Distorting time to deny inevitability

The latest issue of Rhetoric Society Quarterly has its authors engaging with “untimely historiography,” which, as near as I can tell, is an attempt to complicate the notion of time as a one-way river of cause and effect. Most of the essays (I’ve read two and skimmed the others) seem to share a common distrust of grand narratives and a distaste for histories that look beyond the contingency of particular events. Cause and effect, linear time—these are human constructs that make sense of distort an otherwise irreducibly complex mess of events.

The chronological anxiety in these essays is of the sort recently addressed by Ted Underwood in Why Literary Periods Mattered. There is of course good reason to be skeptical about grand narratives and historical theories, so I’m sympathetic to much of what is said in these new essays, and I find value in taking a critical look at constructions of linearity in history. However, as genetics blogger Razib Khan notes, acknowledging the dangers of over-generalization presents us with “problems to be grappled with, not a ‘get out of jail’ card to be thrown at any attempts to construct a formal system of interpretation.” Khan’s post is aptly entitled “Human History is Both Contingent and Inevitable,” and I think this both/and worldview is intellectually useful. It makes room for the radical contingency argued for by Michelle Ballif and others without foreclosing on legitimate linear interpretations of history. Thinking about history as both contingent and inevitable leads us to ask where it’s one or the other, to disentangle where it’s more one than the other.

Not everyone would agree with my sentiment, to put it mildly. As an example, I’ll quote from Hans Kellner’s essay “Is History Ever Timely?”*, in which he recounts a talk given by Hayden White:

In 1967, Hayden White . . . journeyed to Colorado to deliver a talk at a conference on biology. At this conference he spoke on the topic “What is a Historical System?” in which he contrasted a historical system with a biological system. In effect, he said that biological—that is, genetic—systems are timely. By this he meant that one’s biological state had been determined in the past by genetic ancestral code. Today we would speak of DNA. But is this true of historical, cultural ancestry? Are we historically determined in the matter of who we are? Is our historical identity as fixed by the timeliness of time and genetic logic as our biological identity is? At that conference, White said, “no.”

A resounding answer, one that, I believe, many scholars in the humanities would echo. It also rejects my olive branch to both sides of the question. It implicitly denies the possibility that culture and history might exhibit large-scale patterns or processes due to the influence of biology, geography, demographics, economics, and so on.

Kellner continues with an example that White used to prove his point: the Christianization of Europe as a culturally created event that needn’t have occurred:

Cultural communities are constituted on the basis of a shared agreement about the choice of historical ancestors. There are times, however, when people lose faith in their chosen identities . . . The example White cited at the time was the crisis of the seventh and eighth centuries in Northern Europe, when a Romanized world saw that the source of their identity had been changed beyond recognition, and a new candidate for that identity had emerged in the teachings of Christian missionaries. As White put it, when the Germanic peoples of northern Europe decided that they were no longer the cultural descendants of ancient Romans or of pagan barbarians, and that their cultural ancestors were Palestinian Jews with whom they had no biological connection at all, a new culture was formed. Backwards. This did not need to happen. Just as the pin on which one sat might have never been noticed if the pain had not caused it to exist for us, so the “Christianization” might have never happened . . .

But is it true that Northern Europe switched identities and cultures as effortlessly as Kellner’s gloss implies? It seems to me a highly contested statement. The Holy Roman Empire was a hegemon among Europe’s warring monarchs and tribes for a time, and, as White describes, the Church Fathers went to great lengths to adopt for themselves and for Europe a foreign Jewish culture and history, but to suggest that the Scots, the Anglos, the Franks, and the Iberians stopped being Scots, Anglos, Franks, and Iberians just because they became Christian is a gross overstatement belied by the constant warfare and power-plays that constitute European history (you’d think White and Kellner would be more careful about hasty generalizations!). It’s like saying the Persians stopped being Persian when they were conquered by the Muslims. Culture runs deep, precisely, I think, because it is tied to and influenced by processes much more intransigent than individual human whim. I don’t believe culture is a costume ready to be changed in a generation or two, and any attempts to do so often result in backlashes or corrections. One might even argue that during the middle ages Europe was just waiting for its monarchs to re-assert their power over Rome so they could all go back to fighting one another again. And indeed they did.

Now, I’m sympathetic to the political sensibility from which I think all this emerges—the idea that if history is not inevitable then the future is, to some extent, in our hands, ready to be constructed in a more just and moral way. On the other hand, if the movement of history is inevitable, then humans can have no agency over their (often unjust) cultures and behaviors, no more agency than they have over their genetics. Such is the “Cormac McCarthy” view of the world, McCarthy having famously said that wishing the species could be “improved in some way . . . will make your life vacuous.” It is an antipathy to this view that brings out the poststructuralist and postmodern tendencies in these RSQ essays, whose authors deny inevitability to history by denying the linear shape of time altogether. Get rid of linear time and any notion of inevitability disappears with it.

I grew up watching wildlife documentaries, so I was inured from a young age to the McCarthy view. It probably didn’t help that I read Blood Meridian in tenth grade. Nevertheless, I try not to err in extremes, so although my default position on culture is determinism of all types—genetic, geographic, demographic, historical—I enjoy challenging and often replacing my default assumptions. I think those who err on the other side—no determinism of any type, history is always contingent—should likewise challenge their default assumption. Hopefully we can meet in the middle.

Hayden White asked:  Are we historically determined in the matter of who we are? Is our historical identity as fixed by the timeliness of time and genetic logic as our biological identity is? He answered no, but I think we should answer, Sometimes yes and sometimes no. It depends on what you’re talking about. The intellectual challenge is to figure out what is (or was) contingent and what is (or was) inevitable. Does history exhibit patterns and cycles? What are the large-scale processes which stand outside of but influence cultural expressions? Do certain cultural expressions change according to broadly identifiable patterns, while others exhibit no patterned changes whatsoever? How do irreducibly contingent moments interact with larger historical processes? Interesting questions, in my opinion, ones that the cliodynamicists are trying to answer mathematically. Will they be successful? Maybe, maybe not. But before the fact, I don’t think we should, to quote Khan again, “throw our hands up in the air and assume that all of history is a contingent darkness from which we can’t infer general patterns.”

 

*Kellner’s essay is a sensible discussion of the ways that texts, films, and images create connections across great gaps of time to re-figure the past in terms of the present. It’s an excellent piece, and I’m simply using these carefully extracted quotes as a foil.

Elliot Rodger’s Manifesto: Text Networks and Corpus Features

Analyzing manifestos is becoming a theme at this blog. Click here for Chris Dorner’s manifesto and here for the Unabomber manifesto.

Manifestos are interesting because they are the most deliberately written and deliberately personal of genres. It’s tenuous to make claims about a person’s psyche based on the linguistic features of his personal emails; it’s far less tenuous to make claims about a person’s psyche based on the linguistic features of his manifesto—especially one written right before he goes on a kill rampage. This one—“My Twisted World,” written by omega male Elliot Rodger—is 140 pages long, and is part manifesto, part autobiography.

I’ve made a lot of text networks over the years—of manifestos, of novels, of poems. Never before have I seen such a long text exhibit this kind of stark, binary division:

RodgersBetweennessCentrality

This network visualizes the nodes with the highest betweenness centrality. The lower, light blue cluster is Elliot’s domestic language; this is where you’ll find words like “friends”, “school,” “house,” et cetera . . . words describing his life in general. The higher, red cluster is Elliot’s sexually frustrated language; this is where you’ll find words like “girls,” “women,” “sex,” “experience,” “beautiful,” “never”  . . . words describing his relationships with (or lack thereof) the feminine half of our species.

