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‘We are going to do a lot of things for college tuition’:

Vague language in the 2016 U.S. presidential debates

Abstract

The present study investigates the frequency and functions of vague expressions (e.g. something,

sort of) used in the 2016 U.S. presidential debates by Hillary Clinton and Donald Trump. The

data under scrutiny include transcripts of the televised debates (42,137 words). The study reveals

that, while Trump’s speech is less lexically varied than Clinton’s, it contains a noticeably greater

number of vague expressions. Trump’s tendency to use more instances of vague language is

most evident in the categories of ‘vague boosters’ (e.g. very), ‘vague estimators’ (e.g. many),

‘vague nouns’ (e.g. things) and ‘vague extenders’ (e.g. and other places). Clinton, however,

more frequently uses ‘vague subjectivisers’ (e.g. I think) and ‘vague possibility indicators’ (e.g.

would). The differences observed may be attributed to the personal and professional backgrounds

of the candidates and to the different communicative purposes they seek to achieve.

Keywords: Trump, Clinton, U.S. 2016 presidential election, vague language use, boosters, subjectivisers

1. Introduction

“You can’t turn a ‘no’ to a ‘yes’ without a maybe in between”, thinks Frank Underwood, the

imaginary U.S. President in the award-winning TV series House of Cards, when confronted with

his imaginary Russian counterpart ,Viktor Petrov, whose responses to a political proposal being

discussed between the two countries are too vague to be properly understood. Although

expressed in the fictional world of the TV drama series in question, deep down Frank

Underwood’s remark points to a very important feature of human communication, i.e. the use of

vague expressions. While Underwood might not be pleased with the use of vague expressions1

by his Russian counterpart, research has long demonstrated that human communication is

anything but precise (Pierce, 1902; Stubbs, 1986; Williamson, 1994). In fact, it appears that

vagueness is present “in a great deal of language use” to the extent that theories of language use

would not be complete without having vagueness as their “integral component” (Channell, 1994,

1 For a definition of vague language, see Section 2.

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p. 5). In this respect, Jucker et al. (2003, p. 1738) argue that vague language is an “interactional

strategy” without which our range of communication strategies would be gravely restricted (cf.

Cutting, 2007a).

While vague language has to date been a topic of extensive research in a variety of settings (see,

e.g., Cutting, 2007b, 2012, 2015; Drave, 2000, 2001; Fernández, 2015; Gassner, 2012; Li, 2017;

Metsä-Ketelä, 2016; Parvaresh, 2017a; Parvaresh & Ahmadian, 2016; Parvaresh & Tayebi,

2014; Ruzaitė, 2007; Sobrino, 2015; Sabet & Zhang, 2015; Zhang, 2011, 2015), it appears that

no research study has yet focused on the use of vague expressions in such high-stake endeavours

as presidential campaigns and their corresponding debates. Such an inquiry would, theoretically,

be appealing in that vague language can enable interactants to achieve a wide range of

interactional functions, especially in face-to-face interactions.

Evidently, U.S. presidential debates constitute a clear example of those face-to-face interactions

in which the candidates can be expected to resort to whatever strategy will channel more votes

their way. As Benoit et al. (2001, p. 260) note, “[t]he huge size of the presidential debate

audience means that capacity for influence is considerable.” In this context, besides using vague

language in a general way, presidential candidates may resort to vague expressions for some

specific functions (e.g., ‘avoiding precision’).

The current study analyses the three 2016 presidential debates held between the Democratic

nominee Hillary Clinton and the Republican nominee Donald Trump. The first debate took place

on September 26, the second on October 9 and the last debate on October 19. By developing a

“data-informed understanding of patterns and contexts of language use” (Cheng & O’Keeffe,

2014, p. 376), the study is an attempt to provide answers to the following research questions: (a)

Overall, what differences can be found between the language used by Donald Trump and Hillary

Clinton in terms of the number of vague expressions used? (b) What can these differences, if

any, reveal about the communicative purposes and discursive functions that the candidates under

investigation seek to achieve?

To answer the study’s research questions, a manually tagged corpus of the political debates in

question will be analysed both quantitatively, by using WordSmith Tools (version 7.0), and

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qualitatively. In other words, the study adopts a mixed methods approach in which “elements of

qualitative and quantitative research approaches” have been combined (Johnson et al., 2007, p.

123).

2. Vague language

Vague language is “a central feature of daily language in use, both spoken and written” (Cutting,

2007a, p. 3; cf. Cutting, 2015). In fact, vague language “has come to occupy a new place of

legitimacy as a potentially crucial area of inquiry into language use, particularly for

understanding the dynamics of interpersonal interaction” (Fernández & Yuldashev, 2011, p.

2610).

From a philosophical perspective, Smith (cited in Overstreet, 2011, p. 293) proposes that almost

all non-mathematical expressions in natural languages must have vagueness as their inherent

property2. However, as acknowledged by Overstreet (2011, p. 293), “while recognizing the

importance of these observations for a formal semantics of natural language, we should make a

distinction between vagueness as found in the philosophical tradition, and vague language as

found in the study of discourse.” From a discursive perspective, when people use vague

language, they use “words and phrases with very general meanings (thing, stuff, or whatever,

sort of, or something, or anything)” in order to “refer to people and things in a non-specific,

imprecise way” (Carter & McCarthy, cited in Overstreet 2011, p. 293).

As pioneered by Channell (1994), a central tenet underlying pragmatic/discursive studies on

vague language use is that, while we might be able to contextually interpret a vague utterance

(e.g. ‘She did all the people’) in the light of another (non-vague) utterance (e.g. ‘She analysed all

the theorists’) (Cutting, 2012, p. 284), vague expressions are a frequent trait of our

communication system for two main reasons:

(i) In any form of human communication there certainly are contexts which call for a

“purposely and unabashedly vague” (Channell, 1994, p. 20) use of language. An

2 The original sorites paradox would be a classic example of vagueness as discussed in philosophy. If “the removal of one grain from a heap always leaves a heap, then the successive removal of every grain still leaves a heap” (Williamson, 1994, p. 4). Indeed, the word heap is vague because we cannot precisely explain where the boundary between a heap and a non-heap is to be found.

