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How is Brexit Linguistically-Constructed ? A Corpus Linguistic Analysis of Speeches by David Cameron, Theresa May and Boris Johnson

Denis Jamet et Pauline Rodet
p. 21-53

Résumé

Brexit as such existed linguistically before existing politically, as it has been the subject of various controversies and heated debates. From David Cameron, through Theresa May, to Boris Johnson, the conceptualization of Brexit certainly evolved. Thanks to corpus linguistics software tools together with cognitive linguistics and discourse analysis, this article seeks to study the perception of Brexit by Tories through an analysis of 45 speeches delivered by Tory Prime Ministers David Cameron, Theresa May and Boris Johnson. Following a quantitative approach, lexical frequencies as well as positive and negative keywords used by each Prime Minister are analysed and compared thanks to the use of linguistic tools, such as AntConc® and #LancsBox®. The paper concludes on a more qualitative approach by highlighting the semantic / notional domains the three Prime Ministers most frequently resort to, so as to show that Brexit is not constructed identically, at least linguistically-speaking, by the three Conservative Prime Ministers.

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Texte intégral

Introduction

1 Brexit as a political entity and reality just started existing after the UK formally left the EU on 31 January 2020. It is still an ever-evolving object of study yet to be defined. A commentator on The Guardian’s website referred to it as “the undefined being negotiated by the unprepared in order to get the unspecified for the uninformed.”1 Yet, one of the possible ways to better grasp and study this ill-defined, fuzzy entity is to resort to the language used by speakers to talk about it. As claimed by cognitive linguists2, language reflects our conceptual system and the way we perceive the world. Language is the principal way of apprehending and making sense of reality, and studying the language we use, almost unconsciously, sheds light upon the way abstract concepts are constructed. This article will mostly deal with the Conservative and Brexit rhetoric by adopting a cognitive linguistic, discourse-based approach, following Brown & Mondon’s “mixed-methods approach”3:

  • 4 Brown, Katy, Mondon, Aurelien, “Populism, the media, and the mainstreaming of the far right: The Gu (...)

A growing body of literature has highlighted the benefits of combining CDS [Critical Discourse Studies] with CL [Corpus Linguistics] […] noting the capacity of each approach to mitigate some of the limitations associated with the other, and there have been some excellent examples of such analysis […]. Some works combining DT [Discourse Theory] and CL [Corpus Linguistics] have also recently started to emerge (Nikisianis et al., 2019: 280), indicating great potential for a mutually beneficial fusion.4

2Our linguistic analysis will focus on the perception of Brexit by Tory politicians through an analysis of 45 speeches delivered by Tory Prime Ministers David Cameron, Theresa May and Boris Johnson. We will perform linguistic studies, and more specifically lexicometric analyses, i.e. analyses regarding the lexical frequencies of some keywords (KWIC), as well as textometric analyses, i.e. analyses on the lexical specificities of a text, the characteristic lexicon of a text, the contextual attractiveness of words in a text, etc.5 We will first focus on the lexical differences between the three Conservative Prime Ministers: the lexical frequencies will be analysed thanks to the use of linguistic tools, such as AntConc® and #LancsBox®, in a quantitative approach: positive and negative keywords used by each Prime Minister will be studied and compared, as well as the shared collocates for keywords such as UK and EU. Then, we will carry out a more qualitative approach by highlighting the semantic domains – a.k.a. notional domains – the three Prime Ministers most frequently resort to, with the help of USAS (UCREL Semantic Analysis System), via linguistic investigations with WMatrix4®: do the semantic domains differ from one Prime Minister to another, or are they more or less similar throughout the years? Is Brexit constructed identically or differently from a purely linguistic perspective?

Brief historical background, corpus and methodology

Brief historical background

  • 6 Allen, Nicholas, “‘Brexit Means Brexit’: Theresa May and Post-Referendum British Politics”, British (...)
  • 7 Shenhav, S., “Political Narratives and Political Reality”, International Political Science Review 2 (...)
  • 8 Spencer, A., Oppermann K., “Narrative genres of Brexit: the Leave campaign and the success of roman (...)

3 Brexit holds a central place in the British political agenda. It has paralysed the political debates ever since the outcome of the 2016 referendum was made public. The question of whether the UK should remain a member of the European Union has been a controversial subject since the UK joined the European Economic Community on 1 January 1973, after two unsuccessful attempts. This is especially true for the members of the Conservative Party, who have been divided over this issue for several decades, and the Brexit referendum acted as a catalyst6. This controversy hovering over the UK’s political stage turned into a deep political crisis on 23 January 2013, when David Cameron announced that he would hold an in-out referendum provided that the Conservative Party won the 2015 General Elections. This milestone statement at Bloomberg Institute, followed by Cameron’s reappointment as Prime Minister in 2015, triggered the beginning of a picaresque-like political narrative. According to Shenhay, narratives are used by politicians so that they can shape and describe certain events from their own perspective7. Eventually, the narrative shaped by the Leave campaign depicts Brexit as a utopian quest to exit from the EU8.

  • 9 Theresa May used this expression when she set out her objectives for exiting the EU on 17 January 2 (...)

4 As announced in the 2015 Conservative Party manifesto, a referendum on the UK’s EU membership was held in June 2016. Against all odds, the Brexiteers, campaigning in favour of Britain leaving the EU, eventually managed to convince a short majority of the voters. Following the outcome of the referendum, which did not correspond to what he had expected, Cameron announced his resignation on the day after, and Theresa May succeeded him as the captain of the boat in charge of leading the UK towards a “smooth and orderly”9 departure from the EU. After a tumultuous, and yet unsuccessful battle to have the Parliament vote in favour of her deal, Theresa May announced her resignation in 2019. She fell overboard and was replaced by current Prime Minister, Boris Johnson.

