I know it, you know it, everybody knows it: Trump’s Words and Shifty Information

Mike Mena

The Graduate Center, CUNY

michaeldmena85@gmail.com

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What Trump really means”…

“I know words…I have the best words,” President Trump proclaimed to a cheering crowd on the campaign trail in late 2015.  Trump’s “words” have been a gift to political satire.  For example, there is the Kindle publication Make Poetry Great Again: The Poems of Donald J. Trump (2016), which is described as a “groundbreaking collection of poetry” filled with “The Donald’s most poetic turns of phrase.”  There is also the meticulously footnoted collection, The Beautiful Poetry of Donald Trump (2017), which claims his words reveal a “sensitive and shyly artistic side,” we just need to pay closer attention.  Finally, although there are many more, there is the e-book Bigly: Donald Trump in Verse (2017), whose author asserts, “Never in American history has the White House been graced with a man so vivid in his use of metaphor.”   Understanding poetry requires that a reader hold a certain amount of presupposed knowledge—for example, that the genre may feature rhyme schemes paired with particular compositional techniques, and, of course, familiarity with the author’s style always helps.  What we generally do not do is refer to the current Oxford Dictionary with the expectation that definitions will help us interpret the words of poets.  Nor do most Americans carry around a dictionary to help interpret a conversation with friends, or to comprehend a joke on television—we rely heavily on context to understand what words mean.  Sometimes, dictionary definitions would not help either way.  (How would one define the word “that” in the question: “Did you hear that?”)  My goal here is not to support the idea that Trump is a literary poet. However, what these satirical poetry books do well is present Trump’s words in a way that foregrounds the poetic and indexical functions of language (more on this below) while deemphasizing the denotational function—the aspect of language concerned with literal dictionary definitions and matching up words with things and concepts.  I will argue that foregrounding the denotational content of Trump’s words will not produce any substantial public critique of what Trump says—it will, on the contrary, support and legitimize Trump’s words as always potentially being “true” statements.

This essay will focus on several of Trump’s statements and their mediation through two “non-partisan” organizations—PolitiFact.com and CNN— which I assert help to legitimize constant denotational and definitional shifts of Trump’s words.  PolitiFact is one of many so-called “fact-checking” media sources dedicated to “checking the facts”—that is, breaking down and analyzing the truth-value of politician’s statements.  The process appears straight-forward: report Trump’s words and verify their accuracy.  However, as will be shown, the process of reframing Trump’s words into propositions that are potentially true or false is a widely overlooked interpretative maneuver and central to the problem of Trump’s words always appearing to shift meaning.  CNN similarly dedicates much effort to narrowing and “defining” the denotational content of Trump’s words—or more colloquially phrased, both of these organizations try to report on what Trump “really means” and verify that information.   As will be shown, the “news interview” on broadcasting networks like CNN is a privileged site where information shifts are rapidly created, deployed, and legitimized. This process is not simple and involves overlapping ideological beliefs about how language should be used and by whom. 

As voters, we believe politicians should, at a minimum, speak “information” that is not blatantly false (Hill 2000).  As TV news viewers, we expect that there is, or should be, an effort undertaken by news organizations to present “neutral” information (Clayman and Heritage 2002).  And finally, news organizations themselves hold ethical commitments to presenting “objective” information to viewers.  Reporting what someone says “objectively” may begin with reporting a spoken utterance word-for-word.  However, when Trump says something like, “a lot of people know what I mean,” this might force follow-up questions such as: Which people?  How many is a lot? What do they know that our viewers do not?  Asking such questions presupposes there is some information that can be proven true or false.  Nonpartisan news organizations need to present “facts”—the ability to produce a stance of “neutrality” and “objectivity” depends on it.  This essay suggests that the stylistic practice of “objective reporting” supports, wittingly or unwittingly, the ongoing legitimation of what I call here (with a wink to Michael Silverstein) shifty information—that is, information within Trump’s words becomes capable of shifting meaning once detached from one context (decontextualized) and then reported in a new context (recontextualized).  To elucidate this argument it will first be necessary to call attention to one basic, but powerful folk belief on the nature of language: that words have stable definitions and that is how people primarily understand speech.