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example would be the vague item maybe, mentioned in Section 1 above, which is

often used in contexts in which speakers want to highlight their lack of commitment

to the propositional content of an utterance.

(ii) Some of the utterances we make arise from “intrinsically uncertain” contexts

(Channell, 1994, p. 20) which necessitate the use of vague expressions. An example

is found in ‘I wanted to know about their culture, experience etc.’ when the speaker

does not seem to have any precise referent in mind (Cutting, 2012, p. 284).

While definitions of vague language abound in the literature (Cutting, 2007a), it appears that

vague language can be more fruitfully defined in terms of two axes, i.e. context-dependability

and unresolvability (Cheng, 2007; Cheng & Warren, 2003; Parvaresh & Tayebi, 2014; Zhang,

2011; cf. Janney, 2002). Conceptualized as such, vague language includes expressions whose

meaning is negotiable by the interactants (i.e. context-dependable), but which do not lose their

vague status (i.e. unresolvable). For example, in a sentence such as “Checkbooks, cash notes, and

all other things must be put in the safe upstairs” the expression and all other things constitutes an

example of vague language use in that, while the expression ‘cues’ the listener to interpret the

preceding elements (i.e. checkbooks and cash notes) as examples of a more general category

(e.g. ‘valuable papers/items’), it is not entirely clear what other items and all other things might

include (Dines, 1980).

Arguably, due to their ‘unresolvable’ nature, vague expressions depend to a great extent on

assumptions of shared knowledge between the speaker and the hearer (Tomasello, 2003). Of

course, research shows that in communication such assumptions are often successfully met and

that vague expressions rarely cause miscommunication (Dines, 1980; Parvaresh, 2015, 2017a).

3. The current study

As an attempt to further explore the strategic use of vague expressions in political discourse (cf.

Bull, 2008; D’Errico et al., 2013; Obeng, 1997), the current study is concerned with the three

presidential debates held in 2016 between the Republican nominee Donald Trump and the

Democratic nominee Hillary Clinton. It should, however, be stated in passing that in the present

study a quantitative analysis of the various ‘functions’ fulfilled by vague expressions is not

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pursued. This is in large part due to the fact that a vague language item may fulfill more than one

single function at a time and that it is sometimes impossible to specify the entire range of

functions fulfilled by a given vague expression even in context (see Cutting, 2007b; Zhang,

2015).

3. 1. Data and Method

The data for this study comprise transcripts of the three televised presidential debates conducted

in 2016 between Donald Trump and Hillary Clinton. All the sessions were transcribed by a

research assistant, thus compiling a corpus of 42,137 words, excluding the questions addressed

or words uttered by the debates’ hosts/presenters. In order to ensure that the original transcripts

were accurate, the transcripts were compared with the original audio-video files by the

researcher. Only a few discrepancies were identified which were subsequently corrected.

Following Zhang (2015, p. 68), “[t]ranscription was done in conventional orthography” and

included “actual speech plus basic non-verbal activities.”

The transcribed data were tagged manually by the researcher himself with a view to identifying

the categories of vague language delineated below:

a) Vague estimators: They include the two sub-categories of vague quantifiers and vague

approximators. Vague quantifiers (e.g. a few, many) typically “occupy the determiner

slot in a noun phrase” (Channell, 1994, p. 99; cf. Powell, 1985; Ruzaite, 2007). However,

in contrast to precise numbers, “they do not clearly specify the quantity involved” (Jucker

et al., 2003, p. 1751). Similarly, vague approximators (e.g. about, around) denote

imprecision of quantity; they usually precede a numerical expression and qualify it

(Jucker et al., 2003, p. 1758; cf. Mauranen, 2004). Accordingly, a non-vague estimator

would be the same as an exact number.

b) Vague possibility indicators (e.g. possibly, seem): They help the speaker express what

he/she views as the ‘possibility’ (or probability) of something. These expressions

typically serve to indicate uncertainty on the part of the speaker, thus making speech less

authoritative and less assertive (Carter, 2003, p. 11).

c) Vague extenders (e.g. or something, and the like): These expressions are not flexible in

their syntactic distribution and are of crucial communicative significance to the extent

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that Stubbe and Holmes (1995, p. 63) consider them as having crucial significance for

“oiling the wheels of verbal interaction” (cf. Parvaresh et al., 2012; Tagliamonte &

Denis, 2010). Typically, vague extenders “are multifunctional with the context, both

linguistic and non-linguistic, helping to constrain the interpretation on particular

occasions of use” (Cheshire, 2007, p. 157).

d) Vague boosters (e.g. overly, extremely, very): These expressions help the speaker

maintain a persona of ‘assertiveness’ in contexts in which hearers would expect such

assertiveness (Hyland, 1998, 2000; cf. Bradac, Mulac & Thompson, 1995; Holmes, 1990;

Hu & Cao, 2011). In other words, by increasing the tone of speech, boosters allow

speakers to convey a sense of conviction (Hyland, 2000).

e) Vague de-intensifiers (e.g. sort of, kind of): They serve to decrease the tone of utterances

(Berndt & Caramazza, 1978). As Zhang (2015, p. 90) notes, vague de-intensifiers

“express vaguely a low intensity degree, and decrease the tone of speech.”

f) Vague nouns (e.g. someone, thing): These expressions are almost always one of the most

common categories of vague language as they enable the speaker to serve a wide range of

communicative purposes (see Koester, 2007; Boakye, 2007). Most notably, vague nouns

indicate “lack of precision” (Crystal & Davy, 1975, p. 112) and are typically used in

contexts in which the required expressions are not known, cannot be retrieved (e.g. due to

memory lapses) or cannot be mentioned (e.g. taboo words). By referring “to semantic

categories in an open-ended way”, vague nouns also “help the conversation go smoothly”

(Shirato & Stapleton, 2007, p. 396).