It’s quite startling. Although this text is part manifesto and part autobiography, I wasn’t expecting such a clear division: the language Elliot uses to describe his sexually frustrated life is almost wholly severed from the language he uses to describe his life apart from the sex and the “girls” (Elliot uses “girls” far more frequently than he uses “women”—see below). It’s as though Elliot had completely compartmentalized his sexual frustration, and was keeping it at bay. Or trying to. I don’t know how this plays out in individual sections of the manifesto. Nor do I know what it says about Elliot’s mental health more generally. I’ve always believed that compartmentalizing frustrations is, contra popular advice, a rather healthy thing to do. I expected a very, very tortuous and conflicted network to emerge here, indicating that each aspect of Elliot’s life was dripping with sexual angst and misogyny. Not so, it turns out.

Here’s a brief “zoom” on each section:

RodgersDegreeCentralityDomestic

RodgersDegreeCentralityWomen

In the large, zoomed-out network—the first one in the post—notice that the most central nodes are “me” and “my.” I processed the text using AutoMap but decided to retain the pronouns, curious how the feminine, masculine, and personal pronouns would play out in the networks and the dispersion plots. Feminine, masculine, personal—not just pronouns in this particular text. And what emerges when the pronouns are retained is an obvious image of the Personal. Rodgers’ manifesto is brimming with self-reference:

RodgersPronouns

Take that with a grain of salt, of course. In making claims about any text with these methods, one should compare features with the features of general text corpora and with texts of a similar type. The Brown Corpus provides some perspective: “It” is the most frequent pronoun in that corpus; “I” is second; “me” is far down the list, past the third-person pronouns.

Here’s another narcissistic twist, found in the most frequent words in the text. Again,  pronouns have been retained. (Click to enlarge.)

RodgersFreqWords

“I” is the most frequent word in the entire text, coming before even the basic functional workhorses of the English language. The Brown Corpus once more provides perspective: “I” is the 11th most frequent word in that general corpus. Of course, as noted, there is an auto-biographic ethos to this manifesto, so it would be worth checking whether or not other auto-biographies bump “I” to the number one spot. Perhaps. But I would be surprised if “I,” “me,” and “my” all clustered in the top 10 in a typical auto-biography—a narcissistic genre by design, yet I imagine that self-aware authors attempt to balance the “I” with a pro-social dose of “thou.” Maybe I’m wrong. It would be worth checking.

More lexical dispersion plots . . .

Much more negation is seen below then is typically found in texts. According to Michael Halliday, most text corpora will exhibit 10% negative polarity and 90% positive polarity. Elliot’s manifesto, however, bursts with negation. Also notice, below, the constant references to “mother” and “father”—his parents are central characters. But not “mom” and “dad.” I’m from Southern California, born and raised, with social experience across the races and classes, but I’ve never heard a single English-only speaker refer to parents as “mother” and “father” instead of “mom” and “dad.” Was Elliot bilingual? Finally, note that Elliot prefers “girl/s” to “woman/en.”

RodgersGirlsGuys

RodgersMotherFather

RodgersNegation

RodgersSexEtc

Until I discover that auto-biographical texts always drip with personal pronouns, I would argue that Elliot’s manifesto is the product of an especially narcissistic personality. The boy couldn’t go two sentences without referencing himself in some way.

And what about the misogyny? He uses masculine pronouns as often as he uses feminine pronouns; he refers to his father as often as he refers to his mother—although, it is true, the references to mother become more frequent, relative to father, as Elliot pushes toward his misogynistic climax. Overall, however, the rhetorical energy in the text is not expended on females in particular. This is not an anti-woman screed from beginning to end. Also, recall, the preferred term is “girls,” not “women.” Elliot hated girls. Women—middle-aged, old, married, ensconced in careers, not apt to wear bikinis on the Santa Barbara beach—are hardly on Elliot’s radar. (This ageism also comes through in his YouTube videos.) Despite the “I hate all women” rhetorical flourishes at the very beginning and the very end of his manifesto, Elliot prefers to write about girls—young, blonde, unmarried, pre-career, in sororities, apt to wear bikinis on the Santa Barbara beach.

I noticed something similar in the Unabomber manifesto. Not about the girls. About the beginning and ending: what we remember most from that manifesto is its anti-PC bookends, even though the bulk of the manifesto devotes itself to very different subject matter. The quotes pulled from manifestos (including this one) and published by news outlets are a few subjective anecdotes, not the totality of the text .

Anyway. Pieces of writing that sally forth from such diseased individuals always call to mind what Kenneth Burke said about Mein Kampf:

[Hitler] was helpful enough to put his cards face up on the table, that we might examine his hands. Let us, then, for God’s sake, examine them.

 

Demographic distribution: Gender of citations in CCC, RSQ, and RR abstracts

This post follows up on my discussion of citation frequencies in abstracts in rhetoric and composition journals. To reiterate, a safe assumption to make is that citations in abstracts are “central” to the arguments presented and the research undertaken in the articles themselves; they are particularly informative about overall trends. The genre of the humanities article demands more citations than a core argument actually requires, so looking at citations in abstracts should control for that genre requirement, distilling down all citations to the most vital ones.

The journals: College Composition and Communication (CCC), Rhetoric Society Quarterly (RSQ), and Rhetoric Review (RR). The CCC abstracts run from February 2000 (51.3) to September 2011 (63.1), a total of 261 abstracts. The RSQ abstracts run from Winter 2000 (30.1) to Fall 2011 (41.5), a total of 220 abstracts. The RR abstracts run from 2002 (21.3) to 2011 (30.4), a total of 154 abstracts.

The previous post discussed the “long tail” distribution that emerged from the citation frequencies and what it means for disciplinary identity. This post presents information on the gender of the sources cited in the abstracts, then makes a few comments about demographic distributions in general.

There are 79 unique citations in the CCC abstracts; 159 unique citations in the RSQ abstracts; and 121 unique citations in the RR abstracts. (See previous post for .xls data files.) Here’s how the gender distribution falls: in CCC, 23 out of the 79 sources are female; in RSQ, 39 out of the 159 sources are female; in RR, 36 out of the 121 sources are female.

And here are graphs of the raw counts and of the percentages:

Abstract citations by gender (raw count)

Abstract citations by gender (raw count)

Abstract citations by gender (percentage)

Abstract citations by gender (percentage)

In Authoring a Discipline, Maureen Daly Goggin has shown that by 1990 total contributors to 9 of rhetoric and composition’s major journals—including the 3 analyzed here—had equalized to a nearly 50/50 split between males and females. I imagine this trend has continued into the new millennium, but it would be worthwhile to determine whether or not that’s the case.

What has not equalized, however, is the gender contribution in terms of citations. Odds are, counting all citations in the articles themselves would alleviate the large gap seen in the graphs above. But insofar as we accept that abstract citations represent the most vital sources in each journal, then an obvious gender gap still exists in CCC, RSQ, and RR citations.

In RSQ and RR, this gap, in part, likely has something to do with these journals’ tendencies to publish work on rhetorical history. I pointed this out in the last post: 27 (or 22%) of the RR citations are sources from the 17th century or earlier. 26 (or 16%) of RSQ citations are from the same period. Those numbers would grow if they included figures from the 18th and 19th centuries, as well. The reality is, most of these historical sources are male: Plato, Cicero, Aristotle, Quintilian, et cetera.

I have no ready explanation for why CCC citations should have as large a gender gap as the other journals’ citations, given that CCC builds most of its scholarship on sources from the middle part of the 20th century or later. If we look at the 102 most cited figures in CCC between 1987 and 2011 (Mueller, “Grasping”), we discover that 43/102 (42%) of the sources are female: a gender imbalance, but one not nearly as pronounced as the imbalance that surfaces in abstract citations. I’d be curious to see the gender distribution in Mueller’s entire data set. Is there a nearly 50/50 split between male and female sources across all citations in CCC between 1987 and 2011? If so, we could model the gender imbalance in this journal’s citations as an emergent feature: 50/50 across the entire data set; 58/42 in the most popular citations between 1987 and 2011; 71/29 in abstracts between 2000 and 2011. It’s unfortunate that CCC did not publish abstracts until the late 1990s, so that the dates of the abstracts and the articles could be uniform.

