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Exploring register variation
in learner lexis
The high-frequency verb make in
native and learner speech and writing
Claire Hugon
CECL
Louvain-la-Neuve
24. January 2008
1
Outline of the presentation





Background and aims of the study
Methodology
Setting the scene: make in the BNC
Make in native and French-speaking learner speech
and writing
Methodological implications and avenues for future
research
2
Background and aims of the study


Broader context: PhD research on the
acquisition of high-frequency verbs
3 preliminary remarks:



The influence of L1 as the « darling variable » of
learner corpus linguists
Learner writing is frequently said to be speechlike
SLA variables are often studied in isolation
3
Background and aims of the study

Research questions:



Does register have an influence on the use of
high-frequency verbs (HFVs) such as make in
learner English?
Is the use of make in learner writing similar to
native speech?
Can register differences be an alternative/
complementary explanation to features of nonnativeness attributed to L1?
4
Methodology
CIA
IL vs IL
registera
L1a
proficiencya
taska
vs.
vs
vs.
vs.
registerb
L1b
proficiencyb
taskb
...
(CRIA)
5
Methodology
Confrontation of native and learner data to detect similarities and
differences and try to explain them (to-ing and fro-ing between the
two components)
NS (writing)
LOCNESS
NS (speech)
LOCNEC
NNS (writing)
ICLE-FR
NNS (speech)
LINDSEI-FR
6
Implementing the methodology: the
example of make
1.
2.
native language: make (and other HFVs) in the BNC

see how HFVs behave in native language before looking for
differences in learner language

BNC: wide-coverage corpus, much larger than LOCNESS

better suited for broad, quantitative analysis
quantitative and qualitative analysis: make in native and learner
speech and writing

native: LOCNESS and LOCNEC

learner: ICLE-FR and LINDSEI-FR

Comparison of the results
7
Top HFVs in the BNC
Whole BNC
Spoken BNC
Written BNC
1. say
1. get
1. say
2. go
2. go
2. make (rel.freq. 2,190)
3. get
3. say
3. go
4. make (rel.freq.2,160)
4. know
4. take
5. seem
5. think
5. see
6. know
6. see
6. get
7. take
7. come
7. know
8. think
8. mean
8. come
9. come
9. want
9. give
10. give
10. take
10. use
11. look
11. look
11. think
12. use
12. make (rel.freq. 1,905)
12. look
8
Make in the BNC
•Make is less frequent in speech than in writing
•the difference is highly significant according to the
chi-square test
•atypical (most HFVs are more typical of speech)
spoken BNC
(/million words)
written BNC
(/million words)
chi-square value
1,905
2,190
*** 349.7
9
Implementing the methodology: the
exampe of make
1.
2.
native language: make (and other HFVs) in the BNC

see how HFVs behave in native language before looking for
differences in learner language

BNC: wide-coverage corpus, much larger than LOCNESS

better suited for broad, quantitative analysis
quantitative and qualitative analysis: make in native and learner
speech and writing

native: LOCNESS and LOCNEC

learner: ICLE-FR and LINDSEI-FR

Comparison of the results
10
Make in native and learner speech and
writing: some findings
Overall frequency (/100,000 words):

Speech
Writing
Speech vs
writing
NS
146.8
350.6
146.8 < 350.6
NNS
126.6
245
126.6 < 245
NS vs NNS
146.8 ≥ 126.6
350.6 > 245
make is significantly (***) less frequent in NS speech than in NS writing
make is significantly(***) less frequent in NNS speech than in NNS writing
 slight underuse of make in NNS speech, but not significant


highly significant (***) underuse of make in NNS writing
 brings frequency in NNS writing closer to NS speech
Make is a polysemous verb  qualitative analysis to explain the results
11
7 main semantic subdivisions



core meaning (produce, create)
delexical uses
 ‘speech’ collocates
 other collocates
causative uses

causative uses







make + adj
make + verb
make + noun
‘money’ make
phrasal verbs
other uses
link verbs
12
Distribution of the occurrences of make
in the four corpora, by semantic category
NS writing
NS speech
lin
k
ot
he
rs
ph
ra
sa
l
on
ey
m
ca
us
at
iv
e
ic
al
de
le
x
co
re
160
140
120
100
80
60
40
20
0
NNS writing
NNS speech
13
Delexical uses of make
Overall frequency (/100,000 words):

Speech
Writing
Speech vs
writing
NS
28.7
120.9
28.7 < 120.9
NNS
42.9
80.9
42.9 < 80.9
NS vs NNS
28.7 < 42.9
120.9 > 80.9
significantly (***) less frequent in NS speech than in NS writing
significantly(***) less frequent in NNS speech than in NNS writing
 significant (*) overuse in NNS speech


highly significant (***) underuse of make in NNS writing
14
Delexical uses of make