g) Vague subjectivisers (e.g. I believe, we think): They help highlight the speaker’s lower

degree of commitment or certainty. Zhang (2013, p. 91) argues that, due to “its

manifestation of the speaker’s veiled opinion”, the category of subjectiviser is indeed “a

salient indicator for possible differences of vague language use.” A subjectiviser such as I

think, for example, signals “speaker commitment to an utterance” (Adolphs et al., 2007,

p. 63). As Zhang and Sabet (2016, p. 335) note, by using I think, “the speaker is not fully

committing to the truth of his/her utterance.” I think, the authors continue, “acts as a

protector to shield the speaker from the risk of being challenged and refuted.” Indeed, a

vague subjectiviser counts as such because it fulfills its functions (e.g. avoiding

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commitment to the propositional content of the utterance) by being inherently vague and

being purposefully used.3

The decision to include such a wide range of categories as examples of vague language was

motivated by mainstream research in the field, which is based on the idea that any expression

could potentially be an example of vague language as long as its meaning is contextually

underspecified (cf. Cheng, 2007). This view of vague language shifts the focus of attention from

vagueness viewed as an inherent property of certain lexical items to a pragmatic phenomenon

(cf. Gassner, 2012) concerned with pragmatic functions fulfilled by interactants in moment-by-

moment actual language use (Parvaresh & Tayebi, 2014).

It should also be noted that, while the labels given to the above-mentioned categories are not

conceptually uniform (e.g. ‘vague nouns’: part of speech; ‘vague indicators’: content conveyed;

‘vague subjectivisers’: functions), the current researcher decided to leave them unchanged seeing

that these are common terminologies used in studies of vague language.

While the pragmatic view of vague language delineated above enabled the researcher to

exclusively focus on the pragmatic functions these expressions fulfill in context, in order to

avoid imposing such pre-defined categories of vague language upon the transcribed data, the

following working definition for vague language was adopted throughout the study, motivated

by Cheng (2007), Cheng and Warren (2003) and Zhang (2011):

VL is language whose meaning is negotiable by the interactants (i.e., context-

dependability) in conversation, but does not lose its status as vague as a result of this

process (i.e., unresolvability).

About 15% of the manually tagged corpus was ‘randomly’ checked by a senior English linguist

specialising in vague language studies and a 98% inter-rater agreement was achieved. In the 2%

of the cases when the raters did not agree in the first place, agreement was reached through

consensus and after seeking advice from other experts in the field.

3 Due to reasons of space, in this paper a complete list of vague expressions considered is not provided.

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Next, following Tayebi and Parvaresh (2014), the instances of vague expressions identified were

considered in their extended discourse contexts collaboratively with a research assistant. In this

respect, and motivated by Terraschke (2013), we relied on such crucial information as the wider

discourse situation (e.g. the exchanges preceding and/or following the utterances under

scrutiny). Indeed, the video-recorded nature of the data was of immense help in capturing the

dynamics of vague language use, especially on the few occasions in which there was

disagreement between the researcher and the assistant (see Dörnyei, 2007). At this stage, due to

the fact that, as a communicative strategy, vague language functions are tremendously versatile

and at times too difficult to specify, and in order to increase the reliability of our conclusions, we

relied on and utilised Zhang’s (2015; cf. Parvaresh, 2017b) Stretchability Principle of vague

language use, according to which vague expressions are those that, depending on the functions

they fulfill, move in three different directions, upwards, downwards and horizontally. This is

graphically represented in Figure 1 below:

Figure 1: Elasticity of vague language (motivated by and adapted from Zhang, 2015, p. 62)

To clarify, consider the general examples below:

1. The point you have made is very significant.2. About two hundred people attended the lecture. 3. The manager is probably angry at me now.

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(adapted from Parvaresh, 2017a, p. 67)

As Parvaresh (2017a, p. 67) explains, in (a) above, the vague booster very “stretches the tone of

the utterance upward” and serves to highlight the significance of the point being talked about; in

(b) the vague estimator about shifts the number of people who attended the lecture in question

“horizontally”, thus providing “the right amount of information for the hearer in a context in

which it would not be possible or relevant for the speaker to say exactly how many people

attended the lecture”; and finally in (c) the vague possibility indicator probably “stretches the

tone of the utterance downward”, thus lowering the degree of certainty of the utterance.

3. 2. Linguistic and pragmatic realisations of vague languageIn order to investigate the research questions formulated in Section 1 above, both linguistic and

pragmatic realisations of vague language in the data under investigation needed to be identified.

To clarify how the definition of vague language mentioned above and the corresponding

methodology were actually used for such purposes, consider the following examples taken from

the corpus under investigation.

3. 2. 1. Vague estimatorsAs was noted above, vague estimators include the two sub-categories of vague quantifiers and

vague approximators. The following exchange, taken from the first debate, reveals how and why

a quantifier such as ‘many’ was identified as an instance of vague language:

Trump: I do want to say that I was just endorsed and more are coming next week […].

Many of them are here; admirals and generals endorsed me to lead this country. That just

happened. And many more are coming.

In this excerpt, both instances of ‘many’ are indeed examples of vague language in that, while

context-wise they serve to both implicate that “a high number of admirals who have endorsed

Trump for presidency have also attended the current debate” and that “more and more admirals

support Trump by the day” (i.e. context-dependable), it is not immediately exactly clear, relevant

or known how many admirals have actually attended the current debate or how many more

admirals will eventually come out in support of Trump (i.e. unresolvable). Pragmatically

speaking, such a vague use of language seems to have been employed by the speaker to convey

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the idea that support for Trump’s presidency among admirals is on the rise, thus concluding that

Trump is an ideal candidate that can secure America. In other words, it appears that ‘many’

enables the speaker to move the number of admirals supporting Trump positively upward, thus

conveying a sense of trustworthiness.

The following excerpt (from the same debate) contextualizes how and why an approximator such

as ‘almost’ was identified as an instance of vague language:

Trump: In a place like Chicago […] almost four thousand have been killed since Barack

Obama became president. […] almost four thousand people in Chicago have been killed.

In the above excerpt, ‘almost’ constitutes an example of vague language use in that, while the

audience are expected by Trump to interpret the number he has in mind at an extraordinary 4,000

(i.e. i.e. context-dependable), it is by no means clear or relevant what the exact number is. Such a

vague use of language enables the speaker to draw attention to the fact that a high number of

‘almost’ 4,000 people have been killed in Chicago presumably as an attempt to imply that if

Clinton were elected, the situation would not improve. In this example, if the speaker does not

have access to the exact number or if such an exact number is not available, ‘almost’ enables him

to adjust his utterance accordingly; on the contrary, if the number is known to the speaker and is

less than 4,000, ‘almost’ enables the speaker to discursively move the number closer to a higher,

presumably more shocking, figure, i.e. 4,000.