                                                                                                 

“Shifters” and Their Shiftiness

It is not accidental that we almost immediately focus on denotational content and on the definitions of words—Silverstein (1976, 2001[1981]) has convincingly argued that the history of Western knowledge is built upon the ideological belief that language primarily functions as symbolic or representational, meaning there are things in the world that words stand in for when we communicate—in other words, matching words to things is primarily what makes communication possible.  The overwhelming focus on the denotational function of language resulted in the downplaying of another crucial feature: the indexical function.  It does not suit the needs of this essay to offer an extensive conversation of indexicality, except perhaps to say “indexes” (like our index-finger) point to context, both “backward” and “forward”—in other words, indexes require some presupposed knowledge to make sense (the pointing backward at previous known information), and the very practice of drawing upon this presupposed knowledge has creative effects in the world we live in (the pointing forward to the emerging context as it is happening in “real-time,” which creates new information).  There are particular words that work primarily as “indexes”—more so than anything else—meaning it is difficult to find a denotational or definitional meaning of these words without knowing the immediate context.  The technical term for these words is “deixis,” however, I will include them in a more inclusive and generalizable term: “shifters,” which can be shown through the following examples.

We might start with the shifter word “you” in the exclamatory sentence “Hey, you!”  What does you mean?  What (or who) is the definition or denotational content of the word you in this example?  It is difficult to narrow down whom we are speaking to without knowing the context we are in.  As we might expect, a dictionary will not help us figure out what you “really means” since the dictionary operates with even less context than what I have given. I could yell “Hey, you!” to a person walking up the sidewalk and that person waves, but there is a confused look on her face.  In that split second the you was interpreted by the confused stranger to “mean” her, however, I was actually yelling at my friend walking a few steps behind. To be polite, I pretend to be saying hello to the stranger, making the you “actually mean” the stranger.  Within that interaction the word you rapidly “shifted” meanings at least three times.  Yet, we did not even mention that my friend also waved back to the “Hey, you!” and as now thoroughly offended that I seem to be ignoring them.  We might call words like these “person-shifters.”  This includes words like you, them, I, we, everybody, people—any words that the dictionary would be near useless to help us figure out who is being spoken of or who is “really meant.”  As mentioned above, all shifters draw upon presupposed knowledge—they point backward to previous information to make sense.  But, just as importantly, shifters help create new context—they point forward and create new information.  In this paragraph, I (shifter) have been creating a relationship, or creating a we (shifter), both me (shifter) and you (shifter)—teamwork!—working to figure out what “person-shifters” are.   There are other kinds of shifters, such as “space-shifters” (like here and there), “time-shifters” (like now or tomorrow), and “thing-shifters” (like it and that).  What is a bit more complicated, and a central point here, is that much of our language behaves like shifters—that is, most words are promiscuously shifty when paired with context and even more shifty without context.  One more example will drive the point home.

Let us say a man named Donald utters the phrase: “I am going to the bank.”  We would know the person is going to engage in some mundane financial obligation—which often involves waiting in a line that takes so long that, while staring at the back of the person’s head of front of you, you could swear their hair has had enough time to noticeably, and actually grow.  We are pulling on our presupposed knowledge of bank experience and also that this essay is about a businessperson named Donald.  However, this Donald is actually within a mile of a river bank, and because it is a warm Saturday evening—the sun will be setting soon—and Donald is wearing too-big swimming trunks, oversized swimming goggles across his forehead, towel slung across the shoulder, we know the word bank has shifted meaning.  Did Donald say he was going to the “river bank”?  No.  Did he explicitly need to say the word “river?” No.  The word bank has behaved just like a “shifter”—a word that shifts when put into context.  Here comes the plot twist: Donald in this story was President Trump all along, and for whatever reason it becomes politically advantageous to claim that he was going to a meeting with several of his top associates at an actual Wall Street bank.  With almost predictable certainty, non-partisan news media will begin asking: What did Trump “really mean” by “bank?”  The only way to make a plausible case for Donald’s claim that he was going to a Wall Street bank is to radically detach the words from his freckled shoulders showing through his loosely fitting muscle shirt, from the sun-tan lotion in his hand and from the clumsily dragged mini cooler by his feet—an act of total decontextualization.   Once the news media conversation moves onto the terrain of denotational and definitional meaning—what words “really mean”—all of the context that helps us know what words mean rapidly fades.   Without a contextual anchor, words can mean practically anything.  Without context, what Trump “really meant” is unfalsifiable in each direction: the bank and/or the riverbank become likely possibilities.  Surely, a reputable, well researching media outlet such as CNN would be able to figure out what “bank” means in this example, right?  In Donald’s words: “Wrong!”  There are underlying ideologies that prevent “nonpartisan” organizations from doing so, which I turn to next.