The question of demographic balance is one that spills a lot of digital ink. Just this morning, Scott Weingart visualized the gender (im)balance of Digital Humanities Conference attendees: about a 70/30 split that favors males. And Google recently released the demographic characteristics of its workforce: 30% of its employees are women; 17% of its technical employees are women. 60% of its employees are white; 30% of its employees are Asian (read: East Asian and Indian); and only 3% of its employees are Non-Asian Minorities.

I asked Scott why our default assumption should be uniform demographic distribution. When looking at statistical trends that emerge at large scales, we shouldn’t be surprised to discover that human populations cluster differently. At least, that’s my default assumption. The DH Conference draws more males, but then, an Early Childhood Education conference will draw more females. (I once attended a conference on speech and behavior therapy for autistic children; there were no more than three or four males amid about seventy females.) Or take a look at the National Association for the Education of Young Children. Although we often hear about the male-ness of executive boards, the NAEYC’s executive team is entirely female, and its 17-member governing  board boasts 13 females and only 4 males. Looking at all the Early Childhood Education associations and organizations in the country, what gender trends would we expect to find?

The first question to ask about demographic distribution in any particular population (like Google’s workforce or citations in abstracts) is this: What are the characteristics of the larger population from which this particular population is drawing? As long as rhetorical scholars continue to look at rhetorical history, where most of the figures are male, then we can continue to expect many citations in these historical journals to be male. (This may change, however, as more and more rhetorical historians re-discover the history of female oratory.) Or, in Google’s case, if we take the American population as the baseline, assuming a 50/50 gender split, then clearly there is a gender imbalance. But in terms of race and ethnicity, its white workforce is in fact under-represented. Raising the percentage of blacks and Hispanics at Google would mean firing a lot of the Chinese and Indians, unless we want to make whites more under-represented than they already are. (A fairer baseline population would be the percentage of working-age adults in America, or, better yet, the percentage of working-age adults with college degrees; however, those stats are much harder to come by. Total population is a decent but imperfect proxy.)

The point is that we do not always find particular populations boasting a uniform or near-uniform demographic distribution. Why is this? A complex question. Given the totality of the human population (or, more humbly, the totality of any total population in a given geographic area), why do we find the smaller population clusters clustering the way they do around different practices? Why are there more males in CCC citations? Why are there more males at the DH Conference? Why are East Asians and Indians so over-represented at Google? Why are there so few East Asians and Indians in the NFL and the NBA? That populations cluster differently around different practices seems to be a statistical fact. Is it also a future inevitability?

A possible explanation for the emergence of quotative “like” in American English

So Monica was like, “What are you doing here, Chandler?” and Chandler was like, “Uhh nothing” and then Monica was like, “Why are you here with Phoebe?” and Chandler was like, “I don’t know,” and Monica was like, “Whatever!”

Quotative “be like” probably gets on your nerves. Unfortunately for you, it spread like wildfire in the latter half of the 20th century and today is used by native and non-native speakers alike as often as they use traditional say-type quotatives. What is its structure, when did it arise, and why did it spread so quickly? This post offers a possible explanation, based on evidence dragged up from the depths of the Google Books Corpus. To appreciate that evidence, however, we need to start with some discussion of this quotative’s formal properties.

1

One interesting property of quotative “be like” is its ambiguous semantics. In some contexts, it is a stative predicate that denotes internal speech, i.e., thoughts reflexive of an attitude. In other contexts, it is an eventive predicate denoting an actual speech act. Sometimes, the denotation is ambiguous, as in (1):

(1) Monica was like, “Oh my God!”

. . . Did Monica literally say “Oh my God!” or did she just think or feel it?

Another interesting property of quotative “be like” is that it disallows indirect speech.

(2a) Monica was like, “I should go to the mall.”

(2b) *Monica was like that she should go to the mall.

(2c) *Monica was like she should go to the mall

Quotative say of course allows indirect speech:

(3a) Monica said, “I should go to the mall.”

(3b) Monica said that she should go to the mall.

(3c) Monica said she should go to the mall.

Haddican et al. (2012) recognize that quotative “be like” is immune to indirect speech due to its mimetic implicature. (2b) cannot be allowed because quotative “be like” always means something more along these lines:

(4) Monica was like: QUOTE

Given the implied mimesis of this construction, it makes no sense, as in (2b) and (2c), to add an overt complementizer and to change person/tense to produce an indirect, third person report. This property is shared by all uses of quotative “be like,” whether in their stative or eventive readings.

But there’s more to it than a mimetic implicature. Schourup (1982) points out that quotative “go” also shares this mimetic property (although he does not frame it as such). As expected of a quotative with a mimetic implicature, quotative “go” likewise does not allow an indirect speech interpretation via addition of an overt complementizer and shifts in person/tense:

(5a) Monica goes, “I should go to the mall.”

(5b) *Monica goes that she should go to the mall.

Why should these innovative quotatives be so immune to indirect speech and so committed to direct quote marking? Schourup suggests that quotative “go” (and, by extension, quotative “be like”) arose precisely to meet English’s need for a mimetic, unambiguous direct quotation marker. Prior to the occurrence of these new quotatives, English lacked such a marker. Consider (6a) and (6b) below:

(6a) When I talked to him yesterday, Chandler said that you should go to the doctor.

(6b) When I talked to him yesterday, Chandler said you should go to the doctor.

There is no ambiguity in (6a). The speaker of this utterance clearly intends to convey to his interlocutor that Chandler said the interlocutor should go to the doctor. (6b), however, introduces ambiguity. The utterance in (6b) can be interpreted in two ways: a) Chandler said the speaker of the utterance (i.e., I) should go to the doctor; b) Chandler said the speaker’s interlocutor (i.e., you) should go to the doctor. With orthographic conventions, of course, this ambiguity disappears:

(6c) When I talked to him yesterday, Chandler said, “You should go to the doctor.” (So I went.)

However, unlike other languages, spoken English has no “quoting” conventions—it has no direct quote markers for unmarked speech. It is unclear if (6b) is a true quotative or merely an indirect report on speech with a null complementizer.

QuotvsInt

We can imagine speakers needing to clarify this ambiguity:

JOEY: When I talked to him yesterday, Chandler said you should go to the doctor.

ROSS: Wait, he said I should go or you should go?

This ambiguity arises with say-type verbs whenever the complementizer that is omitted. It is traditionally understood that English differentiates between direct quotatives and indirectly reported speech via shifts in person and/or tense. However, the overt complemetizer is really the central feature of this differentiation. Without an overt complementizer, it is never entirely clear if the embedded clause is a direct quote or an indirect report of speech. Here’s another example:

(7) JOEY: Chandler said I will be responsible for the cat’s funeral.

Without the aid of quote marks, we cannot know whether Chandler or Joey is responsible for the cat’s funeral, even though the embedded clause contains a shift in both person and tense. Of course, if Joey wants to convey that Joey himself will be responsible for the cat’s funeral, he can simply add the overt complementizer: “Chandler said that I will be responsible . . .” However, if Joey wants to convey that Chandler has decided to be responsible, Joey has no way to convey it unambiguously with say-type verbs. He must resort to an indirect speech construction with an overt complementizer. Alternatively, he can resort to non-structural signals: a short pause, a change in intonation, or a mimicry of Chandler’s voice. Or he must abandon say-type constructions altogether and convey his meaning some other way.

Quotative “go” and quotative “be like” solve this ambiguity. These innovative quotatives always signal that the following clause is mimetic, a direct quote of speech or thought. Many languages—Russian, Japanese, Georgian, Ancient Greek, to name just a few— have overt markers to ensure that interior clauses are understood as being directly quoted material, whether or not those quoted clauses contain grammatical shifts (though of course they often do). The quotatives “go” and “be like” serve this same purpose. They are structural, unambiguous markers for direct speech, which is why one cannot use them for indirect speech, and which is also why they have spread so widely and quickly: they have met a real need in the language.

