Commonly held perceptions that academic writing is more structurally elabo- rated than conversation would predict that academic writing would use the elaborated grammatical features to a greater extent than conversation. In fact,
the results show that the opposite is true. Figure 9.1 shows the distribution of common dependent clause types. Finite complement clauses (e.g. that-clauses and wh-clauses), non-finite complement clauses (to-clauses and ing-clauses) and finite adverbial clauses (e.g. because-clauses and if-clauses) are all much more prevalent in conversation than in academic writing. The two other types of dependent clauses – finite and non-finite relative clauses – are more preva- lent in academic writing than conversation; these are both nominal features that modify a head noun. Overall, dependent clause types are nearly twice as frequent in conversation as in academic writing.
In contrast, Figure 9.2 shows that much of the embedding and elaboration in academic writing comes from phrasal components modifying a head noun, with all four of the dependent phrasal structures occurring at a higher rate per 1,000 words in academic writing than in conversation. Attributive adjec- tives (e.g. differential reinforcement, theoretical orientation) and nouns as noun modifiers (e.g. trait information, system perspective) are quite common in aca- demic prose in comparison to conversation. The distribution of prepositional phrases as noun postmodifiers (e.g. a strategic approach to mutual understanding;
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Rate per 1,000 words 6
4 2 0 Finite complement clauses Non-finite complement clauses Finite adverbial clauses Finite relative clauses Non-finite relative clauses
Conversation Academic writing
Continuum Companion to Discourse Analysis
a surrogate for a suite of unmeasured covariates) in academic prose is also particu-
larly salient.
Overall, this analysis shows that the stereotype that academic writing is more structurally complex in terms of embedded dependent clauses is not sup- ported by the corpus evidence. While conversation typically employs a higher amount of subordination (embedded dependent clauses) than academic writ- ing, academic writing employs more structures embedded in the noun phrase. These patterns are evident in the following two excerpts. The first text excerpt is from conversation, where the use of subordinate clauses is common and the use of nouns and noun phrase modifiers is less common. In contrast, the second excerpt is from academic prose, illustrating the dense use of modifiers within the noun phrase, including both phrasal structures and relative clauses. In both excerpts, nouns are bolded, noun postmodifiers (finite and non-finite relative clauses, and postmodifying prepositional phrases in noun phrases) are under- lined, attributive adjectives and premodifying nouns are in italics. Dependent
Figure 9.2 Common dependent phrasal types (from Biber and Gray 2010)
Conversation Academic writing 70
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Rate per 1,000 words
20 10 0 Attributes adjectives in NPs Premodifying nouns in NPs Premodifying prepositional phrases in NPs Prepositional phrases as adverbials
clauses which are sentence elements are double-underlined (if the dependent clause overlaps with other features, only the first few words of the clause are double-underlined).
Excerpt 1: From an unscripted organizational board meeting
1: The thing is we only need one funding this year so if they don’t VENRC should fund us
2: Right, but
3: That is true. Or the state department. I talked to Cheryl and, and she thought maybe they could come up with some.
2: Is it that bad a year?
3: Yeah, yeah. They’re eliminating all the jobs except hers at, you know, in Oklahoma. It’s really getting <unclear>.
2: So, just take it out completely?
3: Um, ... yes, take it out completely. Cause we don’t know yet whether she’ll ... I’m pretty sure. I just sent the, uh, <unclear> and the bio two
days ago to <unclear> so maybe because she didn’t have that she didn’t
want to commit. 1: That’s an idea.
2: I, I got a copy for you. Did you make a copy for yourself. Okay, 3: I thought if I put it on my desk to make a copy I’ll never get it in the
mail so I just put it right in the mail for you.
2: Okay. Well I made two copies to send around for anybody who wants to see it and
1: It’s nice.
3: It is a nice <unclear>.
Excerpt 2: From a research article in Biology
A common interest in modeling is to make inferences about the effect
of the longitudinal measures on the time to event, but not to make
inferences about the longitudinal measures or their projected change over time. The longitudinal model is important for accounting for measurement error and defining the individual’s longitudinal trajectory between times
of measurement. Because a complex model for the longitudinal measures may be too complicated to estimate in the joint model, a linear mixed
model that is parametric with respect to time is most commonly used.
More recently, attention has focused on relaxing assumptions on the
model for the longitudinal data, but this research has focused mainly
on the distributional assumptions of the random effects and has not addressed the shape of the trajectory, often making simple parametric
Continuum Companion to Discourse Analysis
in modeling the longitudinal component, we may often judge these
simple models to be inappropriate. Also, when the true relationship
between time and the longitudinal biomarker is nonlinear, the effect that assuming a simple linear longitudinal model has on the estimate of the
relationship of the marker and the time-to-event outcome is unclear.
Both text excerpts are approximately 200 words long. However, the dense use of nouns in the Biology research article is readily evident at a glance. In addition, the high density of nominal modifiers (attributive adjectives, nouns as noun premodifiers, prepositional phrases and relative clauses as postmodi- fiers) is also prominent. In particular, note that there are often multiple levels of embedding within noun phrases, such as in:
inferences about the effect of the longitudinal measures on the time to event
where the head noun inferences is modified by one long prepositional phrase, which contains two additional phrases modifying effect (of the longitudinal mea-
sures and on the time to event), and a final prepositional phrase (to event) modify-
ing the head noun time.
In contrast, the conversation excerpt relies more heavily on pronouns than nouns, and has only one prepositional phrase modifying a head noun (except
hers). However, the conversation excerpt does contain many embedded depen-
dent clauses:
if they don’t whether she’ll . . .
because she didn’t have that . . .
thought (that) . . . I’ll never get it in the mail if I put it on my desk
so I just put it in the mail for you who wants to see it
These corpus findings and the text excerpts above illustrate the distinc- tive patterns differentiating conversation from academic writing in terms of elaboration. Each register’s reliance on particular features can be functionally related to the situational characteristics of the register. While academic writ- ing is not ‘complex’ in its use of subordination features, it is complex in that it utilizes phrasal embedding as a means of structural elaboration. Although tra- ditional measures of complexity and elaboration typically focus on subordina- tion, phrasal elements like attributive adjectives, nouns as noun premodifiers, appositive noun phrases, and prepositional phrases as noun postmodifiers are also elaborating in the sense that they add optional, extra information.
However, these phrasal elements are condensed in the sense that they are compressed alternatives to fuller clausal modifiers. In academic prose, writers prefer these compact structures because they are more economical. That is, they allow the expert reader to process a great deal of information quite effi- ciently. Thus, while both conversation and academic writing are complex and elaborated, they are so in dramatically different ways.
This sample study has illustrated how corpus-based discourse studies of
language in use can uncover systematic patterns of variation across registers. In
addition, it has shown that findings resulting from corpus-based analyses can be counter to many of our intuitions and/or assumptions about language use in a particular register. In the final section, we now turn to how corpus linguistics can be used to investigate language structure beyond the sentence.