  • 10 Theatre slang for failure in performance (McConnell and Tormey, 2020).
  • 11 Baines, D., Brewer, S., Kay, A., “Political, process and programme failures in the Brexit fiasco: e (...)

5 All in all, this brief historical recall aims to show that Cameron, May and Johnson played major roles in this political “fiasco”10. As suggested by Baines et al., Brexit was a fiasco, in the sense that it involves failures in political performances and deceits11 (such as Cameron’s failure to rally his party, Theresa May’s failure to pass a Brexit deal, Johnson’s Leave campaign relying on deceits and untruthfulness). Yet, given its Italian origin from theatre slang, a “fiasco” is intrinsically linked to language. The diversity of opinions regarding the very meaning of the referendum but also the type of Brexit envisaged contributed to blurring the politicians’ messages make a linguistic analysis of the speeches all the more relevant. This is the reason why, as linguists, we decided to build and analyze a corpus composed of their discourses to study Brexit, and how Brexit is represented from a linguistic point of view.

Corpus

  • 12 See the definition of “crisis” in Merriam-Webster’s dictionary: https://www.merriam-webster.com/dic (...)
  • 13 Faucher, Florence, “Brexit : Pourquoi ? Comment ?”, in Barraud, Boris (dir.), Brexit - Dans Toutes (...)
  • 14 Alexandre-Collier, Agnès, “Le Nouveau visage de l’euroscepticisme conservateur à la Chambre des Com (...)
  • 15 Ibidem.

6 Our corpus of interest gathers speeches from David Cameron, Theresa May and Boris Johnson. They are all members of the Conservative Party, and they succeeded each other at the head of the party during the Brexit “crisis”, i.e., an unstable time and turning point in which decisive changes are impending12. Brexit is considered as a political crisis, since it represents a turning point in the “life” of the European Union. Brexit will inevitably induce drastic changes in the organisation of the EU, and things are deemed to change, for better or for worse – History will tell us. Although they share the same political affiliation, they do not necessarily endorse the same outlook on the UK’s relationship with the EU. As noted by Florence Faucher13, the issue surrounding the EU membership has profoundly divided the UK, and these divisions are even more profound amongst the members of the Conservative Party. During the referendum campaign, the Party was polarised over the issue, with 40% of the MPs campaigning in favour of Brexit14. As shown by Agnès Alexandre-Collier, the presence of Eurosceptics on the bench of the Conservative Party has been threatening the cohesion of the party ever since the ratification of the Maastricht Treaty in 199315.

  • 16 Schnapper, Pauline, “David Cameron et la campagne du Remain”, Revue Française de Civilisation Brita (...)
  • 17 Schnapper, Pauline, “Brexit, or Theresa May’s Headache”, Observatoire de la société britannique [En (...)

7Brexit uncovered cleavages and divisions of all kinds, amongst which ideological divisions within the Conservative Party. This fracture is best embedded by the fact that the two leaders of the antagonistic official referendum campaigns were both members of the Conservative Party: David Cameron, Prime Minister and front-runner of “Britain Stronger in the EU”, whereas Boris Johnson, popular figure of the party and Mayor of London at the time, led the “Vote Leave” campaign16. Another example which strikingly shows the divisions of the Party is Michael Gove’s disavowal for Theresa May. In an article for The Telegraph, he shared his opinion on a Brexit deal, which did not align with May’s, although he had been appointed as Secretary of State under her premiership.17

8This leads us to wonder about the emergence of such divisions in the reception of the discourses of the three Prime Ministers under scrutiny for this analysis. We resorted to various corpus linguistics tools to try and answer this research question.

  • 18 McEnery, Tony, Wilson, Andrew, Corpus Linguistics: An Introduction, 2ed., repr. Edinburgh Textbooks (...)

9Corpus linguistics is a branch of linguistics that has gained popularity amongst linguists recently. It can be defined as follows: “Corpus linguistics is perhaps best described for the moment in simple terms as the study of language based on examples of ‘real life’ language use”.18 Corpus linguistics enables researchers to study language based on authentic excerpts of language use. The aim of a corpus-based analysis is thus to collect a set of data representative of a specific type of language in order to study a particular linguistic phenomenon:

  • 19 McEnery, Tony, Hardie, Andrew, Corpus Linguistics: Method, Theory and Practice, Cambridge Textbooks (...)

We could define corpus linguistics as dealing with some set of machine-readable texts which is deemed an appropriate basis on which to study a specific set of research questions.19

10 The set of “machine-readable texts” collected for this study is constituted of transcripts of official statements on the theme of Brexit. These transcripts were collected from the database provided by the UK’s government website www.gov.uk. The period under scrutiny spans from 2015 to 2019, a period during which the Brexit “fiasco” was at its pinnacle. To collect the data, we used a combination of keywords to browse through the aforementioned database: Theresa May; Boris Johnson; David Cameron/Brexit/prior to 2019.

11 These transcripts constitute our set of data to investigate how Brexit is represented in the speeches of Cameron, May and Johnson. By analysing how they picture Brexit through the language each of them uses, we aim to uncover how this representation may differ, how potential differences may be concomitant to their different points of view. The benefits of corpus linguistics for the study of political discourse is highlighted by Brown & Mondon:

  • 20 Brown, Katy, Mondon, Aurelien, “Populism, the media, and the mainstreaming of the far right: The Gu (...)