Quotative “go,” however, is attested long before quotative “be like.” The Oxford English Dictionary puts the earliest usage in the early 19th century, initially as a way to mime sounds people made, then later as a way to report on actual speech. Here’s an example from Dickens’ Pickwick Papers:

DickensPickwick

So, although I have said that both quotative “be like” and quotative “go” met a need in English for an unambiguous direct quotation marker, it was “go” that in fact met the need first, by at least a century. This historical fact leads me to suspect that quotative “be like” met a slightly different need: while quotative “go” became a direct quotation marker for speech acts, quotative “be like” became a direct quotation marker for thoughts. As Haddican et al. rightly note, an innovative feature of these quotatives is that they allow direct quotes to be descriptors of states. In other words, the directly marked quotes of “go” denote external speech; the directly marked quotes of “be like” primarily denote internal speech, i.e., thoughts or attitudes. I believe this hypothesis is supported by the earliest uses of quotative “be like,” to which we now turn:

2

Today, young native and non-native speakers of English frequently use “like” as a versatile discourse marker or interjection in addition to its use as a quotative (D’Arcy 2005). D’Arcy provides two extreme examples of discourse marker “like.” Both are taken from a large corpus of spoken English:

(8) I love Carrie. LIKE, Carrie’s LIKE a little LIKE out-of-it but LIKE she’s the funniest, LIKE she’s a space-cadet.      Anyways, so she’s LIKE taking shots, she’s LIKE talking away to me, and she’s LIKE, “What’s wrong with you?”

(9) Well you just cut out LIKE a girl figure and a boy figure and then you’d cut out LIKE a dress or a skirt or a coat, and LIKE you’d colour it.

This usage does not become noticeable in available corpora until the 1980s, so nearly all papers that I have read assume that discourse marker “like” and qutoative “be like” arose more or less in tandem during the 1970s, becoming common by the 1980s. However, using the Google Books Corpus, I was able to find an early use of “like” that presages quotative “be like.” This early use also seems to set the stage for the versatile discursive uses of “like” seen in (8) and (9). This early use is the expression, “like wow.” It seems to have arisen during the 1950s (though perhaps earlier) in the early rock n’roll scenes in the Southern United States. Here are some examples.

The first is from 1957: a line from a rock n roll song by Tommy Sands:

(10) When you walk down the street, my heart skips a beat—man, like wow!

The second is from a 1960 issue of Business Education World:

(11) Like, wow! I’m taking a real cool course called general business. It’s the most.

BusinessEducationWorld

The third is from a novel called The Fugitive Pigeon, published in 1965:

(12) But all of a sudden you’re like wow, you know what I mean?

And by 1971, we have a full example of quotative “be like,”— note that this early occurrence uses an expletive as the subject:

(13) But to me it was like, “Oh, why can’t you say, ‘Gee that’s wonderful . . .’”

LifeMagazine1971

These early uses of “like wow” in (10) and (11) denote a stative feeling or attitude rather than any kind of eventive speech act. This is especially clear in (11), where the expression is a direct response to a question about how the speaker is feeling. The quotative in (13) likewise seems to be a stative predicate rather than an eventive one. In fact, in nearly all of the earliest 1uses of quotative “be like”—from the 1970s and early 1980s, as reported in the Google Books Corpus—the intention is to denote a feeling or attitude, not a direct quote of a speech act. Such eventive predications don’t become common until the 1990s and 2000s.

“Like wow,” then, arose in 1950s slang as a stative description. However, the sentence in (14) below suggests that wow was not interpreted as a structurally independent interjection but as an adjective. This is from a 1960 edition of Road and Track magazine:

(14) Man, that crate would look like wow with a Merc grille.

RoadTrack

It is possible that like is an adverb here, but in my estimation it is most likely still a garden variety manner preposition that has innovatively selected for a bare adjective. Typically, like as a preposition only selects NPs as its complement. However, with the advent of “like wow,” it loosened its selection requirements and began to select for adjectives as well. And not just adjectives. The bottom line in this advertisement from Billboard magazine in May 1960 demonstrates that it also began to select for adverbs:

BillboardLikeWowAd

Apparently, in the 1950s and early 1960s, like became a popular and versatile manner preposition. Once like loosened its requirements to select AP complements, it’s easy to see how it could start selecting quotes, thus becoming a new direct quote marker (like narrative “go”); and given the stative denotation of the original phrase “like wow,” it’s also easy to see why stative to be would become the verbal element in this quotative rather than a lexical verb like act or go. Indeed, it appears that the first uses of quotative “be like” were entirely restricted to the phrase “like wow,” ensuring that subsequent uses would likewise have stative readings. (The ad above also shows how easy it would be for like to become an all-around discourse marker once it began to select for a wider range of phrases.)

So, based on the timeline of evidence in the corpus, I posit the following evolution:

LikeEvolution

The emergence of quotative “like”

I follow Haddican et al. in assuming that like in quotative “be like” is still a manner preposition. However, while they assume the preposition did not undergo any change, I argue that like became more versatile in its selection restrictions. This versatility allowed it first to select APs, then to select quotes. Initially, this quotative construction was just an extension of the phrase “like wow,” but it soon began to select any quoted material. And from the beginning, this quotative possessed two features: a) it had an obvious mimetic implicature, ensuring that it would be a direct quote marker, similar to narrative “go”; and b) it had a stative denotation, due to the stative dentation of the original phrase “like wow,” ensuring that the directly marked quotes were reflective of internal speech, i.e., thoughts or attitudes.

A corpus analysis by Buchstaller (2001) has shown that, even today, quotative “go” is much more likely than quotative “be like” to frame “real, occurring speech” (pp. 10); in other words, “be like” continues to be used more often as a stative rather than eventive predicate. As I mentioned earlier, Haddican et al. are correct that one innovative aspect of quotative “be like” is that quotes are now able to be descriptors of states; however, I believe they overstate the eventive vs. stative ambiguity that arises in these quotatives. Most of the time, in real contexts, they are as unambiguously stative as they are unambiguously mimetic of the state. Haddican et al. themselves note that even these eventive readings are open to clarification. Asking whether or not someone “literally” said something sounds much odder following a say-type quotative than a “be like” quotative with a putatively eventive reading.

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Nevertheless, as I showed at the very beginning of this post, there are instances where quotative “be like” seems to denote an eventive speech act. Linguistically, this is odder than it sounds at first. A single verbal construction—like quotative “be like”—should not have a stative and eventive reading. This ambiguity can only happen for two reasons: either there is some special semantic function at work in this construction, or there are in fact two separate quotative constructions, each with its own syntactic structures.

It is tempting to see a correlation between this ambiguity and the putative ambiguity between stative be and eventive be, also known as the be of activity. Consider the following sentences:

(15) Joey was silly.

(16) Rachel asked Joey to be silly.

Both forms of be select an adjective; however, (16), unlike (15), can be taken to mean that Joey performed some silly action. In other words, the small clause in (16) seems to be an eventive predication, not a stative one. It has been argued (Parsons 1990) that this eventive be is not the usual copular form but a completely different verb that means something like “to act”—in other words, English to be is actually a homophonous pair of verbs, similar to auxiliary have and possessive have. Perhaps this lexical ambiguity in be is related to the eventive vs. stative ambiguity in quotative “be like.” The stative reading arises when stative be is involved; the eventive reading arises when the eventive, lexical be is involved.

Haddican et al. argue against this line of thought. Diachronically, we know that quotative “be like” has arisen rapidly in many varieties of English, and that in all of these varieties, the semantics are ambiguous. But if there are in fact two be verbs that underwent this quotative innovation, then we would need to posit two unrelated channels of change: one in which like+QUOTE became a possible complement of stative be and one in which like+QUOTE became a possible complement of eventive be.

This is actually a problematic claim, given that, presumably, stative and eventive be have different structures. The former undergoes its typical V to T movement in English; the latter, given its eventive semantics, would be expected to remain in the VP like any other lexical verb. These underlying structures would demand that we devise different processes by which qutoative “be like” arose. However, given the rapidity with which it did in fact arise, it is more probable that it arose via a single process—and the inevitable conclusion is that there is a single, stative verb to be that underwent the process. This conclusion is also verified by the auxiliary-like behavior of be in quotatives involving adverbs and questions:

(17) Ross was totally like, “I don’t care!”