3. 2. 2. Vague possibility indicators

The following excerpt, taken from the third debate, serves to clarify how a vague possibility

indicator such as ‘would’ was identified and analysed:

Clinton: […] it is important that we not reverse marriage equality, […] that we stand up

and basically say, the Supreme Court should represent all of us. That is how I see the

court. And the kind of people that I would be looking to nominate to the [Supreme] Court

would be in the great tradition of standing up to the powerful…

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Talking about her views on the U.S. Supreme Court, in this excerpt Clinton elaborates on the

ideal characteristics of the person she would eventually nominate for the Supreme Court if she

were to be elected president. In this context, she uses the word ‘would’ twice, which is an

example of vague language use. This is due to the fact that while it would be possible to argue

that both instances of ‘would’ used are context-dependable (i.e., there exists the possibility of

Clinton nominating someone for the post in question or the possibility of Clinton nominating

someone who stands up to the powerful), they would still be unresolvable (i.e., it would still be

impossible to say whether such a decision/appointment will ever be made). In this way, the

speaker has been able to provide an answer to the question without necessarily being seen as

unduly certain about her choice. Therefore, Clinton has managed to provide an answer to the

ongoing question while at the same time taking a cautious attitude (i.e. moving the tone of the

utterance downward), as vague possibility indicators are generally associated with expressions of

uncertainty (cf. Sabet & Zhang, 2015).

3. 2. 3. Vague extendersThe following two excerpts, respectively taken from the first and the third debate, reveal how

expressions such as and all these other places and and other places were identified and analysed

as instances of vague language:

Trump: And when they made that horrible deal with Iran, they should have included the

fact that they do something with respect to North Korea. And they should have done

something with respect to Yemen and all these other places.

Trump: You look at the places I just left. You go to Pennsylvania; you go to Ohio; you go

to Florida; you go to any of them. You go to upstate New York. Our jobs have fled to

Mexico and other places.

In the first excerpt Trump is criticizing the 2015 agreement signed between Iran and the so-

called P5+1 group (the United States, the United Kingdom, Russia, France and China, plus

Germany), describing it as a ‘horrible’ deal. Trump believes that the deal is in fact a horrible one,

as it only concerns Iran’s nuclear program and has failed to bring under control what he

considers to be Iran’s relationship with North Korea. Besides, Trump also criticizes the deal on

the grounds that it fails to bring under control Iran’s influence in Yemen ‘and all these other

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places’. The expression ‘and all these other places’ is without doubt a vague expression in that,

while in the context under investigation it refers to a general category such as ‘countries on

which Iran has influence’ or even ‘countries Iran interferes with’ (i.e. context-dependable), it is

not immediately clear exactly what other countries the speaker has in mind (i.e. unresolvable).

From a functional-pragmatic perspective, it appears that in this context the expression ‘and all

these other places’ has enabled the speaker to shift the list of ‘countries on which Iran has

influence’ or ‘countries Iran interferes with’ horizontally, thus refraining from mentioning a

comprehensive list. This way, the speaker conveys to the hearer the idea that “because we share

the same knowledge, experience, and conceptual schemes, I do not need to be explicit; you will

be able to supply whatever unstated understandings are required to make sense of the utterance”

(Overstreet, 1999, p. 68).

A more or less similar situation exists in the second excerpt in which Trump is criticizing Obama

because he believes that, during his presidency, American jobs have gone, or fled, to Mexico

‘and other places’. The expression ‘and other places’ is a vague expression in that, while in the

context under investigation it refers to a general category such as ‘countries to which American

jobs have fled’ (i.e. context-dependable), it is not clear what other countries the speaker has in

mind (i.e. unresolvable), if any (i.e. it shifts the category of ‘countries to which American jobs

have fled’ horizontally). In this way, the audience in general, and supporters in particular, will be

able to supply the missing information, i.e. ‘other places’, in whatever way suits them.

3. 2. 4. Vague BoostersIn order to clarify how a vague booster such as ‘very’ was identified and discussed, let us

consider the following excerpt in which Trump talks about his views on the border between the

U.S. and Mexico:

Trump: We either have a border or we don’t. […] you [i.e. deported Mexicans] can come

back in and you [i.e. deported Mexicans] can become a citizen. But it is very unfair. We

have millions of people that did it [i.e. migration] the right way. They are on line. They

are waiting. We are going to speed up the process […] because it is very inefficient. But

they are on line and they are waiting to become citizens. Very unfair that somebody runs

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across the border, becomes a citizen. Under her [i.e. Clinton’s] plans you have open

borders.

As the exchange makes manifest, all three instances of the booster ‘very’ constitute examples of

vague language, for although they refer to what Trump describes as the unfairness of those who

are deported from the U.S. and then return and become citizens and also the inefficiency of

immigration procedures (i.e. context-dependable), they enhance the strength of the utterance in

an unspecific way (Cheng, 2007), thus enabling the speaker to convey a more assertively

confident voice (Bradac et al., 1995; Hyland, 2000; Zhang, 2011). To use Hyland’s (2005, p. 53)

terms, it appears that in this exchange the speaker’s use of boosters is an attempt at (i) closing

down “possible alternatives”, (ii) emphasizing “certainty” and (iii) marking “involvement with

the topic”, thus “taking a joint position against other voices.” This is due to the fact that ‘very’

has “stretched” the tone of utterances made in this excerpt upward (Zhang, 2011) thus

maximising the speaker’s attitudinal visibility (Hyland, 2005). In this respect, moving the

attitudinal certainty of the speaker towards the propositional content of the utterance, which has

been achieved via the booster ‘very’, can be viewed as Trump’s discursive attempts at

underscoring his fitness for the position of President of the United States.