Critically, with its capacity for automated analysis of large corpora, CL [Corpus Linguistics] is able to offer greater breadth than is possible with in-depth, qualitative discourse studies. […] CL offers essential tools enabling us to track its usage and emerging patterns across the entire corpus.20

  • 21 In corpus linguistics, “tokens” correspond to the number of individual words in a text.

12 92 transcripts were gathered and arranged into three sub-corpora: one for each Prime Minister. The whole corpus is distributed as follows: 34 transcripts for Theresa May (67,474 tokens21), 31 transcripts for David Cameron (64,606 tokens), and 24 for Boris Johnson (50,169 tokens). This constitutes a rather balanced set of data, enabling us to draw comparisons between the three corpora.

Methodology

13 To carry out these analyses and comparisons, we resorted to some corpus linguistics software tools in order to study the semantic patterns that contribute to the way Brexit is framed in the speeches that constitute our corpus of interest. We performed a lexical analysis combined with a semantic analysis in order to get an overview of how language was used. Then, we tried to draw some parallels between these two analyses. The lexical analysis involved the elaboration of frequency lists so as to identify the most frequent lexical items for each Prime Minister. The next step consisted in focusing on certain lexical items particularly relevant as regards the theme of our corpus: EU and UK/Britain-related terms, and then, more specifically: Brexit, EU and UK.

14 We used WMatrix4® to analyze the key semantic domains related to the perception and framing of Brexit in each set of data. WMatrix4® is a software tool developed by a group of researchers at Lancaster University. It features a semantic tagger, labelled USAS (UCREL Semantic Analysis System), which groups together words belonging to the same semantic field into pre-existing semantic categories as shown in the chart in Figure1:

  • 22 Rayson, P., Archer, D., Wilson, A., Introduction to the USAS category system, 2002, 2.

Figure 1. UCREL Semantic Analysis System22

Lexical frequencies: positive, negative and lock words

15 The first analysis we decided to carry out was to create a frequency list for each corpus so as to compare the frequencies for each token in the three corpora. We used AntConc® and downloaded the three corpora individually; we added a lemma list, so that only the lemmas, i.e. the uninflected bases of the words, would be listed in the results. As our study aimed to focus mostly on lexical frequencies so as to highlight the saliency of lexical items used in the speeches, we deemed grammatical functional words not relevant to our study, and we added a stoplist to exclude them. Yet, we decided to retain some grammatical functional items such as pronouns, as they play a role in rhetorical techniques, as well as modal auxiliaries, as they reflect the speaker’s position regarding their utterances. We first analyzed the absolute frequencies in the three corpora. According to SketchEngine®,

Frequency (also absolute frequency) refers to the number of occurrences or hits. If a word, phrase, tag etc. has a frequency of 10, it means it was found 10 times or it exists 10 times. It is an absolute figure. It is not calculated using a specific formula.23

16 We kept the first twenty-five most frequent words for each corpus, as exemplified in Figures 2, 3 and 4:

Figure 2. Absolute Frequency for the Cameron Corpus

Figure 2. Absolute Frequency for the Cameron Corpus

Figure 3. Absolute Frequency for the May Corpus

Figure 3. Absolute Frequency for the May Corpus

Figure 4. Absolute Frequency for the Johnson Corpus

17 Interestingly, the most frequent word in the three corpora is the modal auxiliary will, as well as its preterit form would, denoting future time, hence some uncertainty (epistemic modality), but also willingness from the speaker to do something (root modality). Occurrences (1) to (3) exemplify the recurrence of will in the three corpora:

18(1) CAMERON 58 Britain will hold a referendum on whether to stay in the EU. Support for our membership has declined over many years. So I am negotiating changes which will address the concerns of the British people. But these changes will benefit the EU too, and Germany can help deliver them. Let me explain.

19(2) MAY 10 We will continue to work together to keep our people safe and to stand up for our values around the world. We did so long before the European Union existed and we will continue to do so long after the UK has left.

20(3) JOHNSON 273 We will trade as much as ever before, if not more. We will be able to love our fellow Europeans, marry them, live with them, share the joy of discovering our different cultures and languages – but we will not be subject to the jurisdiction of a single court and legal system that is proving increasingly erratic and that is imitated by no other trading group.

21 The words shared by the three corpora are the following ones: people, EU, European, UK, Britain, country, all, can, new and year, which shows that those themes are shared by the three Prime Ministers, as they are frequent in their respective speeches, as exemplified by occurrences (4) to (6):

22(4) CAMERON 28 That is very positive. But we have to be frank. There are threats to the British economy, from slow growth in Europe, and challenges in other parts of the world. And so it’s very important to play a role here in encouraging other countries to make the structural reforms that we’ve made, to make sure people set and stick to targets in terms of deficit reduction and make sure that Europe does the key deals in terms of completing the single market and services, signing trade deals with the fastest growing parts of the world, the things that will make a difference to get this continent, to get these economies growing faster, which would be good for them and good for Britain.

23(5) MAY 26​ I am delighted to welcome Prime Minister Cazeneuve to Downing Street today at such an important moment in both the profound friendship between our countries and the wider relationship between Britain and the whole European Union. Mr Cazeneuve and I worked very closely together as interior ministers, tackling the shared security challenges our countries face and I look forward to continuing that close cooperation.​

24(6) JOHNSON 38​ “Today we are not only no longer a world power, but we are in the first rank even as a European one.” Two months later Margaret Thatcher had won her first majority, and began the process of reversing that view of Britain, in this country and around the world. In 1981 she took on the expert opinion of 364 economists who wrote a pompous letter to the Times, calling for a U-turn on her budgetary policies; and she routed them by delivering a supply-side revolution in Britain whose benefits we enjoy to this day.​

  • 24 We would like to thank Agnès Alexandre-Collier (private conversation) for the data provided and for (...)