(18) Was Ross like, “I don’t care”?

Although the ambiguous stative vs. eventive reading still occurs here, (17) exhibits raising above AdvP, and (18) exhibits subject-aux inversion. In other words, be in these quotatives behaves like an ordinary copular auxiliary, not a lexical verb. We therefore should not posit a separate, eventive be verb. We need another way to explain the semantic ambiguity of these quotatives.

Haddican et al. explain this ambiguity with Davidsonian semantics. Briefly stated, they argue that there is a single stative be verb—both in these qutoative constructions and in English more generally. However, be has a semantic LOCALE function that, in certain contexts, can localize the state in a short-term event, and this localization of an event can force an agentive role onto the subject, even when an adjective has been selected by be. So, in a sentence such as (19), be will have a denotation as in (20):

(19) Joey is being silly.

(20) [[be]] = λSλeλx. ∃s ϵS [e = LOCALE(s) & ARGUMENT(x,e)]

(20) takes a property of state S and localizes it into an event (a moment in which Joey was silly); in the right context, it is not a great leap to coerce this experiencer event into an agentive one. The application of these semantics to “(be) like” quotatives is straightforward:

In the state reading, be like is simply a stage level use of the copula, localised to the event in which the subject of be exhibited the relevant behaviour. The eventive reading arises when the event mapped to is an agentive one, where the most plausible event of an agent behaving in a quotative manner is the relevant speech act. (Haddical et al. 2012 pp. 85)

In short, the ambiguity between stative and eventive “be like” arises from a semantic property that forces certain “states of being” to be processed as localized events whereby the experiencer of the event takes on an agentive role. In certain quotative contexts, the embedded quote is processed as an event, and the subject is understood as having caused that event, i.e, as actually saying something rather than just experiencing an attitude.

I agree that it would be better not to posit two homophonous verbs (stative be vs. be of activity) to account for the ambiguous stative vs. eventive denotations of quotative “be like.” Doing so requires two separate analyses and two separate channels of diffusion, which seems unlikely given the rapidity with which this quotative did in fact spread across many varieties of English. However, Haddican et. al’s application of Davidsonian semantics to explain the ambiguous readings runs into a problem in sentences like (21) below, as well as in the earlier example in (13):

(21) It was like, “Oh Mom, Can I film a movie in the house, it won’t be any problem at all.”

This is clearly an eventive predication of quotative “be like.” But instead of an agentive subject we have expletive it. Recall that Haddican et. al’s analysis relies on the notion that stative be has a LOCALE function that locates the state into a temporary moment or event. This localization can coerce an experiencer subject into the role of an agentive subject when the most likely reading (as above) suggests that the temporary event was an actual speech act. As Haddican et al. say themselves, “this event assigns an agentive role to the subject” (pp. 85). However, by definition, the expletive in (21) receives no theta role and can therefore be neither the experiencer of a state nor the agent of an event. And yet (21) clearly denotes an eventive reading: the speaker actually spoke the words, or something like them.

The fact that “be like” quotatives can take an eventive (or even a stative) reading when an expletive surfaces in spec-TP suggests that Davidsonian semantics do not explain the ambiguous eventive vs. stative readings associated with these quotatives. (The fact that “be like” quotatives exhibit both experiencer subjects and expletive subjects also suggests that the quote CP is the only obligatory argument assigned by “be like.”)

The only alternative seems to be that there are in fact two homophonous be verbs, and quotative “be like” makes use of both. Maybe this isn’t such a big deal. If I’m right about the diachronic process by which quotative “be like” arose, then we can at least see a two-step process: quotative “be like” was solely a stative predicate in its early use and for most of its early history; only later did it begin to be used as an eventive predicate. And if there are in fact two be verbs, the eventive sounds exactly like the stative and is in fact much rarer than the stative, so I suppose one can see how these facts laid the groundwork for the eventual use of stative “be like” as an eventive predicate.

Lying with Data Visualizations: Is it Misleading to Truncate the Y-Axis?

Making the rounds on Twitter today is a post by Ravi Parikh entitled “How to lie with data visualization.” It falls neatly into the “how to lie with statistics” genre because data visualization is nothing more than the visual representation of numerical information.

At least one graph provided by Parikh does seem like a deliberate attempt to obfuscate information–i.e., to lie:

y-axis2

Inverting the y-axis so that zero starts at the top is very bad form, as Parikh rightly notes. It is especially bad form given that this graph delivers information about a politically sensitive subject (firearm homicides before and after the enacting of Stand Your Ground legislation).

Other graphs Parikh provides don’t seem like deliberate obfuscations so much as exercises in stupidity:

y-axis3

Pie charts whose divisions are broken down by % need to add up to 100%. No one in Fox Chicago’s newsroom knows how to add. WTF Visualizations—a great site—provides many examples of pie charts like this one.

So, yes, data visualizations can be deliberately misleading; they can be carelessly designed and therefore uninformative. These are problems with visualization proper, and may or may not reflect problems with the numerical data itself or the methods used to collect the data.

However, one of Parikh’s “visual lies” is more complicated: the truncated y-axis:

y-axis1

About these graphs, Parikh writes the following;

One of the easiest ways to misrepresent your data is by messing with the y-axis of a bar graph, line graph, or scatter plot. In most cases, the y-axis ranges from 0 to a maximum value that encompasses the range of the data. However, sometimes we change the range to better highlight the differences. Taken to an extreme, this technique can make differences in data seem much larger than they are.

Truncating the y-axis “can make differences in data seem much larger than they are.” Whether or not differences in data are large or small, however, depends entirely on the context of the data. We can’t know, one way or the other, if a difference of .001% is a major or insignificant difference unless we have some knowledge of the field for which that statistic was compiled.

Take the Bush Tax Cut graph above. This graph visualizes a tax raise for those in the top bracket, from a 35% rate to a 39.6% rate. This difference is put into a graph with a y-axis that extends from 34 – 42%, which makes the difference seem quite significant. However, if we put this difference into a graph with a y-axis that extends from 0 – 40%—the range of income tax rates—the difference seems much less significant:

y-axis4

So which graph is more accurate? The one with a truncated y-axis or the one without it? The one in which the percentage difference seems significant or the one in which it seems insignificant?

Here’s where context-specific knowledge becomes vital. What is actually being measured here? Taxes on income. Is a 35% tax on income really that much greater than a 39.6% tax? According to the current U.S. tax code, this highest bracket affects individual earnings over $400,000/year and, for  married couples, earnings over $450,000/year. Let’s go with the single rate. Let’s say someone makes $800,000 per year in income, meaning that $400,000 of that income will be taxed at the highest rate:

35% of 400,000 = 0.35(400,000) = 140,000

39.6% of 400,000 = 0.396(400,000) = 158,400

158,400 – 140,000 = 18,400

So, in real numbers, not percent, the tax rate hike will equal $18,400 to someone making 800k each year. It would equal more $$$ for those earning over a million. So, the question posed a moment ago (which graph is more accurate?) can also be posed in the following way: is an extra eighteen grand lost annually to taxes a significant or insignificant amount?

And this of course is a subjective question. Ravi Parikh thinks it’s not a significant difference, which is why he used the truncated graph as an example in a post titled “How to lie with data visualization.” (And as a graduate student, my response is also, “Boo-freaking-hoo.”) However, imagine a wealthy couple, owners of a successful car dealership, being taxed at this rate (based on a combined income of ~800k). They have four kids. Over 18 years, the money lost to this tax raise will equal what could have been college tuition for two of their kids. I believe they would think the difference between 35% and 39.6% is significant. (Note that the “semi-rich” favor Republicans, while the super rich, the 1%, favor Democrats.)