3. 2. 5. Vague de-intensifiersThe following excerpt taken from the second debate provides information concerning how a

vague de-intensifier such as ‘sort of’ was identified and subsequently analysed in the corpus

under investigation:

Clinton: Everything you have heard from Donald is not true. I am sorry I have to keep

saying this, but he lives in an alternative reality. And it is sort of amusing to hear

somebody who hasn’t paid federal income tax in maybe 20 years talking about what he is

going to do.

As the excerpt shows, Clinton is questioning Trump’s proposed tax plans because she believes

that, as Trump has not paid income tax in the past, his attempts as a presidential candidate to

propose tax provision changes is ‘sort of’ amusing. In this context, ‘sort of’, which seems to have

been used by the speaker to de-intensify (i.e. move ‘downward’) the tone of the utterance, is

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indeed an example of vague language use. While it conveys the idea that an individual like

Trump, who has not paid income tax and is proposing changes to tax provision, is rather amusing

(i.e. context-dependability), it would be impossible to determine to what degree “Trump’s

attempts at proposing changes to tax provision” is being scaled down from what we consider an

assumed norm for being labelled ‘amusing’ (i.e. unresolvability). It should, however, be noted

that, upon a rather different, but related, reading of this utterance, ‘sort of’ can be considered a

‘lexical imprecision signal’ (Holmes, 1988) indicating that “the speaker is being approximate

perforce – due to lack of vocabulary or performance pressures” (p. 95), or a ‘semantic

imprecision signal’ indicating that “there is an intended concept which she cannot explain

precisely or for which she knows of no adequate word” (p. 96).

3. 2. 6. Vague nounsTo clarify how a vague noun such as ‘thing’ was identified and analysed in the corpus, consider

the following excerpt, taken from the third debate:

Trump: […] you [i.e. Clinton] do have experience. I say the one thing you have over me

is experience. But it is bad experience because what you have done has turned out badly.

In this excerpt, the word ‘thing’ is an example of vague language use in that, while one would be

able to interpret the expression along the lines of ‘advantage’ or ‘superiority’ (i.e. context-

dependable), it is by no means clear what the expression exactly means (i.e. moving the set

‘horizontally’). What is clear, however, is that by using ‘thing’ Trump has made an attempt to

distance himself from the topic at issue (i.e. ‘what advantage(s) Clinton has over Trump’).

3. 2. 7. Vague subjectivisersThe following excerpt, taken from the second debate, clarifies how a vague subjectiviser such as

‘I think’ was identified and analysed:

Clinton: We are producing a lot of natural gas that serves as a bridge to more renewable

fuels. And I think that is an important transition. We have to remain energy-independent.

It gives us much more power and freedom than to be worried about what goes on in the

Middle East. We have enough worries over there without having to worry about that. So I

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have a comprehensive energy policy, but it really does include fighting climate change

because I think that is a serious problem. And I support moving towards more clean

renewable energy as quickly as we can. Because I think we can be the twenty first

century clean energy superpower and […].

As the example shows, Clinton is talking about three issues: (i) the importance of a ‘transition’

from reliance on current forms of energy to the use of ‘more renewable’ fuels; (ii) the fact that

‘climate change’ is a serious problem which needs to be addressed methodically; and (iii) the

fact that the USA has the potential to become a ‘clean energy superpower’. However, by using ‘I

think’ each time she explicitly puts on record the fact that those issues are her subjective opinion

rather than actual facts, thus hedging “the commitment of the speaker to that which she […]

asserts” (Rowland, 2007, p. 82) and moving the tone of the utterance downward. All instances of

‘I think’ used in this excerpt are indeed examples of vague language because their meaning is

both context-dependable (e.g. they provide information about ‘the possibility of a transition from

current forms of energy to more sustainable ones’) and unresolvable (i.e. it would not be possible

to decide how committed Clinton is to the truth of the proposals she is making).

In what follows, the quantitative findings of the study are presented and discussed in light of the

research questions formulated above.

4. Results

Transcription of the televised debates resulted in a corpus of 42,137 words, 22,659 words uttered

by Trump and 19,478 words by Clinton. The following table shows the number of words spoken

by each candidate on each occasion, and also the total across all three debates:

Table 1: The transcribed corpusFirst Second Third Total

16

Debate Debate Debate

Clinton 6,457 6,202 6,819 19,478

Trump 8,793 7,197 6,669 22,659

Percentage Difference 30.63% 14.85% 2.22% 15.09%

All Debates 42,137

As Table 1 shows, Trump generally used more words compared to Clinton in the first two

debates; this results in an overall 15.09 percentage difference between the two candidates. To

make the corpora comparable, the Type-Token Ratio and the Standardised Type/Token Ratio

were also calculated for each corpus (McEnery & Hardie, 2012). The results are shown in Table

2 below.

Table 2: Lexical variabilityCandidate 1st

Debate

2nd

Debate

3rd

Debate

All

Debates

Trump

Type/Token Ratio

Standardised Type/Token Ratio

14.61

34.19

15.84

33.69

16.09

33.56

9.24

33.69

Clinton

Type/Token Ratio

Standardised Type/Token Ratio

21.08

38.62

20.40

38.32

20.60

38.75

12.57

38.56

As Table 2 shows, although overall Clinton used fewer words, her speech reveals greater

vocabulary variation on all occasions. Nevertheless, because the corpora under investigation

were slightly different in size, each frequency was also converted into a value per 1,000 words.

In other words, each frequency score was normalised.

In total, 2,072 instances of vague expressions were identified. Of these, 851 were attributed to

Clinton and 1,221 instances were attributed to Trump. Table 3 below provides more detailed

information concerning the use of vague language items across the debates in question. Note

that in Tables 3-10 ‘percentage difference’ values are positioned alongside the candidate who has

the most occurrences (per 1,000 words).

17

Table 3: Vague language use across debates and candidatesFrequency Frequency per

1,000 words

Percentage

difference

1st

Debate

Clinton 316 48.93

Trump 523 59.47 19.44

2nd

Debate

Clinton 280 45.14

Trump 331 45.99 1.86

3rd

Debate

Clinton 255 37.39

Trump 367 55.03 38.17

All Debates Clinton 851 43.69

Trump 1,221 53.88 20.88

As Table 3 shows, overall Trump used more than 20% as many vague language items as Clinton

did in the debates under investigation. Trump’s tendency to use more instances of vague

language is consistent across all the three debates. As the table shows, the most noticeable

difference between the two candidates is, however, found in the third (38.17%) and first debate

(19.44%), respectively, with the second debate ranking third (1.86%) in this respect.

