is a a systematic bias against certain accents in England (particularly Southern working-class varieties), whereas RP is evaluated much more positively and is perceived to be the most suitable for professional employment.

However, these results are reported for the general public. Would we see the same types of evaluations amongst those who are responsible for hiring candidates? In the next blog post, we explore this question. In the meantime, you can find our more about the project by visiting the project website. 

This summary was written by Christian Ilbury