Evaluative Meanings and Disciplinary Values - eTheses Repository ...

study incorporated the second type into the data of the pattern A DJ PR EP N.
After the patterns were extracted, a back-check was conducted in order to remove
any irrelevant examples (e.g. N about N). This was achieved by manually checking instances
using a concordancer. Two particular sources of irrelevant examples in both corpora were
detected when examining the patterns A DJ of N and A DJ on N: good, kind, characteristic,
net and top in the pattern A DJ of N (e.g. [T]o do this successfully, an efficient net of
anaphoric and cataphoric link is essential.) and firm, kind and light in the pattern A DJ on N
(e.g. [T]hen firm F is as efficient as any other firm on the frontier). These words are listed in
Francis et al. (1998) as adjectives appearing in each pattern, but my concordance investigation
found that some examples were more accurately judged as nouns and were thus removed. It is
also worth noting at this point that this is the reason why my corpora are not annotated with
part-of-speech tags. Originally, I had hoped to extract the adjective patterns
semi-automatically by using tags to search for adjective patterns. To this end, I annotated parts
of my corpora with Go Tagger (Goto, 2005), and Q-tag (ver. 3.1) (Mason, 2003). However,
when I checked through these data manually I found that there were big differences in the
number of adjective patterns identified by manual and tag-driven analyses. I therefore decided
to adopt a manual approach for the current study. (N.B. Although Dr. Pernilla Danielsson
assisted me in tagging my corpora and extracting the patterns from them, she also had no idea
why there were such big differences between manual and tag-driven analyses.)
The 16 patterns described in Francis et al. (1998) were found to form two clearly
distinguishable groups in ALC and BC with regard to the pattern frequency. One group
consisted of 8 high-frequency patterns, and the other group consisted of 8 low-frequency
patterns. The high-frequency group includes the patterns A DJ about/for/in/of/of/on/to/with
N; the low-frequency group includes the patterns A DJ against/as/as
to/at/between/by/over/toward(s) N. (N.B. For practical reasons, the cut-off point is at 200
occurrences of the total tokens in both corpora combined). Since the most significant findings
are found in the high-frequency group, I will focus mainly on these patterns in the analysis
and discussion that follows. However, in cases where interesting data are found in the
low-frequency patterns, these will also be included.
5.3.3. Correspondence analysis procedure
As explained in Chapter 4, the aim of correspondence analysis is to visualize the
interrelationships among samples and variables. In the current study, a correspondence
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