25 Regarding the differences in terms of frequency, it is interesting to note that deal, agreement and future are three words frequently used by Theresa May (see occurrence (7)), but neither by Cameron nor Johnson, which is revealing of their perception of the relationship between the UK and the EU. Indeed, Theresa May’s ambition was to get her “Brexit deal” through Parliament (see “meaningful votes”); Johnson also had to secure a deal with the EU, but if he does not resort to the terms deal and agreement as often as May, it might show that he did not try to compromise with Parliament or with his own party (he actually suspended 21 Tory rebels)24:

26(7) MAY 203 And the deal sets us on course for a good future relationship with our friends and allies in the EU.

27MAY 204 A close economic partnership that is good for business.

28MAY 205 Ongoing security co-operation to keep our peoples safe.

29MAY 206 The deal honours the referendum result and is good for both the UK and the EU.

30MAY 208 Having an insurance policy to guarantee that there will never be a hard border in Northern Ireland is absolutely right it honours the UK’s solemn commitments in the Belfast/Good Friday Agreement.

31MAY 209 But if we ever have to use that insurance policy, it cannot become a permanent arrangement and it is not the template for our future relationship.

32MAY 210 The deal that MPs voted on in January was not strong enough in making that clear and legally binding changes were needed to set that right.

33MAY 211 Today we have agreed them.

34 On the contrary, Johnson (see occurrences (8) to (10)) is the only one to use the word other frequently, which is proof of a new beginning for the relationship between the UK and the EU, which has become an “other”:

35(8) JONHSON 253 Do we feel loyalty to that flag? Do our hearts pitter-patter as we watch it flutter over public buildings? On the contrary. The British share with other EU populations a growing sense of alienation, which is one of the reasons turn-out at European elections continues to decline.

36(9) JOHNSON 267 2) The Living Wage is an excellent policy, but how will you stop it being a big pull factor for uncontrolled EU migration, given that it is far higher than minimum wages in other EU countries?

37(10) JOHNSON 274 We will not lose influence in Europe or around the world – on the contrary, you could argue we will gain in clout. We are already drowned out around the table in Brussels; we are outvoted far more than any other country – 72 times in the last 20 years, and ever more regularly since 2010; and the Eurozone now has a built-in majority on all questions.

38 As the three corpora do not contain the same number of tokens, we decided to resort to relative frequencies by using #LancsBox® which, contrary to AntConc®, enables researchers to change the statistical measurement. According to SketchEngine®,

Relative frequency, frequency per million (also called freq/mill in the interface) [is] a number of occurrences (hits) of an item per million, also called i.p.m. (instances per million). It is used to compare frequencies between corpora of different sizes.25

39Using relative frequency measurement allows researchers to compare corpora of different sizes by normalizing their respective sizes. We decided to focus essentially on the most frequent words related to Europe / the European Union / the EU on the one hand, and to the UK / Britain on the other hand, as well as on the relative frequency of use for the word Brexit.

40 Figure 5 displays the results in terms of relative frequency for “EU-related words”, namely EU, Europe, Union and European. What can be noticed is a significant drop in the number of EU-related words for each successive PM:

Figure 5. Specific Relative Frequency for Europe-Related Words

41More generally, a significant decrease in the number of EU-related words in terms of relative frequency can be noted, which is symbolic of the change of focus operated by each Prime Minister, each focusing less and less on the EU, as clearly shown in Figure 6:

Figure 6. General Relative Frequency for Europe-Related Words

42 On the contrary, we analyzed the frequency of UK/Britain-related words for the three Prime Ministers (Figure 7), with the lemmas country, people, British, Britain and UK. Contrary to EU-related words, no general tendency can be observed:

Figure 7. Specific Relative Frequency for UK/Britain-Related Words

43 We then decided to restrict our analysis to the three lemmas British, Britain and UK by adding the relative frequencies for the three Prime Ministers. Strangely enough, the relative frequency for Britain/UK-related terms also sharply decreases, as exemplified in Figure 8, when the opposite tendency was expected:

Figure 8. General Relative Frequency for UK/Britain-Related Words

44This can be accounted for by the fact that once Brexit has been accepted as a political reality, the need to talk about the future of Britain and the UK tends to decrease, as the low frequency in the Johnson corpus tends to indicate, even if the question of the future of the UK outside the EU became more acute once the ties with the EU were officially cut.

  • 26 See Scott, M., WordSmith Tools Help Manual, Version 3.0., Mike Scott and Oxford University Press, 1 (...)
  • 27 A reference corpus is a corpus chosen as a standard of comparison with the corpus of interest (pilo (...)

45 The next step in our contrastive approach was to focus on the positive keywords, i.e. words with comparatively high frequency in the corpus of interest, and negative keywords, i.e. words with comparatively low frequency in the corpus of interest, when we compare their relative frequencies to the one found in a reference corpus. Positive keywords are interesting in a linguistic analysis as they indicate the “aboutness”26 of a particular text, i.e. what this text is about. We then looked at the relative frequency of each corpus compared to the BE06 corpus (a reference corpus27 of British English of various written text types: newspapers, fiction, academic writing and general prose), with the Log-likelihood statistic measurement tool:

Figure 9. Positive and Negative Keywords in the Cameron Corpus

46 The positive keywords in Cameron’s speeches have essentially to do with the EU and Britain, as Figure 9 above illustrates, which is no surprise as Cameron was the one to initiate the Brexit referendum.

