BACKGROUND AND RATIONALE FOR STUDY
3.10 Grammatical Metaphor (GM) (Halliday and Martin, 1993)
Halliday (1985a) explains that there are two kinds of expressions:
a. congruent, non-metaphorical or non-marked; and, b. incongruent, metaphorical or marked
Briones et al. (2003: 139) offer examples of each of the above:
a) The light that is emitted by a fluorescent tube ... (congruent) and;
b) The emission of light by a fluorescent tube... (metaphorical)
“It is generally considered that people, places and things are realized by means of a noun;
actions are realized verbally; and circumstances are realized by prepositional phrases and adverbs. This is the typical, congruent relationship between semantic and grammatical
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categories that usually happens in spontaneous spoken language. However, all meanings may have more than one way of realization, and sometimes, in written language and especially in the language of science, the realizations of the semantic functions of the clause are not typical, but marked. This realization constitutes a Grammatical Metaphor (GM)” (Briones et al. 2003: 137). GM is thus defined as:
● “a substitution of one grammatical class, or one grammatical structure by another” (Halliday and Martin, 1993: 79);
● the process whereby meanings are multiply-coded at the level of grammar” (Martin, 1993: 230); or as
● a variation in the grammatical forms through which a semantic choice is typically realized in the lexicogrammar” (Sáenz, 2000:
498).
Halliday (1985a) notes that in Grammatical Metaphors, “the variation is essentially in the grammatical forms although often entailing some lexical variation as well” (320). Halliday (1993) also expresses the point that GM is “like a metaphor in the usual sense except that, instead of being a substitution of one word for another, it is a substitution of one grammatical class, or one grammatical structure, by another; for example his departure instead of he departed” (79). With regard to this example cited, Halliday and Martin (1993) comment that:
the words (lexical items) are the same; what has changed is their place in the grammar. Instead of pronoun he + verb departed, functioning as Actor plus Process in a clause, we have determiner his + noun departure, functioning as Deictic38 plus Thing in a nominal group. Other examples are her recent speech concerned poverty instead of she spoke recently concerning poverty; glass crack growth rate instead of how quickly cracks in glass grow. Often the words may change as well as the grammar, as in the last example where how quickly is replaced by rate (79).
“Academic writing has a reliance on GM” (Halliday, 2004a: xvi). GM is a very economical means of packaging information and is consequently frequently used in scientific information where the “real” actors are often absent from the scene, replaced by the nominalised processes. “Besides efficiency, GM lends an appearance of objectivity to the text” (Stålhammar, 2006: 100). Schleppegrell (2009) explains that “grammatical metaphor enables a writer to create abstractions that can participate in building arguments and structuring texts in ways that enable the development of an explanation, and to infuse a clause with causal and other meanings without explicit conjunctions ... While grammatical
38 The Deictic ‘indicates whether or not some subset’ of ‘a class of things’ is ‘intended’ (e.g. ‘all’,‘some’), and, used ‘demonstratively’, can stipulate ‘proximity to the speaker’ (e.g. ‘this’) or ‘possession’ (e.g. ‘your’) (Halliday, 1991 cited in de Beaugrande, 1991).
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metaphor increases the density of text, it also enables conciseness and precision” (13-14).
Halliday (1998) notes lexical density, nominalisation and grammatical metaphor as the main lexicogrammatical characteristics of the written (academic) language.
Nominalisation “is the single most powerful resource for creating grammatical metaphor”
(Halliday, 2004b: 656). Nominalisation is commonly used in science discourse (Hyland, 2002; Halliday, 2004b; Holtz, 2009 and Hadidi, 2012). Through nominalisation, processes (linguistically realized as verbs) and properties (linguistically realized, in general, as adjectives) are re-construed metaphorically as nouns, enabling an informationally dense discourse (Holtz, 2009). Nominalized structures in academic writing include nouns that have been morphologically derived from verbs (e.g. development, progression) as well as verbs that have been ‘converted’ to nouns (e.g. increase, use) (Biber and Gray, in press).
“Nominalization turns actions or processes into concepts, while also reducing the number of clauses and compressing more information into each nominal group (Hadidi, 2012: 349).
Halliday and Martin (1993) provide examples to illustrate the use of GM in science discourse:
1. Glass cracks more quickly the harder you press on it.
2. Cracks in glass grow faster the more pressure is put on.
3. Glass crack growth is faster if greater stress is applied.
4. The rate of glass crack growth depends on the magnitude of the applied stress.
5. Glass crack growth rate is associated with applied stress magnitude (55).
In a discussion of these examples, Biber and Gray (in press) note that the first of these examples above is the most ‘congruent’, where the meanings of words correspond to the expected meanings of the grammatical categories used. For example, the verbs cracks and press are used to refer to those processes. In contrast, examples 4 and 5 above illustrate a dense use of grammatical metaphor, with qualities and processes being expressed by nouns rather than adjectives and verbs.