NNS writing: underuse of EAP delexical structures (make
a case, make a statement)


maybe register-related
NNS speech: overuse of delexical uses

probably communication strategy (pressure, online
processing, make as default verb):
 especially one course we have to make erm . a kind of work
 when I go . eat em . with my master the: the cooking he
made for us is just er .
 about er .. an .. experience which I .. made when I was in
first candi
15
Causative uses of make
Overall frequency (/100,000 words):

Speech
Writing
Speech vs
writing
NS
64.9
142.1
64.9 < 142.1
NNS
24.2
102.6
24.2 < 102.6
NS vs NNS
64.9 > 24.2
142.1 > 102.6
significantly (***) less frequent in NS speech than in NS writing
significantly(***) less frequent in NNS speech than in NNS writing
 significant (***) underuse in NNS speech


significant (**) underuse in NNS writing
16
Causative uses of make

underuse of causative structures as a whole in learner
language (both in speech and in writing)

3 causative structures:
•
•
•
make + adjective (make sth easier)
make + verb (make someone feel bad)
make + noun (make someone an outcast)
17
The proportion of each category is remarkably
similar for NS and NNS registers
NS writing
NNS
writing
NS speech
NNS
speech
Adjective
57%
57.6%
39%
40.9%
Verb
30%
32.7%
54.5%
50%
Noun
13%
9.7%
6.5%
9.1%
Total
100%
100%
100%
100%
18
Some previous findings about make:
1.
2.
French-speaking and Swedish-speaking learners
underuse make in delexical structures (Altenberg &
Granger 2001, Altenberg 2001)
Swedish-speaking learners overuse causative make
+ adj and make + verb (Altenberg 2002a, 2002b)
(Partially) L1-related explanations:
1.
2.
delexical structures: avoidance strategy due to
arbitrary and L1-specific choice of the verb
causative structures: transfer of frequency from L1 +
overgeneralisation
19
Plausible register-related explanation?
delexical combinations:yes.
1.
•
Transfer and register have a similar impact. Underuse of
delexical structures in NNS writing: much less frequent in NS
speech than in NS writing: possible transfer of frequency from
target language speech
causative structures: no (at least not for Swedish-speaking
learners).
2.
•
•
•
Transfer and register seem to pull in opposite directions:
L1 Swedish causes overuse of L2 English ADJ and VERB
causative structures
English speech uses fewer causatives structures, so poor register
awareness is not a valid explanation for the Swedish-speaking
NNS’observed overuse of causative structures.
20
To sum up:
Make is a multi-faceted verb with many meanings,
functions, and patterns: a very interesting picture of
scale of proficiency of advanced interlanguage emerges



from no knowledge at all (e.g. some phrasal verbs, link verb uses,
‘money’ make are nearly absent)
to near-perfect knowledge (e.g. proportions of 3 causative syntactic
structures)
including various levels of partial knowledge (e.g. core uses, delexical
uses, overall frequency of causative uses, etc.)
 knowing a word is not an all-or-nothing matter
21
Methodological implications


The results can be partially skewed by one part of
the interview:
e.g. for the core meaning of make (= produce,
create), overuse in LINDSEI-FR due to picture
description task
 NS: do/draw a portrait, do/paint a picture
 he

paints the picture of a beautiful woman
NNS: make a portrait/a drawing/ a picture
 there
is a painter he’s making a portrait the portrait
of a of a girl
22
Methodological implications

e.g. for the causative make + V structure, in LOCNEC
16 instances/42 involve look:





he’s now repainting it making her look . much more attractive
he makes her look . totally different makes her look very
glamorous
clearly topic-induced by picture description which
elicits predictable patterns
bears unduly on the overall results for that category
not mirrored in LINDSEI-FR (1/11)
 probably more appropriate to study the picture
description (elicited) separately from the more
spontaneous tasks
23
Where to from here? Possible avenues for
further research



Complement quantitative analysis of native English HFVs by carrying
out a similar analysis on learner data (requires preparation of the data,
e.g. tagging of LINDSEI)
Combine corpus data with other types of data (e.g. elicitation)
Complement qualitative analysis of make by carrying out similar
analyses of other HFVs


reach better understanding of how these complex verbs are gradually
acquired in the interlanguage system
Study other variables:


L1: Carry out transfer analysis on the same data + other learner populations
Proficiency: longitudinal approach (data from other proficiency levels)
 also help to understand the gradual evolution of the interlanguage system
in time
24
Thank you!
25