Figure 10. Positive and Negative Keywords in the May Corpus

47 The positive keywords in May’s speeches are still related to the EU and the UK, but words such as deal and trade are included in the list, which is proof of the beginning of the negotiation process to withdraw from the EU, as shown in Figure 10.

Figure 11. Positive and Negative Keywords in the Johnson Corpus

48 Interestingly, even if EU- and Britain-related words are still positive keywords in Johnson’s speech, they are not as present as in Cameron’s and May’s, and the only EU-related word is EU. The word Brexit appears as well as the let’s construction, which indicates something dynamic, a change to occur initiated by an agent, as shown in Figure 11. Through the words used, Johnson wants to picture himself as someone dynamic, willing to get Brexit done quickly.

49 We finally decided to focus on the very word Brexit, which was coined in 2012 according to the OED online:

Figure 12. Brexit Entry in the OED online

50A quick analysis in Google Books Ngram Viewer (see Figure 13) clearly shows a continuous increase in the frequency of use of the term:

Figure 13. Brexit in Google Books Ngram Viewer

51 Is the continuous increase in the frequency of use of the word Brexit also found in the speeches of the three Prime Ministers? The relative frequency for Brexit in Figure 14 is quite relevant, as it shows an unexpected result: from an extremely low frequency for Cameron (0.31), the word reached a significant frequency (17.04) with May, who was mostly in charge of the withdrawal of the UK from the EU, to finally decrease with Johnson (13.56), as if the word lost some of its novelty once the deal was struck:

Figure 14. Relative Frequency of Brexit in the three corpora

  • 28 T-score: T-score expresses the certainty with which we can argue that there is an association betwe (...)
  • 29 The concept of “narrative” was introduced in section 1.1.
  • 30 Firth, John Rupert, Papers in Linguistics 1934-1951, London, Oxford University Press, 1957.

52To go deeper into the use made by the three Conservative Prime Ministers of the word Brexit, we resorted to the GraphColl tool in #LancsBox® to study the collocates of Brexit; the T-score28 statistical measurement tool was used to visualize the most frequent collocates, instead of the LogDice, which is used preferably for large corpora; interestingly, the T-score enables us to tell the “narrative”29, or more simply the “story” of Brexit for the three Prime Ministers, i.e. how a fuzzy concept is slowly taking shape through words, which leads to a coherent narrative about this concept. Studying collocates is crucial in corpus linguistics, as collocates are words that are commonly used together, and the meaning of a given word is not simply the result of its meaning, but the interactions it develops with other words, following Firth’s famous principle: “You shall know a word by the company it keeps”.30

53For David Cameron, there is no narrative or story to tell as there are no collocates for Brexit, as shown in Figure 15:

Figure 15. T-score for Brexit in the Cameron Corpus

54On the contrary, the collocates for Brexit in Figure 16 enable us to tell the following narrative about Brexit for Theresa May: “I / We will deliver a new Brexit deal”. Brexit is on the go, oriented toward the future deal aimed at by Theresa May.

Figure 16. T-score for Brexit in the May Corpus

55Finally, the collocates for Brexit found in Figure 17 perfectly summarize Boris Johnson’s narrative about Brexit (and motto31): “Let’s get Brexit done”.

Figure 17. T-score for Brexit in the Johnson Corpus

  • 32 MI Score: The Mutual Information score expresses the extent to which words co-occur compared to the (...)

56 We also studied the shared collocates for EU and UK in the three Prime Ministers’ speeches, using the MI score32. In the Cameron corpus, there are 20 shared collocates, but the majority of collocates are with EU (119), vs. UK (26):

Figure 18. Shared Collocates between EU and UK in the Cameron Corpus

57If we compare the Cameron corpus with the May corpus, there are more shared collocates (47), and the number of collocates is still more significant with EU (115) than with UK (73), even if it tends to decrease:

Figure 19. Shared Collocates between EU and UK in the May Corpus

58Finally, in the Johnson corpus, there are fewer shared collocates (only 15), even if the majority is still with EU (52), vs UK (21):

Figure 20. Shared Collocates between EU and UK in the Johnson Corpus

59Figure 21 summarizes the data with percentages added to highlight some trends:

Number of collocates for UK

Number of collocates for EU

Shared collocates between UK and EU

Total number of collocates

Cameron

26

119

20

145

17.9%

82.1%

13.8%

100%

May

73

115

47

188

38.8%

61.2%

25%

100%

Johnson

21

52

15

73

28.8%

71.2%

20.5%

100%

Figure 21. Data and Percentages on the Shared Collocates

60 We can note that the number of collocates with UK increases with May, but decreases with Johnson, and that the same trend can be observed with the shared collocates between EU and UK, which seems to be revealing of the two entities drifting apart. Yet, interestingly enough, the number of collocates with EU remains relatively high, and even increases with Johnson compared to May, as if the speeches were mimetic of the fact that the EU was still in the limelight, even more now that Brexit was on its way, and that the ties between the UK and the EU had to be severed.

Semantic analysis and notional domains

61 To go deeper into this analysis and to offer a qualitative approach, we resorted to the UCREL Semantic Analysis System (USAS) available in WMatrix4® in order to uncover the most recurrent semantic domains in our corpus of interest. This system aims to tag each word in a given corpus with a specific semantic domain. Following the result of the tagging procedure, we performed a close reading of how these semantic domains were used in context. In other words, we looked at the words tagged under the semantic domains and suggested an interpretation as regards the way they contribute to the conceptualisation and representation of Brexit in the speeches of each Prime Minister.