                              

Checking the Facts – Creating the Facts

In Jane Hill’s (2000) contribution to work on language ideologies, she asserts that at a basic level politicians are expected to be a source of “information”—that is, politician’s words should reduce uncertainty and permit voters to make an “informed choice” at the ballot box.  These words (spoken or written) are expected to be verifiable—an ideological position that privileges the denotational function and downplays the indexical function of language (where those pesky “shifters” live).  The public expects a certain degree of consistency in the informational content of statements over time.  Trump’s often more-than-questionable claims have spurred an explosion of so-called “fact-checking” websites dedicated to verifying the truth-value in the words of politicians.  One popular “fact-checking” website is PolitiFact.com, which “rates the accuracy of claims by elected officials” on a “Truth-O-Meter” scale with units from “Pants on Fire [False],” “False,” “Mostly False,” “Half True,” “Mostly True,” and “True.”  The website claims to analyze immediate and historical context and wishes to hold people “accountable for their words.”  However, just as we expect politicians to speak “information,” PolitiFact expects Trump to speak in terms of verifiable information that is fact or non-fact, true or false, and will deeply research his claims and present a “ruling” accordingly.  Two PolitiFact examples should illustrate this process.

During an interview with ABC News on January 25, 2017, Trump asserted, “A poll just came out on my inauguration speech […] People loved it.  Loved and liked.”  PolitiFact ruled that this statement was “Mostly True.”  There are two parts presented in Trump’s assertion that are potentially verifiable: 1) a poll exists and 2) people “liked” his speech in that poll.  It is true that a poll exists, and PolitiFact presents the percentages in detail with 49% of those polled saying the speech was “excellent” or “good” in comparison to 39% believing the speech was “fair” or “poor” (Jacobson 2017).  Notice, however, the use of the person-shifter “people,” which can rapidly shift its denotational meaning. Even if Trump had said the opposite, “People thought my inauguration speech was poor,” it could have been “mostly true” because we are now speaking of the people who thought his speech was “poor.”  In another example, PolitiFact (Qui 2016) reviewed Trump’s August 1, 2016 statement in which he told a rally in Columbus Ohio, “November 8th, we’d better be careful, because that election is going to be rigged.”  PolitiFact rated this as “Pants on Fire” false.  When radically de- and recontextualized—that is, not taking into account that Trump is yelling these assertions at multiple campaign rallies to his excitable supporters and, crucially, then transcribing his words into printed form—these statements appear to be informative claims that can be proven true or false.  At a basic level, his “rigging” statement could just be an opinion.  But, more importantly, and for our purposes here, the word “rigging” can potentially shift in denotational meaning to refer to many different scales.  Is Trump referring to electoral college overruling the popular vote (a national scale), voter suppression laws designed to disenfranchise minority votes (state-level scale), gerrymandering (county-level scale), or, perhaps, the ill-defined “illegal” vote (individual-person scale)?  The point here is not to overturn Politifact rulings.  It is to highlight the tendency of news organizations to radically decontextualize and recontextualize Trump’s words through a “fact-checking” practice that foregrounds the denotative function, that is, attempts to prove or disprove the validity of information (or lack thereof) in order to present an analysis.  Through this process, Politifact creates factual claims so that they can be “checked.”  We can expand this kind of informational or denotative foregrounding to another communication medium: Trump’s Twitter account.