The general frequency that emerged from the analysis of vague language use revealed how vague

language was generally distributed. In the following, each category of vague language used by

both candidates will be discussed separately.

4. 1. Vague boosters

The following table provides information concerning the use of vague boosters as used by both

candidates in each of the debates and across the three debates in total.

Table 4: Vague boosters Frequency Frequency per

1,000 words

Percentage

difference

1st Clinton 82 12.69

18

Debate

Trump 174 19.78 43.67

2nd

Debate

Clinton 63 10.15

Trump 99 13.75 30.12

3rd

Debate

Clinton 62 9.09

Trump 132 19.79 74.09

All

Debates

Clinton 207 10.62

Trump 405 17.87 50.89

As Table 4 shows, whilst both candidates show an overall tendency to make frequent use of

vague expressions, Trump noticeably used more instances of vague boosters in each of the

debates. Indeed, as the Appendix shows, the booster ‘very’ appears so frequently in Trump’s

speech to the extent that it becomes his most commonly used vague word.

4. 2. Vague estimators

As in the case of vague boosters discussed above, overall Trump used a noticeably higher

number of vague estimators. According to Table 5 below, with the exception of the second

debate, Trump’s tendency to use more vague estimators is consistent across the other two

debates. Also note that ‘many’ is among Trump’s most frequently used words (see Appendix).

Table 5: Vague estimators Frequency Frequency per

1,000 words

Percentage

Difference

1st

Debate

Clinton 90 13.93

Trump 155 17.62 23.39

2nd

Debate

Clinton 85 13.70 10.28

Trump 89 12.36

3rd Clinton 64 9.38

19

Debate

Trump 95 14.24 41.15

All

Debates

Clinton 239 12.27

Trump 339 14.96 19.75

4. 3. Vague nouns

Table 6 below summarises the differences found between Trump and Clinton in terms of the

number of vague nouns used in each debate and across the three debates in total.

Table 6: Vague nouns Frequency Frequency per

1,000 words

Percentage

difference

1st

Debate

Clinton 41 6.34

Trump 90 10.23 46.95

2nd

Debate

Clinton 48 7.73

Trump 70 9.72 22.80

3rd

Debate

Clinton 30 4.39

Trump 59 8.84 67.27

All

Debates

Clinton 119 6.10

Trump 219 9.66 43.78

As Table 6 shows, Trump used a greater number of vague nouns compared to Clinton’s,

especially in the first (46.95%) and third (67.27%) debates. This tendency has resulted in his

higher overall use of vague nouns (43.78%).

20

4. 4. Vague extenders

As far as the corpora under investigation reveal, Trump used a noticeably greater number of

vague extenders compared to Clinton’s. The following table reveals how both candidates used

vague extenders in each debate and across the three debates in total.

Table 7: Vague extenders Frequency Frequency per

1,000 words

Percentage

Difference

1st

Debate

Clinton 3 0.46

Trump 13 1.47 104.66

2nd

Debate

Clinton 9 1.45 26.56

Trump 8 1.11

3rd

Debate

Clinton 9 1.31

Trump 13 1.94 38.76

All

Debates

Clinton 21 1.07

Trump 34 1.50 33.46

As Table 7 reveals, with the exception of the second debate, Trump’s tendency to use a greater

number of vague expressions is consistent across the other two debates, thus resulting in an

overall percentage difference of 33.46%.

4. 5. Vague subjectivisers

In the three presidential debates under investigation, Clinton used a higher number of vague

subjectivisers overall (46%). Table 8 below summarises the results.

Table 8: Vague subjectivisers Frequency Frequency per Percentage

21

1,000 words difference

1st

Debate

Clinton 43 6.65 40.07

Trump 39 4.43

2nd

Debate

Clinton 33 5.32 67.67

Trump 19 2.63

3rd

Debate

Clinton 45 6.59 37.90

Trump 30 4.49

All

Debates

Clinton 121 6.21 46.18

Trump 88 3.88

As the table illustrates, Clinton’s tendency to use more instances of vague subjectivisers is

consistent across all the three debates. This tendency can be taken as evidence which suggests

that, compared to her rival, Clinton tends to highlight her lower degree of commitment or

certainty to a greater extent than Trump.

4. 6. Vague possibility indicators

The results of the current study indicate that, once again, Clinton used more instances of vague

possibility indicators compared to her rival Trump. Consider the table below:

Table 9: Vague possibility indicators Frequency Frequency per

1,000 words

Percentage

difference

1st

Debate

Clinton 55 8.51 37.87

Trump 51 5.80

22

2nd

Debate

Clinton 39 6.28 7.43

Trump 42 5.83

3rd

Debate

Clinton 45 6.59 17.31

Trump 37 5.54

All

Debates

Clinton 139 7.13 21.77

Trump 130 5.73

As the table shows, the differences are more noticeable in the first (37.87%) and third debate

(17.31%), resulting in an overall 21.77 percentage difference between the two candidates. In

particular, it is interesting to note that the possibility indicator ‘would’ is constantly among

Clinton’s two foremost vague expressions (see Appendix).

4. 7. Vague de-intensifiers

Vague de-intensifiers (e.g. ‘sort of’, ‘somewhat’) comprise the least frequent category of vague

expressions used by both candidates under scrutiny. Indeed, both candidates used considerably

more instances of vague boosters (see Table 4) than vague de-intensifiers to the extent that, in

comparison with vague boosters, vague de-intensifiers are almost non-existent.

Table 10: Vague de-intensifiers Frequency Frequency per

1,000 words

Percentage

difference

1st

Debate

Clinton 2 0.30 92.68

Trump 1 0.11

2nd

Debate

Clinton 3 0.48

Trump 4 0.55 13.59

3rd Clinton 0 0.00 ---*

23

Debate

Trump 1 0.14 ---*

All

Debates

Clinton 5 0.25

Trump 6 0.26 3.92

*Note that Percentage difference can only be calculated for positive numbers

greater than 0.