62 Figure 21 displays a sample of the semantic domains that appeared statistically more frequently across our data. The column on the left corresponds to the name of the semantic tag, and the column on the right shows the semantic domain that matches the tag:

Figure 21. Semantic Domains Sorted by Frequency

63 The first striking observation is that most of the notional domains tagged by the semantic tagger are common to the three Prime Ministers. For this case-study, we decided to focus on three of these domains, which seem to be significantly frequent in the Cameron, May and Johnson corpora: Geographical Names, Location and Direction and General Actions.

64 To begin with, the semantic domain Geographical Names appears significantly more frequently in the three corpora. This is no surprise given the context of our study, which involves geographical and political places. However, when considering the context of use, it is interesting to note that the politicians do not necessarily resort to the same lexical items. David Cameron uses a significant number of geographical names related to the European Union, such as euro-zone, Schengen, single-market, Germany, and this tends to differ from the Johnson corpus. We investigated the number of occurrences for the lemma Europe in the Cameron corpus and the Johnson corpus, and it confirmed our initial intuition. In the Johnson corpus, 992 words have been tagged under the domain Geographical Names, and out of these 992 words, the noun Europe appears 94 times (9,5%), whereas in the Cameron corpus, among the 2,028 words related to this semantic domain, there are 478 occurrences of the noun Europe (23%). This tends to show that Europe holds a larger place in Cameron’s speeches, and thus in Cameron’s political interest; this also supports the analysis of the shared collocates (Figures 18, 19 and 20).

  • 33 See Lakoff, George, Johnson, Mark. Metaphors We Live By, Chicago: University of Chicago Press, (198 (...)

65 Secondly, the Location and Direction semantic domain is, likewise, particularly recurrent in the three corpora. This domain includes prepositions, such as beyond, forward, away from, outside of, as well as verbs, such as face, stand, leave, come back, and nouns: destination, directions. The importance of this semantic field leads us to think that Brexit is conceived as a journey, a move from one point to another, as if Britain was literally exiting a place. The presence of this semantic field can also be linked with the Conceptual Metaphor Theory33. According to this theory, some semantic domains, such as the JOURNEY semantic domain, are used in order to conceptualise abstract notions, that is notions that cannot be easily mentally represented. For example, the notion of “love” is often talked about via the use of expressions belonging to the JOURNEY semantic domain. The expression “we are at a crossroads in our relationship” illustrates this idea. Here, the term crossroads is used metaphorically in order to frame the concept of relationships. This leads to the conceptual metaphor love is a journey. Likewise, the use of words from the Location and Direction domain to talk about Brexit could be framed under the conceptual metaphor brexit is a journey, which is a way to impose some mental structure on the fuzzy concept of Brexit.

  • 34 Rayson, P., Archer, D., Wilson, A., Introduction to the USAS category system, Benedict project repo (...)
  • 35 See Langacker’s “billiard-ball model”: Langacker, Ronald W., Foundations of Cognitive Grammar, Stan (...)
  • 36 Cooper, Luke, Cooper, Christabel, “ ‘Get Brexit Done’: The New Political Divides of England and Wal (...)

66 Thirdly, the use of the General Actions domain contributes to the conceptualisation of Brexit as a dynamic process, something moving, evolving, unstable. According to the USAS semantic tagger, the General Actions category refers to “general/abstract terms relating to an activity or action.”34 This category mostly encompasses verbs that denote actions. In cognitive grammar, verbs are likened to energy and motion35, hence instability. For instance, Theresa May repeatedly uses the expression work together. This could be linked to her will to co-operate with the EU, and it stresses the cooperative dimension of the EU-UK relationship. Interestingly, the most frequent verb in the Johnson corpus is do, a rather semantically empty verb. For instance, when Boris Johnson repeats Let’s get Brexit done, the meaning of done is elusive and unfathomable. It is unclear what done means to him. This once again echoes the fuzziness of Brexit and its abstract nature. Alternatively, Johnson’s catchphrase could be interpreted as a rhetorical means appealing to the voters who grew weary of Brexit, and who wanted to “get it done”, whatever the cost.36

  • 37 The EU membership supposedly costs £350M a week (we would like to thank Agnès Alexandre-Collier for (...)

67 Additionally, it is interesting to point out the extensive use of words tagged under the Numbers domain in the Johnson corpus, considering that this domain is statistically more dominant in the Johnson corpus than in the Cameron and May corpora. This is particularly relevant as regards Johnson’s rhetoric during the referendum campaign: one of his most memorable arguments, although based on a lie, was related to the financial cost of the EU membership, and the amount of money the NHS would allegedly receive provided that the UK left the EU. This leads us to the assumption that for Johnson Brexit is conceived as a financial exchange, as an economic issue. This may also indicate that Johnson used figures as a rhetorical tool during the referendum campaign, not only to mention the economic implications of Brexit via the fees paid to the EU37, as illustrated in (11), but also to back up the argument of British sovereignty, as illustrated in (12):

68(11) JOHNSON 961​ Do we want to spend another billion pounds a month that could be going on the NHS?

69JOHNSON 197 People are surprised and alarmed to discover that our gross contributions to the EU budget are now running at about £20bn a year and that the net contribution is £10bn, and it is not just that we have no control over how that money is spent.

70(12) JOHNSON 410 Now the WTO, that over decades has helped to break down the folly of protectionism and open markets, a benign and transformative process that is not only good for Britain, since our trade amounts to nearly 60% of our GDP, but which is good for the world, lifting billions of people out of poverty in the last 40 years.

