The inductive approach devised by Gledhill (2000) in investigation of cancer research articles is applied by Groom (2003; 2006) to US stem-cell patent specifications and to exploration of links between epistemology and phraseology in two disciplines, history and literary criticism. To briefly summarise their methodology, investigation begins with the generation of keywords not only in comparison with a reference corpus but (in Groom 2006) between the two disciplines and (in Gledhill 2000 and Groom 2003) between rhetorical sections.1 For this purpose, corpora are divided into subcorpora containing, in Gledhill (2000), title, abstract, introduction, methods, results, and discussion. The ten most frequent key grammatical or closed-class items form the basis of investigation, and the phraseologies into which these closed-class items enter explored using concordance lines. In Groom (2006) this is extended to make claims about the link between phraseologies and each discipline‘s epistemological stance.
Gledhill‘s and Groom‘s defence of their methodology as corpus-driven is essentially that it is inductive, in that wordform frequency and keyness direct the course of investigation, guided by previous corpus-driven findings concerning the significance of phraseology (Sinclair 1991; 2004) and closed-class words which contribute to the meaning of phrases as much as the lexical items which control them (Hunston and Francis 2000). Phraseologies which emerge are not those evident within traditional approaches.
Figure 3.4 Semantic sequence identified by Groom (2006: 86) as part of his model investigation
process of object
the building of a church the attribution of insensitivity
the rescue of Jews
A change of mind
the elaboration of native histories
As with corpus-based studies, there is still a degree of selection in determining features to study. The assumption made is not only that keywords play a role in significantly frequent
1 In other words, words which are significantly more frequent in one section compared to the rest of the corpus thus form the basis of much of their analysis, regardless of their significance in comparison to general language use.
phraseological patterns (Gledhill 2000: 102), but that these phraseologies are of greater significance than other features traditionally explored in academic or scientific texts such as nominalisation or modality, discussion of which is precluded by focusing on phraseologies. However, the research draws attention to the existence of phraseological patterns which vary according to language functions and so challenge corpus-based findings.
Far from providing a framework for application to similar phraseologies across varieties, these corpus-driven studies highlight the fact that what serves to describe one kind of language may be inappropriate for another. Groom (2006), for example, is concerned with describing the way in which knowledge is perceived and constructed linguistically in literary criticism and history.1 In other words, he focuses on links between phraseology and epistemology: ‗epistemology is manifested in phraseology‘ while ‗phraseology produces and reproduces epistemology‘ (Groom 2006: 25). In fact, he suggests, each distinct disciplinary discourse emerges from fusing its epistemological stance to knowledge2 and to the ‗conventionalised forms of expression‘, or phraseologies, used to capture them (Groom 2006: 24). Although this epistemological perspective could prove insightful in investigating other academic or science texts, it would hardly be appropriate in application to more generalised varieties whose users share no epistemological perspective: such as texting.
Practical drawbacks include the potential unwieldiness of Gledhill and Groom‘s approach with larger datasets or less specialised varieties. The corpora used in both studies are small, around 500,000 words (150 articles) and 5,500,000 (405 patents) respectively.3 As Groom points out, investigation of the larger section in his patent specifications, ‗Detailed descriptions of the invention‘, is difficult to summarise within the limits of his thesis. Furthermore, academic writing is ‗specialised‘ in the sense that participation is limited to individuals who learn and accept the discourse community‘s meanings, values and goals, as well as the language and specialised terminology used to express them (Groom 2006: 24). The formulaic nature of sections such as ‗Titles‘ suggests that less specialised language may not be amenable to this approach.
1
Rather than how language is used within different genres.
2 For example, whether the discipline is soft or hard, pure or applied (Becher e.g. 1987).
3 Incidentally and as briefly alluded to in an earlier section, both can claim, due to the limited generality of the varieties studied, a degree of representativeness: the texts in Gledhill‘s (2000: 51-53/90-98) corpus reflect the discourse community at one Pharmaceutical Science Department (PSD), while Groom‘s texts comprise all US stem-cell patents issued at the time (Groom 2003: 23).
The extent, therefore, to which this model can inform other corpus-driven studies of language varieties is by definition limited. The danger is that a corpus-driven approach quickly becomes corpus-based, in the sense that observations driven by one dataset are applied (perhaps inappropriately) to another, and subsequent datasets adjusted to enable comparisons. To ensure that future investigations are truly corpus-driven, researchers can similarly start with frequency and computer-generated keyness calculations, but the direction their investigation takes should be determined by the frequency and significance of features in their data. For example, Gledhill‘s and Groom‘s focus on closed-class rather than open-class words is useful in warning against dismissing the former, but should not preclude investigation of open-class words; similarly, the focus on positive keywords should not preclude consideration of negative keywords. Gledhill‘s and Groom‘s work is important and the principles they uphold guide the current investigation of texting, although the exact form the investigation takes necessarily differs. The implication, however, is that corpus-driven study can never be truly comparative nor generate models for application across varieties.
The final limitation to the work described above is that, by focusing on lexical patterns in which significantly frequent function words operate, the researchers risk missing other features or ‗levels‘ of language description. These features include discourse markers, as well as features without searchable surface forms, such as ellipsis. The work of Carter and McCarthy (2006), inductive but based on in-depth reading, potentially fills gaps left by the corpus-driven approach.