5. Discussion and conclusion

It has long been argued that vague language is an important feature of language for it facilitates

communication. In this respect, several researchers have recently argued that we are always

confronted with vagueness (Janney, 2002) and that appropriate use of vague language is a

hallmark of a skilled language user (Carter & McCarthy, 2006; Channell, 1994). As Ediger

(1995, p. 127) notes, “the ability to use appropriately vague language in certain situations, in

fact, allows speakers and writers to tailor their language more suitably to a particular context or

situation.” The present study was concerned with the use of vague expressions in the three U.S.

presidential debates between Hillary Clinton and Donald Trump. The results showed that:

a. Trump’s speech reveals less lexical variability compared to Clinton’s.

b. Vague language is frequently used in the debates under investigation.

c. Trump used many more instances of vague language compared to Clinton, particularly

vague boosters (50.89%), vague nouns (43.78%), vague extenders (33.46%) and vague

estimators (19.75%).

d. Clinton used notably more instances of vague subjectivisers (46.18%) and vague

possibility indicators (21.77%) compared to her rival Trump.

e. Vague de-intensifiers were almost non-existent in the corpora under investigation.

24

Regarding the first finding of the study, it could be claimed that the rather high number of vague

expressions (e.g. ‘things’) in Trump’s speech, which are constantly repeated, might, to some

extent, have resulted in his speech being less lexically varied4.

The second finding of the study shows that, regardless of whether or not vague language is

‘appropriate’ within the context of political debates, the candidates tended to resort to using

vague expressions. An observation that can be made on the basis of the rather high frequency of

vague expressions employed in the political debates under investigation, and found both in

Trump’s and Clinton’s speeches, is that both candidates tended to make frequent use of vague

expressions, albeit with certain differences in the number used. Noting that vague language has

been claimed to feature mainly in more informal conversations, it would appear that a

supposedly formal event such as a political debate (Irvine, 1979), does not necessarily feature

more formal language (i.e. one with fewer vague expressions). While it would be too far-

reaching a claim to equate political debates, such as the type discussed in this paper, to

‘conversation’, it could be claimed that those debates investigated in this study have, to some

extent, come closer to adapting typical features of informal conversations. Indeed, candidates

“seem to be aware that voters favour simple over sophisticated rhetoric” (Ahmadian et al., 2017:

50; cf. Malouf & Mullen, 2008). Note that recent research has clearly documented that an

association exists:

between simple campaign rhetoric and success in gaining power (Conway et al.,

2012; Suedfeld & Rank, 1976). The key lesson is to match one's complexity to

that of the audience (Suedfeld, 1992). (Ahmadian et al, 2017, p. 52; emphasis

added).

Arguably, the frequent use of vague language items in political debates can also be attributed to

the fact that, as was discussed above, vague expressions have the potential to help the speaker

fulfill a variety of functions in communication. Indeed, to borrow from Bavelas et al. (1990, p.

4 I am aware that, given the high-stake nature of the debates in question in which people may need precision rather than imprecision, some people may consider a vague noun such as ‘thing’, as used in 'the one thing you have over me' being uttered by a presidential candidate, to be inappropriate. However, we are not at this stage in a position to judge which expression would be more appropriate.

25

235-236), a “logical” explanation regarding the vagueness observed in political communication

would be to attribute a politician’s vague language use to the situation he/she has found

himself/herself in; a situation in which for the audience “[p]erceiving the communication of a

political candidate as vague seems more dependent on his lack of stand and not so much on the

fact that he does not [, by resorting to vague language,] explain his political action into details”

(D’Errico et al., 2013, p. 11). In other words, as long a particular candidate in the view of his/her

supporters does not lack ‘stand’, it would be rather unlikely that his/her frequent use of vague

expressions could necessarily make him/her sound weak or undetermined. It is exactly against

such a backdrop that one could claim that the notion of ‘appropriate’ vague language use has

something to do with the range of strategic functions it serves in communication. According to

Capone (2010, p. 2967), in political speeches such as the ones discussed in this paper, it is the

audience that in part “establishes the meaning of what is said.”

The reasons behind why Trump used a greater number of vague expressions, compared to

Clinton, are not entirely clear. What is clear, however, is that Trump’s speech reveals more

vague expressions and thus a more informal language, a factor which, as stated above, may be a

successful factor in ‘gaining power’. While the literature on the relationship between vague

language and gender is not at all conclusive, Channell’s (1994) claim is that vagueness is

“stereotypically associated” more with women rather than men, “whether or not they actually use

more vague expressions” (p. 193). The fact that Trump used more instances of vague language in

all the three debates under scrutiny seems to be in conflict with such a prediction. Such a finding

also seems not to be consistent with the prediction that in mixed-sex dialogues “females use

double the density of vague language that males do” (Cutting, 2007c, p. 228). What this finding

clearly shows, however, is that Trump’s speech, compared to that of Clinton’s, is generally

closer to a more casual mode of communication; indeed, research has clearly shown that “the

dialogues that contain the highest density of vague language are the casual conversations

between close friends” (Cutting, 2007c, p. 228).

As was noted above, one of the categories in which Trump used notably more expressions is that

of vague boosters (e.g. ‘very’). Taking the issue of gender into consideration, this is in conflict

with the findings of other studies. With regards to a vague expression such as ‘very’, for

26

example, Murphy (2010, p. 132) reports that it occurs “less frequently in the male data.”

Regarding other vague expressions (e.g. absolutely), Murphy (2010) also reports that “males

boost less often” (p. 158). Murphy’s hypothesis, which is based on data pertaining to casual

conversations, is worth considering:

The fact that they [males] boost less often may be due to the way males and

females interact and converse. Females have generally been found to be more

interactive and open during conversation than men (Holmes, 1995). They bond

during conversation and become very enthused and engaged in the topic which

may account for high frequency of boosters. Men, on the other hand, have been

found to be less interactive which may account for their low use of boosting

devices. (Murphy, 2010, pp. 158-159)

Trump’s more frequent use of vague boosters appears to be a result of his tendency to appear as

authoritatively confident as possible. In this respect, it seems that Trump is more inclined to

resort to vague boosters to discursively highlight a sense of assertiveness. Such frequent use of

vague boosters can also be taken as evidence suggesting that Trump wants to appear more

interactive and engaged, presumably as an attempt to make the audience feel involved in the

communication process. Whilst the extent to which more frequent use of vague boosters can, in

practice, help the speaker achieve more authority is still far from clear, it “at least sketches out a

possible terrain of inquiry” (Corcoran, 1990, p. 65) for future research in the field, especially

with reference to “economic and power processes” (Izadi & Parvaresh, 2016, p.201) involved.