71JOHNSON 411 And yet the gossamer web of obstruction is growing thicker every year, and the political support for openness in trade is draining away across the world, and for the first time in decades trade is no longer growing as fast as global GDP, with volumes rising by only 2.8 per cent this year compared with an average of 5 per cent since 1990.

  • 38 Charteris-Black, Jonathan, Metaphors of Brexit. No Cherries on the Cake?, Palgrave Macmillan, 2019.

72 To sum up, this semantic analysis has revealed that the three Prime Ministers resort to similar semantic domains for the major part. However, a close look at the lexical items tagged under these semantic domains pinpointed noteworthy differences and variations across their discourses. This analysis also demonstrated that the semantic tagger could also be used to study metaphors, and this is something that we wish to work on in a future, in-depth study, following Jonathan Charteris-Black’s pivotal work Metaphors of Brexit. No Cherries on the Cake?38

Conclusion

73 The aim of this article has been to analyze and compare the lexical frequencies, positive and negative keywords, collocates and semantic domains to see how Brexit was linguistically represented and constructed through the discourses of the three successive Conservative Prime Ministers. The language used in terms of lexical keywords, collocates and most frequently used semantic domains was studied in the corpora composed of the speeches of Cameron, May and Johnson. Our analyses enabled us to reach the following conclusions:

74Firstly, there are noteworthy variations between David Cameron’s, Theresa May’s and Boris Johnson’s speeches, more on the lexical level than on the semantic level, as the same semantic domains – Geographical Names, Location and Direction, and General Actions – are used by the three Prime Ministers, even if the frequency may differ. Variations are therefore to be found more at the level of the word, of the lexis used than at the level of the semantic domains, which remain pretty similar for the three Conservative Prime Ministers;

75Secondly, the lexical and the semantic analyses, even if they brought out interesting differences, remain nonetheless complementary, as they confirm some tendencies: the theme of the EU as well as EU-related words are significantly more present at the lexical level in Cameron’s and May’s speeches than in Johnson’s; this may be explained by the fact that before the referendum, the place of the EU was at stake, whereas after the referendum, it is the future place and role of the UK that is mentioned and becomes the focus of interest. Another interesting finding is that the relative frequency for Europe-related words follows a steady decline in the speeches of the successive three Prime Ministers – which was a trend that was expected – but that the relative frequency for UK/Britain-related words follows the same trend, which was something unexpected. Interestingly, the list of positive keywords, i.e. the words with comparatively high frequency, in the speeches of the three Prime Ministers shows that, on the one hand, the number of EU-related words tends to decrease when, on the other hand, the number of UK-related words tends to increase. Yet, this finding needs to be qualified because even if the number of shared collocates between EU and UK tends to decrease, the number of collocates with EU remains relatively higher than the number of collocates with UK;

76Thirdly, the conceptualization and representation of Brexit, just like Brexit itself, seems unstable and has varied from 2015 to nowadays, following the political process leading to the official leave in January 2021. The collocates of the word Brexit, which are quite different for the three Conservative Prime Ministers, have enabled us to tell its narrative and to shed some light on the way it is differently conceptualized in their respective speeches.

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Brown, Katy, Mondon, Aurelien, “Populism, the media, and the mainstreaming of the far right: The Guardian’s coverage of populism as a case study”, Politics, 2020, 1-17: https://journals.sagepub.com/doi/full/10.1177/0263395720955036

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Cooper, Luke, Cooper, Christabel, “ ‘Get Brexit Done’: The New Political Divides of England and Wales at the 2019 Election”, The Political Quarterly 91, n°4, 2020.

Fairclough, N., Mulderrig, J., Wodak, R., “Critical discourse analysis”, in van Dijk, T. A. (ed.), Discourse studies, Thousand Oaks: Sage, 2011, 357–378.

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Notes

1 https://www.theguardian.com/politics/2019/mar/05/green-lights-for-the-new-amber-rudd (see “Comments” section).

2 See Lakoff & Johnson (2003), Langacker (1987), among others.

3 Brown, Katy, Mondon, Aurelien, “Populism, the media, and the mainstreaming of the far right : The Guardian’s coverage of populism as a case study”, Politics, 2020, 3.

4 Brown, Katy, Mondon, Aurelien, “Populism, the media, and the mainstreaming of the far right: The Guardian’s coverage of populism as a case study”, Politics, 2020, 4.
According to Fairclough et al., Critical Discourse Analysis is a “problem-oriented interdisciplinary research movement, subsuming a variety of approaches, each with different theoretical models, research methods and agenda.” (Fairclough, N., Mulderrig, J., Wodak, R., “Critical discourse analysis”, in van Dijk, T. A. (ed),Discourse studies, Thousand Oaks: Sage, 2011, 357–378). “By studying discourse, it emphasizes the way in which language is implicated in issues such as power and ideology that determine how language is used, what effect it has, and how it reflects, serves, and furthers the interests, positions, perspectives, and values of, those who are in power.” (Waugh, L., Catalano, T., Masaeed, K., Hong Do, T., Renigar, P., “Critical Discourse Analysis: Definition, Approaches, Relation to Pragmatics, Critique, and Trends”, in Capone, A., Mey, J. (eds) Interdisciplinary Studies in Pragmatics, Culture and Society, Perspectives in Pragmatics, Philosophy & Psychology, vol 4. Springer, Cham, 2016, 72).