What about the baseball graph? It shows a pitcher’s average knuckleball speed from one year to the next. When measuring pitch speed, how significant is the difference between 77.3 mph and 75.3 mph? Is the truncated y-axis making a minor change more significant than it really is? As averages across an entire season, a drop in 2 mph does seem pretty significant to me. If Dickey were a fastball pitcher, averaging between 92 mph and 90 mph would mean fewer pitches under 90mph, which could lead to a higher ERA, fewer starts, and a truncated career. For young pitchers being scouted, the difference between an 84 mph pitch and an 86 mph pitch can apparently mean the difference between getting signed and not getting signed. Granted, there are very few knuckleballers in baseball, so whether or not this average difference is significant in the context of the knuckleball is difficult to ascertain. However, in the context of baseball more generally, a 2 mph average decline in pitch speed is worth visualizing as a notable decline.

So, do truncated y-axes qualify as the same sort of data-viz problem as pie charts that don’t add up to 100%? It depends on the context. And there are plenty of contexts in which tiny differences are in fact significant. In these contexts, not truncating the y-axis would mean creating a misleading visualization.

Distant Reading and the “Evolution” Metaphor

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Are there any corpora that purposefully avoid “diachronicity”? There are corpora that possess no meta-data about publication dates and whose texts are therefore organized by some other scheme—for example, the IMDB movie review corpus, which is organized according to positive/negative polarity; its texts, as far as I know, are not arranged chronologically or coded for time in any way. And there are cases where time-related data are not available, easily or at all. But have any corpora been compiled with dates—the time element—purposefully elided? Is time ever left out of a corpus because that information might be considered “noise” to researchers?

Maybe in rare situations. But for most corpora whose texts span any length of time greater than a year, the texts are, if possible, arranged chronologically or somehow tagged with date information. In this universe, time flows in one direction, so assembling hundreds or thousands of texts with meta-data related to their dates of publication means the resulting corpus will possess an inherent diachronicity whether we want it to or not. We can re-arrange the corpus for machine-learning purposes, but the “time stamp” is always there, ready to be explored. Who wouldn’t want to explore it?

If we have a lot of texts—any data, really—that span a great length of time, and if we look at features in those data across the time span, what do we end up studying? In nearly all cases, we end up studying patterns of formal change and transformation across spans of time. The “evolution” metaphor suggests itself immediately. Be honest, now, you were thinking about it the minute you compiled the corpus.

One can, of course, use “evolution” as a general synonym for change. This is probably the case for Thomas Miller’s The Evolution of College English and for many other studies whose data extend only to a limited number of representative sources. However, when it comes to distant readings, the word becomes much more tempting. The trees of Moretti’s Graphs, Maps, Trees are explicitly evolutionary:

For Darwin, ‘divergence of character’ interacts throughout history with ‘natural selection and extinction': as variations grow apart from each other, selection intervenes, allowing only a few to survive. In a seminar a few years ago, I addressed the analogous problem of literary survival, using as a test case the early stages of British detective fiction . . . (70-71)

The same book ends with an afterword by geneticist Alberto Piazza (who worked with Luigi Luca Cavalli-Sforza on The History and Geography of Human Genes). Piazza writes:

[Moretti's writings] struck me by their ambition to tell the ‘stories’ of literary structures, or the evolution over time and space of cultural traits considered not in their singularity, but their complexity. An evolution, in other words, ‘viewed from afar’, analogous at least in certain respects to that which I have taught and practiced in my study of genetics. (95)

Analogous at least in certain respects . . . For Moretti and Piazza, literary evolution is not just a synonym for change in literature. Biological evolution becomes a guiding metaphor (not perfect, by any means) for the processes of formal change analyzed by Moretti. Piazza continues:

The student of biological evolution is especially interested in the root of a [phylogenetic] tree (the time it originated). . . . The student of literary evolution, on the other hand, is interested not so much in the root of the tree (because it is situated in a known historical epoch) as in its trajectory, or metamorphoses. This is an interest much closer to the study of the evolution of a gene, the particular nature of whose mutations, and the filter operated by natural selection, one wants to understand . . . (112-113)

Obviously, for Piazza, Moretti’s study of changes to and migrations of literary form in time and space evokes the processes and mechanisms of biological evolution—there’s not a one-to-one correspondence, of course, and Piazza points this out at length, but the similarities are evocative enough that he, a population geneticist, felt confident publishing his thoughts on the subject.

In Distant Reading, Moretti has more recently acknowledged that the intense data collection and quantitative analysis that has marked work at Stanford’s Literary Lab must at some point heed “the need for a theoretical framework” (122). Regarding that framework, he writes:

The results of the [quantitative] exploration are finally beginning to settle, and the un-theoretical interlude is ending; in fact, a desire for a general theory of the new literary archive is slowly emerging in the world of digital humanities. It is on this new empirical terrain that the next encounter of evolutionary theory and historical materialism is likely to take place. (122)

In Macroanalysis, Matthew Jockers also acknowledges (and resists) the temptation to initiate an encounter between evolutionary theory and the quantitative, diachronic data compiled in his book:

. . . the presence of recurring themes and recurring habits of style inevitably leads us to ask the more difficult questions about influence and about whether these are links in a systematic chain or just arbitrary, coincidental anomalies in a disorganized and chaotic world of authorial creativity, intertextuality, and bidirectional dialogics . . .

“Evolution” leaps to mind as a possible explanation. Information and ideas do behave in a ways that seem evolutionary. Nevertheless, I prefer to avoid the word evolution: books are not organisms; they do not breed. The metaphor for this process breaks down quickly, and so I do better to insert myself into the safer, though perhaps more complex, tradition of literary “influence” . . . (155)

And in the last chapter to Why Literary Periods Mattered, Ted Underwood does not mention evolution at all but there is clearly an evolutionary connotation to the terms he uses to describe digital humanities’ influence on literary scholars’ conception of history:

. . . digital and quantitative methods are a valuable addition to literary study . . . because their ability to represent gradual, macroscopic change brings a healthy theoretical diversity to literary historicism . . .

. . . we need to let quantitative methods do what they do best: map broad patterns and trace gradients of change. (159, 170)

Underwood also discusses “trac[ing] processes of change” (160) and “causal continuity” (161). The entire thrust of Underwood’s argument, in fact, is that distant or quantitative readings of literature will force scholars to stop reading literary history as a series of discrete periods or sharp cultural “turns” and to view it instead as a process of gradual change in response to extra-literary forces—“Romanticism” didn’t just become “Naturalism” any more than homo erectus one decade decided to become homo sapiens.

Tracing processes of gradual, macroscopic change . . . if that doesn’t invoke evolutionary theory, I don’t know what does. Underwood doesn’t even need to use the word.

Moretti, Jockers, and Underwood are three big names in digital humanities who have recognized, either explicitly or implicitly, that distant reading puts us face to face with cultural transformation on a large, diachronic scale. Anyone working with DH methods has likely recognized the same thing. Like I said, be honest: you were already thinking about this before you learned to topic model or use the NLTK.

 

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Human culture changes—its artifacts, its forms. This is not up for debate. Even if we think human history is a series of variations on a theme, the mutability of cultural form remains undeniable, even more undeniable than the mutability of biological form. Distant reading, done cautiously, gives us a macro-scale, quantitative view of that change, a view simply not possible to achieve at the scale of individual texts or artifacts. Given the fact of cultural transformation, then, and DH’s potential to visualize it, to quantify aspects of it, one of two positions must be taken.

1. The diachronic patterns we discover in our distant readings are, to use Jockers’ words, “just arbitrary, coincidental anomalies in a disorganized and chaotic world of authorial creativity, intertextuality, and bidirectional dialogics.” Theorizing the patterns is a fool’s errand.

2. The diachronic patterns we discover are not arbitrary or random. Theorizing the patterns is a worthwhile activity.

Either we believe that there are processes guiding cultural change (or, at least, that it’s worthwhile to discover whether or not there are such processes) or we assume a priori that no such processes exist. (A third position, I suppose, is to believe that such processes exist but we can never know them because they are too complex.) We can all decide differently. But those who adopt the first position should kindly leave the others to their work. In my view, certain criticisms of distant reading amount to an admonition that “What you’re trying to do just can’t be done.” We’ll see.