One way of contrasting the relative complexity of speech and writing is by means of lexical density. Lexical density, according to Halliday and Martin (1993), “is a measure of the density of information in any passage of text, according to how tightly the lexical items (content words) have been packed into the grammatical structure. It can be measured, in English, as the number of lexical words per clause” (76). Lexical density can be expressed
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either as a percentage of lexical words within all the words of a text (Ure, 1971)39 or the number of lexical items as a ratio of the number of clauses” (Halliday, 1985b: 67)40. Originally, Ure (1971) proposed that lexical density should be treated as the proportion of the number of lexical items per the number of running words. The following example illustrates how lexical density is calculated using the method proposed by Ure (1971):
“The Trust has offered advice to local government authorities on cemetery conservation” (Halliday, 1985b: 61).
In the above example, there are eight lexical items (in bold type) and four grammatical items (italicized), giving a proportion of eight lexical items out of twelve items in total.
Using Ure’s (1971) method, lexical density would be sixty seven percent (see footnote40).
The following sentence illustrates how lexical density is calculated using the method proposed by Halliday (1985b):
“The basic ‘stuff’ of living organisms is protoplasm/. There is no set composition of this/and it varies between one individual and the next/
(Halliday, 1985b: 67).
In the above example, there are nine lexical items (in bold type) and three clauses (denoted by the forward slash, / ), giving the ratio nine out of three. Using Halliday’s (1985b) method, lexical density would be three (see footnote41).
In order to measure lexical density, it is necessary to distinguish between grammatical items and lexical items. Grammatical items or ‘function words’ include all modals and auxiliary verbs; determiners (articles, demonstrative, possessive adjectives, quantifiers and numerals); pronouns and ‘this’ and ‘that’ when used to replace clauses; some classes of adverbs (interrogative adverbs - what, when, how and negative adverbs - not, never) and finite verbs; prepositions; conjunctions; sequencers (next, finally); and quantifier phrases (anyway, somehow, whatever) (Johansson, 2008; To et al. 2013 ).
39 Using Ure’s (1971) method, “the lexical density of a text can be measured by counting the total words in a text and then counting the lexical words, that is, the content words, excluding the grammar or function words, and calculating the lexical words as a percentage of the total words; the higher the percentage, the higher the lexical density” (McCarthy, 1990: 71).This would then be Lexical density = number of lexical items x 100/total numbers of words (Ure, 1971).
40Lexical density =
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Nouns, verbs, adjectives and adverbs are the four word classes belonging to lexical items since they have autonomous meaning even in isolation and new members can be added to these categories (Le et al. 2011). According to To et al. (2013), Halliday (1985b) uses the term ‘items’ rather than ‘words’ when discussing lexical items and grammatical items since they many contain more than one word in the usual sense. For example, the phrasal verb
‘stand up’ consists of two words: a lexical verb and a preposition but Halliday (1985b) treats them as a lexical item. In contrast, Ure (1971) would count ‘stand up’ as two separate words (the lexical word, ‘stand’; and the preposition, ‘up’).
Lexical density levels are higher in writing than in speech. “Informal spoken language is made grammatically out of chains of short clauses, linked by coordinating or subordinating conjunctions: “and”, “but” “or” “because”, “when”, etc., while formal written language compresses the information into heavily modified nominal groups” (Whittaker, 2010: 34).
A discussion on GM is significant in this study which examines the use of discipline- specific literacies in science. The language of science is heavily reliant on the use of lexical density and nominalisation which are discussed in greater detail in Chapter 4 of this dissertation. The issue of GM is relevant to this study as students in the FP in science are exposed to dense scientific articles and textbooks that they would have to decode, deconstruct, interpret and study. This does not only involve understanding science content, but also becoming familiar with academic language and register. Scientific articles and texts convey content through the use of secondary discourse and elaborated code. Effective engagement with them means decoding such types of complex language and requires well- developed CALP (Cummins, 1979). This will involve the use of new ways of expressing themselves using academic language in science.
The FP students have to rely on new linguistic resources to understand and make sense of science context in order to complete academic tasks in science. It is thus the intention of this study to investigate what discipline-specific literacies those academics (viz. the ALSs and the DSs) who teach the modules offered in the FP believe are required by the students enrolled in the FP. This is obtained via critical research question 1. The ways in which the DSs, in particular, assist students in the acquisition of the discipline-specific literacies needed for science discourse is explored via critical research question 3. The perceived challenges confronting students in respect of coping with the challenges of the language of
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science (for example, the way in which GM features in science discourse) and the discipline-specific literacies in science, are measured through critical research question 2.