On March 4, 2017, in a rapid succession of Tweets, Trump accused former President Obama of allegedly conducting illegal surveillance during the Trump/Clinton election season. Trump presents the accusation as fact, claiming that he “[j]ust found out” (see Fig. 1). This kind of accusation from President Trump has its legal limits, which then required White House Press Secretary Sean Spicer to clarify what Trump “really meant.”  Spicer instead attacked “the media” for not paying attention to the quotation marks President Trump used around the phrase “wire tapps” and “wire tapping.”  According to Spicer, “[President Trump] said [wiretapping] very clearly, in quotes.  Wiretapping in quotes.”  Throughout Spicer’s statement, he employed the use of “air-quote” gestures with both hands to emphasize the words “in quotes.”  Indeed, President Trump did tweet quotation marks around the word wiretap.  In Trump’s third tweet he offers more literal detail, suggesting that Obama wiretapped his phones in Trump Tower.  Predictably, news organizations expect that these tweets have some verifiable information—after all, there seem to be some factual claims here, right? “Wrong!”  Remarkably, the Press Secretary faults “the media” for expecting there to be any literal information at all and even translates Trump’s words into a verifiable statement.  Spicer, moving “the media’s” analysis into a hyper-literal realm, follows up by saying, “He [Trump] doesn’t really think that President Obama went up and tapped his phone personally.” In the coming days, Trump’s pundits and supporters would take to the TV airwaves describing Trump’s tweets as having a metaphorical essence: wiretapping “really means” a more general culture of government surveillance under President Obama. There is some evidence to suggest here the Trump administration expects news organizations to attempt to verify his words—to analyze what appears to be explicit information or at least informative and verify its accuracy.  In this case, whether the “metaphor argument” is convincing or not, proving someone is or is not speaking metaphorically is already several steps removed from the original political issue.  Furthermore, metaphors themselves are not meant to be literal—they are purposefully shifty.  In this final example, I present the way CNN has helped legitimize the possibility that Trump’s promise to build a southern wall on the U.S.-Mexico border (and have Mexico pay for it) was actually a “metaphor” for border security.

Figure 1: Trump’s “Wiretap” Tweets

One year into his presidency, we have observed Trump’s withdrawal from TV interviews unless they are pre-taped and with a conservative (read: friendly) news interviewer.  Trump now leaves much of his handling of the media to his conservative pundits who are generally made up of “hard-right” political commentators, “hard-right” news and talk-show hosts, and other politicians who are presently in the good graces of Trump.  The interview affords a different set of ideological constraints and possibilities on non-partisan news media, however, the basic idea remains the same: gather, present, and verify information for the electorate.  This is done through a Question-Answer turn-taking format with the interviewer’s turn consisting of questions approximately 85% of the time (Clayman 2002: 104). In Clayman’s sociolinguistic work on the news interview in the US and UK, he describes the interviewer as managing “a ‘neutralistic’ stance toward the interviewees statements, positions, and opinions” (120).  This is primarily done in two ways: avoid assertions of opinions and avoid direct dis/agreement with interviewees.  This includes refraining from basic phatic cues like yeah, uh huh, or even an enthusiastic nodding that could be seen as an ideological alignment with interviewee.  Clayman describes exchanges as interactional “games” with moves and countermoves that help create the appearance of “neutrality.” Additionally, broadcasted interviews are viewed as “a central means for sustaining the sense that each citizen has the right to participate, be heard, and affect collective life” (Briggs 2007: 557).  For example, on CNN, an overly aggressive interviewer will most certainly be seen as impeding or limiting the right to “be heard,” an explicit break with producing “neutrality.”  Yet, producing a neutral stance has its problems when interviewees are not being truthful, or, as is the case frequently with Trump allies, overtly lying.             