 

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When we decide to theorize data from distant readings, what are we theorizing? Moretti, Jockers, and Underwood each provide a similar answer: we are theorizing changes to a cultural form over time and, in some instances, space. Certain questions present themselves immediately: Are the changes novel and divergent, or are they repeating and reticulating? Is the change continuous and gradual, or are there moments of punctuated equilibrium? How do we determine causation? Are purely internal mechanisms at work, or also external dynamics? A complex interplay of both internal mechanisms and external dynamics? How do we reduce data further or add layers of them to untangle the vectors of causation?

To me, all of this sounds purely evolutionary. Even talking about gradual vs. quick change is a discussion taken right out of Darwinian theory.

But we needn’t adopt the metaphor explicitly if we are troubled that it breaks down at certain points. Alex Reid writes:

Matthew Jockers remarks following his own digital-humanistic investigation, “Evolution is the word I am drawn to, and it is a word that I must ultimately eschew. Although my little corpus appears to behave in an evolutionary manner, surely it cannot be as flawlessly rule bound and elegant as evolution” (171). As he notes elsewhere, evolution is a limited metaphor for literary production because “books are not organisms; they do not breed.” He turns instead to the more familiar concept of “influence” . . . Certainly there is no reason to expect that books would “breed” in the same way biological organisms do (even though those organisms reproduce via a rich variety of means). [However], if literary production were imagined to be undertaken through a network of compositional and cognitive agents, then such productions would not be limited to the capacity of a human to be influenced. Jockers may be right that “evolution” is not the most felicitous term, primarily because of its connection to biological reproduction, but an evolutionary-type process, a process as “natural” as it is “cultural,” as “nonhuman” as it is “human,” may exist.

An “evolutionary-type” process of culture is what we’re after, one that is not necessarily reliant on human agency alone. Will it end up being “flawlessly rule bound and elegant as evolution”? First, I think Jockers seriously over-estimates the “flawless” nature of evolutionary theory and population genetics. If the theory of evolution is so flawless and elegant, and all the science settled, what do biologists and geneticists do all day? Here’s a recent statement from the NSF:

Understanding the tree of life has been a goal of evolutionary biologists since the time of Darwin. During the past decade, unprecedented gains in gathering and analyzing phylogenetic data have demonstrated increasingly complex genealogical patterns.

. . . . Our current knowledge of processes such as hybridization, endosymbiosis and lateral gene transfer makes clear that the evolutionary history of life on Earth cannot accurately be depicted as a single, typological, bifurcating tree.

Moretti, it turns out, needn’t worry so much about the fact that cultural evolution reticulates. And Jockers needn’t assume that biological evolution is elegantly settled stuff.

Secondly, as Reid argues, we needn’t hope to discover a system of influence and cultural change that can be reduced to equations. We probably won’t find any such thing. However, within all the textual data, we can optimistically hope to find regularities, patterns that can be used to make predictions about what might be found elsewhere, patterns that might connect without casuistic contrivance to theories from the sciences. Here’s an example, one I’ve used several times on this blog: Derek Mueller’s distant reading of the journal College Composition and Communication. Mueller used article citations as his object of analysis. When he counted and graphed a quarter century of citations in the journal, he discovered patterns that looked like this:

muellerlongtail

Actually, based on similar studies of academic citation patterns, we could have predicted that Mueller would discover this power law distribution. It turns out that academic citations—a purely cultural form, a textual artifact constructed through the practices of the academy—behave according to a statistical law that seems to affect all sorts of things, from earthquakes to word frequencies. This example makes a strong case against those who argue that cultural artifacts, constructed by human agents within their contextualized interactions, will not aggregate over time into scientifically recognizable patterns.  Granted, this example comes from mathematics, not evolutionary theory, but it makes the point nicely anyway: the creations of human culture are not necessarily free from non-human processes. Is it foolish to look for the effects of these processes through distant reading?

 

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“Evolution,” “influence,” “gradualism”—whatever we call it in the digital humanities, those of us adopting it on the literary and rhetorical end have a huge advantage over those working in history: we have a well-defined, observable element, an analogue of DNA, to which we can always reduce our objects of study: words. If evolution is going to be a guiding metaphor, we need this observable element because it is through observations of its metamorphoses (in usage, frequency, etc.) that we begin to figure out the mechanisms and dynamics that actually cause or influence those metamorphoses. If we had no well-defined segment to observe and quantify, the evolutionary metaphor could be thrown right out.

To demonstrate its importance, allow me a rhetorical demonstration. First, I’ll write out Piazza’s description of biological evolution found in his afterword to Graphs, Maps, Trees. Then, I’ll reproduce the passage, substituting lexical and rhetorical terms for “genes” but leaving everything else more or less the same. Let’s see how it turns out:

Recognizing the role biological variability plays in the reconstruction of the memory of our (biological) past requires ways to visualize and elaborate data at our disposal on a geographical basis. To this end, let us consider a gene (a segment of DNA possessed of a specific, ascertainable biological function); and for each gene let us analyze its identifiable variants, or alleles. The percentage of individuals who carry a given allele may vary (very widely) from one geographical locality to another. If we can verify the presence or absence of that allele in a sufficient number of individuals living in a circumscribed and uniform geographical area, we can draw maps whose isolines will join all the points with the same proportion of alleles.

The geographical distribution of such genetic frequencies can yield indications and instruments of measurement of the greatest interest for the study of the evolutionary mechanisms that generate genetic differences between human populations. But their interpretation involves quite complex problems. When two human populations are genetically similar, the resemblance may be the result of a common historical origin, but it can also be due to their settlement in similar physical (for example, climactic) environments. Nor should we forget that styles of life and cultural attitudes of an analogous nature (for example, dietary regimes) can favour the increase or decrease to the point of extinction of certain genes.

Why do genes (and hence their frequencies) vary over time and space? They do so because the DNA sequences of which they are composed can change by accident. Such change, or mutations, occurs very rarely, and when it happens, it persists equally rarely in a given population in the long run . . . From an evolutionary point of view, the mechanism of mutation is very important because it introduces innovations . . .

. . . The evolutionary mechanism capable of chancing the genetic structure of a population most swiftly is natural selection, which favours the genetic types best adapted for survival to sexual maturity, or with a higher fertility. Natural selection, whose action is continuous over time, having to eliminate mutations that are injurious in a given habitat, is the mechanism that adapts a population to the environment that surrounds it. (100-101)

Now for the “distant reading” version:

Recognizing the role lexical variability plays in the reconstruction of the memory of our (literary and rhetorical) past requires ways to visualize and elaborate data at our disposal on the basis of cultural space (which often correlates with geography). To this end, let us consider a word (a segment of phonemes and morphemes possessed of a specific, ascertainable grammatical or semantic function); and for each word let us analyze its stylistic variants, or synonyms. The percentage of texts that carry a given stylistic variant may vary from one cultural space to another, or from one genre to the other. If we can verify the presence or absence of that variant in a sufficient number of texts produced in a circumscribed and uniform cultural space we can draw maps whose isolines will join all the points with the same proportion of stylistic variants.

The distribution of such lexical frequencies can yield indications and instruments of measurement of the greatest interest for the study of the evolutionary mechanisms that generate lexical differences between “generic populations.” But their interpretation involves quite complex problems. When two rhetorical forms or genres are lexically similar, the resemblance may be the result of a common historical origin, but it can also be due to their development in similar geographic or political environments. Nor should we forget that styles of life and cultural attitudes of an analogous nature (for example, religious dictates) can favour the increase or decrease to the point of extinction of certain lexical items or clusters of lexical items.

Why do words (and hence their frequencies and “clusterings”) vary over time and space? They do so because of stylistic innovations. Such innovation occurs very rarely, and when it happens, it persists equally rarely in a given generic population in the long run . . . From an evolutionary point of view, the mechanism of innovation is very important because it introduces new rhetorical forms . . .

