60
presented in Table 4.3 See also Appendix 3. The examples below illustrate the probability of the occurrence of instances possessing non-given and given
beneficiary.
1
a. getting work for the nonet non-given beneficiary more probable b. getting the nonet work
less probable 2
a. get men for the navy non-given beneficiary
more probable
b. get the navy men less probable
3
a. gets them given beneficiary a decent wage
more probable
b. gets a decent wage for them less probable
4
a. get you given beneficiary some drops
more probable
b. get some drops for you less probable
This result of the effect of givenness of beneficiary confirms the finding of the earlier studies on alternations. As non-given beneficiary favors benefactive PP
construction, it simply agrees the claim that given information precedes the non- given one in alternations Collins 1995; Bresnan
et al.
2007; Theijssen
et al.
2009. It puts the non-given information at the very end of the sentence, whereas the given information comes just after verb postverbal position.
Whereas beneficiary and theme should be in complement Bresnan 2007, the result suggests that the givenness of theme does not significantly
affect the choice of benefactive construction. The p value of the feature givenness of theme is 0.874 far from being significant. Its 95 confidence interval CI is
too way spread. It has lower limit less than 1 and the upper limit of 5.900. The coefficient is positive of 0.133 which cannot be said to be in balance with the
61
givenness of beneficiary See Table 4.3 and Appendix 3. Ideally, when the givenness of beneficiary possesses positive coefficient, the givenness of theme
should have negative coefficient. This way, the idea of given information preceding non-given will stay correct. However, this phenomenon is explainable
since the feature of givenness of theme is insignificant to the choice of benefactive construction.
Partially, the feature givenness of beneficiary has stronger effects on the choice of benefactive construction. When the feature of givenness of beneficiary
is tested in one on one binary logistic model, the classification table of the feature givenness of beneficiary toward the choice of benefactive alternation shows
83.8 of the model accuracy. Ignoring the other features, the feature givenness of beneficiary and the intercept are able to predict the occurrence of the benefactive
PP or double object construction with 83.8 accuracy. In addition, the omnibus and model summary tables support the idea by giving the evidence that the single
feature of givenness of beneficiary reduce the -2 log likehood of 246.260. The model with intercept only owns -2 log likehood of 535.883. while after adding the
variable of givenness of beneficiary the -2 log likehood decrease to 289.623. Applying the variable of givenness of beneficiary in the model will be able to
explain the choice of benefactive construction as Nagelkerke R square suggests of 0.623. The model fit accuracy, -2 log likehood, and Nagelkerke R square are
presented in Appendix 3. The coefficient and the odds ratio of the feature givenness of beneficiary increase considerably to 5.010 and 149.860 from the
ones when it was applied with the other thirteen features See the Table 4.5 below.
62
Variables in the Equation of beneficiary givenness
B S.E.
Wald df
Sig. ExpB 95 C.I.for
EXPB Lower Upper
Step 1
a
beneficiarygivenness 5.010
.601 69.429 1 .000 149.860 46.123 486.919
Constant -5.920
.655 81.614 1 .000
.003 a. Variables entered on step 1: beneficiarygivenness.
Table 4.5 Variable givenness of beneficiary removed from full model
4.1.2 Animacy of Beneficiary
The second significant feature
animacy of beneficiary
was coded to categorical variable in the logistic model beneficiary=animate is 1, and
beneficiary=inanimate is 2 See Appendices 1 and 2 for the detailed identification and annotating process of the benefactive data. The default of the
feature is inanimate, whereas the default of the benefactive construction is benefactive PP. The p value of the feature animacy of beneficiary reaches the
number 0.035 See Table 4.3 and Appendix 3 which is less than the conventional significance level 0.05. Thus, the feature animacy of beneficiary is proven to be
relevant to the choice of benefactive construction. The crosstabulation table of animacy of beneficiary toward ditransitivity
shows that 98 of inanimate beneficiary take benefactive PP construction, only the rest 2 of inanimate beneficiary take double object construction. Conversely,
51.8 of animate beneficiary take double object construction, and the rest 48.2 take benefactive PP construction. Both statistics say that animate argument comes
before inanimate one.