In April 2017, the construction of the U.S.-Mexico border wall came under scrutiny when a leaked phone call transcript revealed President Trump imploring Mexican President Enrique Peña Nieto to stop publically criticizing the border wall.  On April 6th, Senator Ron Johnson (Republican, Wisconsin) came on CNN to redefine Trump’s campaign promise to build a “concrete” border wall as a metaphor.

CNN’s New Day aired April 6, 2017

Interviewer: Chris Cuomo

Interviewee: Ron Johnson (Republican, Wisconsin)

20        RJ        I’ve always thought the wall was a metaphor for securing the border.  And I

21                    think that it’s just been incredibly important that this president, finally, we have

22                    an administration that is committed to securing the border in whatever shape

23                    and form that takes[…]

[…]

40        CC       Alright, Senator Ron Johnson, [I] appreciate it, I’ve never heard the president

41                    refer to it as a metaphor, but you make a reasonable case here for why it should

42                    be that way. Thank you for being here on New Day as always.

Senator Ron Johnson, in a calm demeanor, asserts that he has “always thought” (line 20) the border wall was a metaphor that could take many forms, whether additional fencing, more border patrol agents, or technological upgrades.  This is after Trump has campaigned for months on the literalness of a concrete wall made with steel rebar, which included different estimations on the height (35-90 feet) as well as construction costs (4 to 12 billion dollars). What is troubling about this particular example is that there are likely hours of footage of Trump describing the wall’s materiality. Trump has defined, in no uncertain terms, what he meant by “border wall.”  Trump’s border wall is one of the few examples where clear, explicit denotational information exists.  It cannot be understated here: Trump has defined the materiality of the wall repeatedly—over and over again. While the interview was less than two minutes long, interviewer Chris Cuomo had enough time to support Johnson’s “metaphorical wall” argument calling it “reasonable” (line 40-42)—legitimizing the denotational shift from a concrete border wall to a metaphorical border wall—perhaps the most radical example of Trump-era shifty information to date.  In the coming months, there would be a steady flow of interviews and articles, from partisan and nonpartisan news organizations alike, discussing the likelihood of whether Trump was speaking metaphorically or literally.  Once again, the “metaphor argument” could only happen through a process of decontextualization and recontextualization that focuses on definitions of words.  This is made possible through the ideological production of “neutrality” that frames a focus on the definitions of words as “objective reporting.”

Closing Words: Trump Wins “Bigly”

This essay has focused on the way two so-called nonpartisan news organizations attempted to produce as stance of neutrality and objectivity by reporting on the verifiability of Trump’s words—that is, decontextualizing and recontextualizing Trump’s words so that the definitional or denotative function of language is foregrounded and made to appear as “information.”  “Fact-Checking” websites continue to be a popular source of TrumpTalk analysis and they continue to (re)frame and report Trump’s speech as “true” or “false” with little apparent awareness that this reframing is what makes analysis possible in the first place.  Undoubtedly, Twitter will continue to be a source of entertainment and mass confusion to audiences and news organizations alike.  The interview, however, offers particular affordances—both constraints and possibilities—that print media does not. It makes possible the production of shifty information in real-time, from one spoken utterance to the next.  Conservative news organizations, like Fox News, are extraordinarily effective at naturalizing newly interpreted shifty information—often, leaving Trump supporters “knowing what he meant the whole time,” even repeating the Trumpian mantra: “I know it, you know it, everybody knows it.”   On the other hand, there are notable efforts by left-leaning organizations at anchoring Trump’s words in context.   Perhaps most notably is the MSNBC news anchor Rachel Maddow whose production team regularly dedicates 20 minutes worth of uninterrupted contextualizing background information—often providing context from multiple interacting scales and angles buttressed by multiple sources and video clips of Trump’s words.  Highly effective, yet, ultimately “partisan” and there for lacks the legitimacy of “non-partisanship.”  In a similar position, comedy news programs such as HBO’s Jon Oliver lack the “objectivity” to be cited as “serious” news.  Yet, it is clear comedy producers must thoroughly contextualize the scene if they expect jokes to be successful and sometimes Oliver’s production team dedicates up to 30-minutes on a single Trump theme or joke.  Comedians are well aware of language’s indexical and poetic functions and necessarily rely on these functions to make words funny.  Therefore, it should not be surprising that comedy producers are particularly (and ironically) qualified to offer in-depth analysis of Trump’s words.  It is not simply that Trump says funny words—he does not—it is that his words take an absurd quality when thoroughly contextualized.  Yet, those comedy production techniques would be difficult to apply to a real-time interview where information is revealed and molded from one utterance to the next. 