. . . The evolutionary mechanism capable of changing the lexical structure of a rhetorical form or genre most swiftly is cultural selection, which favours the forms best adapted for survival to publication and circulation, or with a higher degree of influence (meaning a higher likelihood of being reproduced by others without too many changes). Cultural selection, whose action is continuous over time, having to eliminate rhetorical innovations or “mutations” that are injurious in a given cultural habitat, is the mechanism that adapts a rhetorical form to the environment that surrounds it.

Obviously, it’s not perfect. I leave it to the reader to decide its persuasive potential.

I think the biggest problem is in the handling of mutations. In biological evolution, genes mutate via chance variations during replication of their segments; these mutations can introduce innovations in an organism’s form or function. In literary evolution, however, no sharp distinction exists between a lower-scale “mutation” and the innovation it introduces. The innovation is the formal mutation. This issue arises because, in literary evolution, as in linguistic evolution, the genotype/phenotype distinction is not as obvious or strictly scaled as it is in evolutionary theory. Words are more phenotype than genotype, unless we want to get lost in an overly complex evocation of morphology and phonology.

The metaphor always breaks down somewhere, but where it works, it is, I think, highly suggestive: the idea is that we track rhetorical forms—constellations of words and their stylistic variants—across time and space, in order to see where the forms replicate and where they disappear. Attach meta-data to the texts that constitute those forms, and we will have what it takes to begin making data-driven arguments about how cultural ecology affects or does not affect cultural form.

It’s an interesting framework in which distant reading might go forward, even if explicit uses of the word “evolution” are abandoned.

Historical Linguistics and Population Genetics

Reich et al.  provide a model of two ancient populations in India that are ancestral to modern populations—Ancestral North Indians (ANI) and Ancestral South Indians (ASI). According to Reich et al, ANI is, on average, more genetically similar to Middle Easterners, Central Asians, and Europeans. ASI, on the other hand, is distinct from ANI as well as from East Asian populations. This same study found that “ANI ancestry ranges from 39–71% in most Indian groups, and is higher in traditionally upper caste and Indo-European speakers.” Furthermore, Reich et al. showed that the Indian caste system is old and historically implacable—high FST values indicate that “strong endogamy must have shaped marriage patterns in India for thousands of years.” This seriously contradicts the claims of Edward Said, Nicholas Dirks, and others who have argued that caste in India was more fluid and less systematized before British imperial rule.

However, a recent paper (Moorjani et al. 2013) does show fluid population admixture between Indian groups somewhere between 1,900 and 4,200 years ago.

Our analysis documents major mixture between populations in India that occurred 1,900 – 4,200 years BP, well after the establishment of agriculture in the subcontinent. We have further shown that groups with umixed ANI and ASI ancestry were plausibly living in India until this time. This contrasts with the situation today in which all groups in mainland India are admixed. These results are striking in light of the endogamy that has characterized many groups in India since the time of admixture. For example, genetic analysis suggests that the Vysya from Andhra Pradesh have experienced negligible gene flow from neighboring groups in India for an estimated 3,000 years. Thus, India experienced a demographic transformation during this time, shifting from a region where major mixture between groups was common and affected even isolated tribes such as the Palliyar and Bhil to a region in which mixture was rare.

As the researchers go on to indicate, ~2,000 to 3,000 years ago corresponds to the major transitions attendant to the end of the Harappan civilization and the influx of the Indo-Aryans. Can these genetic studies shed any light on the controversies of Indian language history?

Emeneau’s famous 1956 paper, “India as a Linguistic Area,” holds up reasonably well to contemporary scrutiny. The Indo-Aryan, Dravidian, and Munda language families have obviously influenced one another. Dravidian influence on Indo-Aryan is well attested. But this seems odd given the correlation, discovered by Reich et al. and others, between Indo-European speaking ancestry and upper caste status in India. Another population genetics study (Bamshad et al. 2001) puts it this way:

Indo-European-speaking people from West Eurasia entered India from the Northwest and diffused throughout the subcontinent. They purportedly admixed with or displaced indigenous Dravidic-speaking populations. Subsequently they may have established the Hindu caste system and placed themselves primarily in castes of higher rank.

These “Indo-European-speaking people” probably have something to do with Reich et al.’s Ancestral North Indians. But if these “invaders” were strong enough to admix with and displace the indigenous Dravidic-speaking populations, why does Emeneau find Dravidian influence on Indo-Aryan? Imagine Cherokee influencing English on the scale of 5%. It’s just not going to happen. Most linguistic history shows that dominant languages influence less dominant languages; the opposite rarely occurs, and if it does, its influence on the dominant language is minimal.  In another paper, Emeneau has this to say:

[There has long been the assumption] that the Sanskrit-speaking invaders of Northwest India were people of a high, or better, a virile, culture, who found in India only culturally feeble barbarians, and that consequently the borrowings that patently took place from Sanskrit and later Indo-Aryan languages into Dravidian were necessarily the only borrowings that could have occurred . . . It was but natural to operate with the hidden, but anachronistic, assumption that the earliest speakers of Indo-European languages were like the classical Greeks or Romans—prosperous, urbanized bearers of a high civilization destined in its later phases to conquer all Europe and then a great part of the earth—rather than to recognize them for what they doubtless were–nomadic, barbarous looters and cattle-reivers whose fate it was through the centuries to disrupt older civilizations but to be civilized by them.

Rather than the image of Indo-European “invaders” whose civilized power subjugated indigenous Indian populations, Emeneau instead imagines barbarians at the gates. Certainly, the language of nomads would be more socially susceptible to indigenous Dravidian, but how does this picture fit with the recent discovery of early population admixture? Would indigenous Dravidians have been more likely to breed freely with uncivilized nomads roaming and slowly penetrating the borderlands? Possibly.

Michael Witzel might have a different solution. The oldest Indian text following the actual Harappan script itself is the Rigveda, a collection of sacred Vedic Sanskrit hymns. Witzel finds in the earliest sections of the Rigveda several hundred lexical items and a few morphological features that are clearly not of Sanskrit (and therefore, not of Indo-European) origin. His analysis of these features leads him to believe that the language spoken before the arrival of Indo-Europeans—i.e., spoken in the Harappan civilization—was more closely related to the Munda languages and the Austroasiatic language family. In other words, Witzel’s analysis suggests that an Indo-European “invasion” and domination of indigenous Dravidian speakers is probably not an accurate historical picture. A sacred Indo-European text like the Rigveda would not contain so many non-IE loanwords if its speakers had entered the scene as dominant bringers of hierarchy. And given that the non-IE loanwords and morphological features are more likely Austroasiatic than Dravidian, Witzel envisions a time when Indo-European speakers and Dravidian speakers immigrated slowly into Harappan civilization, neither dominant invaders nor barbarous raiders. This would explain the cross-linguistic influence in the Indian subcontinent. It would also explain Moorjani et al.’s recent paper showing major mixture between groups in India prior to the rise of the caste system several thousand years ago.

Or maybe not. Witzel’s theory is not well accepted among historical linguists. And if Indo-Aryan and Dravidian immigration was so gradual and perhaps even egalitarian (Witzel imagines that Harappan urban centers may have been trilingual), from whence came a caste system that so clearly favors one ancestral group over the others? And there’s a nagging question about timing: one study suggests that Reich’s ANI might not fit within the purported timeline of Indo-European speakers’ migration. There’s also the issue of linguistic distribution. Razib Khan notes:

It seems an almost default position by many that the Austro-Asiatics are the most ancient South Asians, marginalized by Dravidians, and later Indo-Europeans. I would not be surprised if it was actually first Dravidians, then Austro-Asiatics and finally Indo-Europeans. Dravidians are found in every corner of the subcontinent (Brahui in Pakistan, a few groups in Bengal, and scattered through the center) while the Austro-Asiatics exhibit a more restricted northeastern range.

It’s all quite messy, but my point is that linguists interested in language contact and linguistic evolution should be reading work in population genetics, too. Papers on population genetics often reference work in historical linguistics; however, I rarely see historical linguists citing population genetics.