Arguably, assertiveness’ is not necessarily a feature of vague boosters and each member of the

audience might have a different interpretation of each candidate’s assertiveness. In fact, it would

not be surprising to find people who believe that, overall, Clinton has had a more assertive tone.

What is suggested here is that by using more instances of vague boosters, Trump has tried to

portray himself as a more assertive person. The extent to which he has been successful is, of

course, a matter of political, social, and strategic debate.

The overall higher use of vague estimators in Trump’s speech can also be taken as evidence

suggesting that he has a greater tendency to avoid specifying “the quantity involved” (Jucker et

27

al., 2003, p. 1751) or to avoid giving precise information for various reasons (cf. Mauranen,

2004).

In this context, Clinton’s notably more frequent use of vague subjectivisers (e.g. I think) and

vague possibility indicators (e.g. would) compared to her rival Trump, points towards Clinton’s

tendency to further highlight her subjective opinion (Rue & Zhang, 2008). It therefore appears

that Clinton tends to convey the idea that “what I say here is merely my personal opinion” to a

greater extent than Trump, thus protecting herself from the risk of being challenged and refuted

(Zhang & Sabet, 2016). Extrapolating from this, one could claim that Clinton tends to adopt a

more cautious tone compared to that of her rival, particularly when it is considered that these

expressions are typically associated with the expression of a speaker’s uncertainty and

tentativeness.

Finally, the low number of vague de-intensifiers found in this study is in sharp contrast with the

commonly held belief that people generally tend to ‘hedge’ their utterances rather than to boost

them (for a discussion, see Hyland, 2000, 2005; Powell, 1985). Even if one combines the

category of ‘vague possibility indicators’ with that of ‘vague deintensifiers’, which both move

the degree of certainty an utterance expresses downward, one would still be able to see a huge

gap between the use of vague boosters and these expressions. Such a deviation from using more

instances of uncertainty markers than vague boosters can clearly be explained by referring to the

nature of the debates in question, which presumably require the candidates to express themselves

with more certainty and confidence.

On a general level, the differences observed can, on the one hand, be interpreted with reference

to the well-defined personality, career, and professional differences between the candidates in

question and, on the other hand, be attributed to the different communicative purposes they seek

to achieve. Indeed, besides the high-stake nature of the presidential debates under investigation,

the differences observed can be attributed to the fact that, as repeatedly acknowledged by both

media and the candidates themselves, the nominees in this campaign clearly belonged to, and

represented, opposing views and personalities. While group membership and related experience

alone cannot determine communicative strategies, it might, in one way or another, influence the

28

way in which each candidate formulates his/her speech. Such stark contrasts between the two

candidates may lead us to consider how the debate under investigation, in general, and the

differences in the use of vague expressions, in particular, have been caused by such seemingly

intercultural differences (cf. Kecskes, 2014). Trump and Clinton “might frequent the same

weddings and tax brackets, but they represent competing binaries”, wrote Thomson (2016) in

The Atlantic several months before the debates.

Nevertheless, one should not lose sight of the fact that notions such as speaker’s ‘assertiveness

and ‘authority’ mentioned above depend not only on the use of vague expressions, but on a

multitude of other factors (e.g. lexical choice, body language, intonation, audience expectations

and power relations), the investigation of which is certainly beyond the scope of the present

paper.

On the whole, the findings of the current study show that, despite differences in individual

speakers, vague language is frequently used in political debates in what can best be described as

“fluid, dynamic and multidimensional” as well as “stretchable and strategic” ways (Zhang, 2016,

p. 18). As Mey (2017, p. 198) notes, however, “working along CL [Corpus Linguistics] lines

often opens up for new vistas.” This study is no exception. Therefore, more work needs to be

done on vague language use in political discourse in general, and in political debates in

particular, by drawing on corpora of a larger size. Other possible avenues for future research

would be the investigation of the frequency and function of vague language in political debates

in different languages and cultures, and also intercultural debates in which politicians of different

language and cultural backgrounds are involved. Future researchers may also be interested in

investigating audience perceptions of vague language use in political debates to measure how,

and to what extent, vagueness and equivocation can influence the voting populace.

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Appendix

Top 10 vague expressions across the debates

Clinton

Debate 1

Trump

Debate 1

Clinton

Debate 2

Trump

Debate 2

Clinton

Debate 3

Trump

Debate 3

Item Freq.

Per

1,000

Item Freq.

Per

1,000

Item Freq.

Per

1,000

Item Freq.

Per

1,000

Item Freq.

Per

1,000

Item Freq.

Per

1,000

I think 6.03 Very 8.08 I think 4.83 Very 4.44 I think 4.98 Very 5.99

Would 5.11 Thing(s) 4.66 Would 4.03 Thing(s) 4.16 Would 3.51 So 4.79

More 3.40 I think 3.86 Very 3.86 So 3.33 Very 2.78 Many 3.14

Really 3.09 Many 3.18 A lot of 3.70 Would 2.77 More 2.19 Would 3.14

Thing(s) 2.32 So 2.50 More 2.41 Many 2.22 Really 1.75 I think 3.14

A lot of 2.16 Would 2.16 Some 2.25 More 1.80 Some 1.46 Much 2.69

So 2.01 Really 2.16 Something 1.61 I think 1.80 Could 1.02 Thing(s) 2.54

Many 1.85 Some 2.04 Maybe 1.28 A lot of 1.52 Just 1.02 Millions 1.79

Some 1.85 Much 2.04 Really 1.12 Something 1.52 I believe 1.02 More 1.64

Very 1.85 More 1.36 Anyone 1.12 Really 1.38 Many 0.87 Some 1.28