5 The definition of “textometry” is available at http://textometrie.ens-lyon.fr/spip.php?rubrique80&lang=en

6 Allen, Nicholas, “‘Brexit Means Brexit’: Theresa May and Post-Referendum British Politics”, British Politics 13, no 1, April 2018, 109.

7 Shenhav, S., “Political Narratives and Political Reality”, International Political Science Review 27, n°3, 2006, 248.

8 Spencer, A., Oppermann K., “Narrative genres of Brexit: the Leave campaign and the success of romance”, Journal of European Public Policy, 2019, 676.

9 Theresa May used this expression when she set out her objectives for exiting the EU on 17 January 2017, at Downing Street.

10 Theatre slang for failure in performance (McConnell and Tormey, 2020).

11 Baines, D., Brewer, S., Kay, A., “Political, process and programme failures in the Brexit fiasco: exploring the role of policy deception”, Journal of European Public Policy 27, n°5, 2020, 743-744.

12 See the definition of “crisis” in Merriam-Webster’s dictionary: https://www.merriam-webster.com/dictionary/crisis

13 Faucher, Florence, “Brexit : Pourquoi ? Comment ?”, in Barraud, Boris (dir.), Brexit - Dans Toutes Ses Dimensions, Paris: Éditions L’Harmattan, 2018, 18.

14 Alexandre-Collier, Agnès, “Le Nouveau visage de l’euroscepticisme conservateur à la Chambre des Communes”, Revue Française de Civilisation Britannique [En ligne], XXII-2, 2017, 2.

15 Ibidem.

16 Schnapper, Pauline, “David Cameron et la campagne du Remain”, Revue Française de Civilisation Britannique [En ligne], XXII-2, 2017, 6.

17 Schnapper, Pauline, “Brexit, or Theresa May’s Headache”, Observatoire de la société britannique [En ligne], 21, 2018, 6.

18 McEnery, Tony, Wilson, Andrew, Corpus Linguistics: An Introduction, 2ed., repr. Edinburgh Textbooks in Empirical Linguistics, Edinburgh: Edinburgh University Press, 2011, 1.

19 McEnery, Tony, Hardie, Andrew, Corpus Linguistics: Method, Theory and Practice, Cambridge Textbooks in Linguistics, Cambridge: Cambridge University Press, 2012, 1.

20 Brown, Katy, Mondon, Aurelien, “Populism, the media, and the mainstreaming of the far right: The Guardian’s coverage of populism as a case study”, Politics, 2020, 4-5.

21 In corpus linguistics, “tokens” correspond to the number of individual words in a text.

22 Rayson, P., Archer, D., Wilson, A., Introduction to the USAS category system, 2002, 2.

23 https://www.sketchengine.eu/my_keywords/frequency/

24 We would like to thank Agnès Alexandre-Collier (private conversation) for the data provided and for her interpretation.

25 https://www.sketchengine.eu/my_keywords/freqmill/

26 See Scott, M., WordSmith Tools Help Manual, Version 3.0., Mike Scott and Oxford University Press, 1999.

27 A reference corpus is a corpus chosen as a standard of comparison with the corpus of interest (pilot corpus).

28 T-score: T-score expresses the certainty with which we can argue that there is an association between the words, i.e. their co-occurrence is not random. The value is affected by the frequency of the whole collocation which is why very frequent word combinations tend to reach a high T-score despite not being significant collocations: https://www.sketchengine.eu/my_keywords/t-score/

29 The concept of “narrative” was introduced in section 1.1.

30 Firth, John Rupert, Papers in Linguistics 1934-1951, London, Oxford University Press, 1957.

31 https://www.reuters.com/article/us-britain-eu-johnson-idUSKBN1YZ1EQ

32 MI Score: The Mutual Information score expresses the extent to which words co-occur compared to the number of times they appear separately: https://www.sketchengine.eu/my_keywords/mi-score/

33 See Lakoff, George, Johnson, Mark. Metaphors We Live By, Chicago: University of Chicago Press, (1980) 2003.

34 Rayson, P., Archer, D., Wilson, A., Introduction to the USAS category system, Benedict project report, 2002, 3.

35 See Langacker’s “billiard-ball model”: Langacker, Ronald W., Foundations of Cognitive Grammar, Stanford University Press, 1987, 56.

36 Cooper, Luke, Cooper, Christabel, “ ‘Get Brexit Done’: The New Political Divides of England and Wales at the 2019 Election”, The Political Quarterly 91, n°4, 2020, 1.

37 The EU membership supposedly costs £350M a week (we would like to thank Agnès Alexandre-Collier for this information).

38 Charteris-Black, Jonathan, Metaphors of Brexit. No Cherries on the Cake?, Palgrave Macmillan, 2019.

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Denis Jamet et Pauline Rodet, « How is Brexit Linguistically-Constructed ? A Corpus Linguistic Analysis of Speeches by David Cameron, Theresa May and Boris Johnson »Observatoire de la société britannique, 27 | 2021, 21-53.

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Denis Jamet et Pauline Rodet, « How is Brexit Linguistically-Constructed ? A Corpus Linguistic Analysis of Speeches by David Cameron, Theresa May and Boris Johnson »Observatoire de la société britannique [En ligne], 27 | 2021, mis en ligne le 01 juin 2022, consulté le 31 mai 2023. URL : http://journals.openedition.org/osb/5290 ; DOI : https://doi.org/10.4000/osb.5290

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Denis Jamet

Professeur en linguistique anglaise à l'Université Jean Moulin Lyon 3 et Professeur associé de linguistique française à l'Université de l'Arizona (US)

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Pauline Rodet

Doctorante en linguistique anglaise à l'Université Jean Moulin Lyon 3

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