Clayman (2002: 13-14) has described the broadcasting news interview as an “interactional game” being played between the interviewer and interviewee—both sides with a set of rules that govern “fair play.”  Each side takes turns, making interactional “moves” that guide the direction of the interview.  The interviewer is expected to ask questions and refrain from qualitative commentary or from exerting too much pressure on the interviewee to respond in a way that could foreground the motive of the interviewer—even if the motive is an “objective” effort to clarify information.  The way non-partisan media appears neutral is often by focusing on the words of the interviewee or by asking the interviewee to comment on the words of others.  In Trump related interviews, this amounts to describing what Trump “really means.”  As the interview game unfolds, the interviewer and interviewee often co-construct “definitions” of Trump’s words as we saw above in the “borderwall metaphor” example.  The core rules of Clayman’s interview game are still present today—15 years later—however, what is explicitly different in the Trump-era interview is that the interview game now has “winners” and “losers.”  This is at odds with ideological stances of “neutrality” and “objectivism” attempted by nonpartisan news organizations.  And, put simply, if you are not playing to win in the Trump-era, then, perhaps, you have already lost—and, losing is not a “neutral” stance.  The form that “objectivity” primarily takes in “nonpartisan” news is the practice of reporting speech and reporting texts like transcripts and tweets.  Through the search for “information” in Trump’s words it becomes necessary to decontextualize then recontextualize his words in a way that searches and creates verifiable facts.  This essay asserts that this practice, this very process performed on Trump’s words is not “objective,” but an ideologically saturated practice that has so far worked to Trump’s advantage.  In fact, transforming Trump’s words into “information” is the very practice that produces and legitimizes shifty information—and, with each successful shift, Trump wins “bigly.”  

Works Cited

Briggs, Charles L. 2007. “Anthropology, Interviewing, and Communicability in Contemporary Society.” Current Anthropology 48 (4): 551–80. doi:10.1146/annurev.anthro.34.081804.120618.

Clayman, Steve, and John Heritage. 2002. The News Interview: Journalists and Public Figures on the Air. Cambridge and New York: Cambridge University Press.

Goffman, Erving. 1981. Forms of Talk. Philadelphia: University of Pennsylvania Press.

Hill, Jane. 2000. “Read My Article: Ideological Complexity and the Overdetermination of Promising in American Presidential Politics.” In Regimes of Language: Ideologies, Polities, and Identities, edited by Paul V. Kroskrity, 259–91. Santa Fe: School of American Research Press.

Jacobson, Louis. 2017. “Donald Trump’s inaugural speech polled well, but not as well as predecessors.’”PolitiFact.com. http://www.politifact.com/truth-o-meter/statements/2017/jan/26/donald-trump/donald-trumps-inaugural-speech-polled-well-not-wel/.  Accessed 1 November 2017.

Silverstein, Michael. 1976. “Shifters, Linguistic Categories, and Cultural Description.” In Meaning in Anthropology, edited by Keith Basso and Henry Selby, 11–55. Albuquerque: University of New Mexico Press.

Silverstein, Michael. 2009. [1981] “The Limits of Awareness.” In Linguistic Anthropology: A Reader, edited by Alessandro Duranti. Sociolinguistic Working Paper. Austin: Wiley-Blackwell.

Qiu, Linda. 2016. “Donald Trump’s baseless claims about the election being ‘rigged.’” PolitiFact.com. http://www.politifact.com/truth-o-meter/statements/2016/aug/15/donald-trump/donald-trumps-baseless-claims-about-election-being/. Accessed 1 November 2017.

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