63
Animacy of Beneficiary toward Ditransitivity Crosstabulation
Ditransitivity Total
benefactive construction
prepositional construction
Animacy of Beneficiary
animate beneficiary
Count 155
144 299
within Animacy of Beneficiary 51.8
48.2 100.0 within Ditransitivity
98.7 59.3
74.8 of Total
38.8 36.0
74.8 inanimate
beneficiary Count
2 99
101 within Animacy of Beneficiary
2.0 98.0 100.0
within Ditransitivity 1.3
40.7 25.3
of Total .5
24.8 25.3
Total Count
157 243
400 within Animacy of Beneficiary
39.3 60.8 100.0
within Ditransitivity 100.0
100.0 100.0 of Total
39.3 60.8 100.0
Table 4.6 Crosstabulation of animacy of beneficiary toward ditransitivity
In addition, the result shows that the feature animacy of beneficiary possesses positive coefficient B of 2.268. It means that the default inanimate
beneficiary favors the default benefactive PP construction. The size of the effect of the feature is explainable through the odds ratio expB of 9.657. It suggests
that inanimate beneficiary is more than 9 times likely to take benefactive PP construction rather than animate beneficiary. The 95 confidence interval CI
supports the claim, showing that inanimate beneficiary tends to choose benefactive PP construction between 1.175 to 79.383 times. Conversely, if the
beneficiary is animate, the sentence will tend to appear in the double object construction. The coefficient B, odds ratio expB, and 95 CI above are
presented in Table 4.3 See also Appendix 3. The examples below illustrate the
64
probability of the occurrence of instances possessing inanimate and animate beneficiary.
4
a. getting water for their shipping inanimate
more probable
b. getting their shipping water less probable
5
a. getting funding for clinical trials inanimate
more probable
b. get clinical trials funding less probable
6
a. get thee animate a wife
more probable
b. gets a wife for thee less probable
7
a. get you animate anything
more probable
b. get anything for you less probable
This result of the effect of animacy of beneficiary confirms the finding of the earlier studies on alternations. As inanimate beneficiary favors benefactive PP
construction, it simply agrees the claim that animate argument precedes inanimate one in alternations Bock
et al
1992; Thompson 1995; Bresnan and Hay 2008; Lamers
et al.
2008; Theijssen
et al.
2009. The benefactive PP puts inanimate argument, which is the beneficiary, after the postverbal NP position in
the end of the construction. Beneficiary and theme should be in complement Bresnan 2007 and the
result suggests the same way. Although animacy of theme does not significantly affect the choice of benefactive construction, its relation with animacy of
beneficiary is in harmony. The coefficient of animacy of theme is negative of - 1.055 which implies that animate theme favors benefactive PP construction. On
the other hand, the coefficient of animacy of beneficiary is as we know positive of
65
2.268, thus inanimate beneficiary favors benefactive PP. This way, the statistic show balance in the way animate theme choosing benefactive PP and inanimate
beneficiary choosing benefactive PP construction. This combination left the fact that the animate argument precedes the inanimate one.
Partially, the feature animacy of beneficiary also has strong effect although doubtfully accurate toward the choice of benefactive construction. When the
feature of animacy of beneficiary is tested in one on one binary logistic model, the classification table of the feature beneficiary of beneficiary toward the choice of
benefactive alternation shows 63.5 of the model accuracy. Ignoring the other features, the feature animacy of beneficiary and the intercept are able to predict
the occurrence of the benefactive PP or double object construction with 63.5 accuracy. In addition, the omnibus and model summary tables support the idea by
giving the evidence that the single feature of animacy of beneficiary reduce the -2 log likehood of 102.137. The model with intercept only owns -2 log likehood of
535.883, while after adding the variable of animacy of beneficiary the -2 log likehood decrease to 433.745. Applying the variable of animacy of beneficiary in
the model will only be able to explain the choice of benefactive construction as Nagelkerke R square suggests of 0.305. The model fit accuracy, -2 log likehood,
and Nagelkerke R square are presented in Appendix 3. The coefficient and the odds ratio of the feature givenness of beneficiary increase significantly to 3.976
and 53.281 from the ones when it was applied with the other thirteen features See Table 4.7 below.
66
Variables in the Equation of Beneficiary Animacy
B S.E.
Wald df
Sig. ExpB
95 C.I.for EXPB
Lower Upper
Step 1
a
beneficiaryanimacy 3.976
.724 30.192
1 .000
53.281 12.903 220.011
Constant -4.049
.751 29.087
1 .000
.017 a. Variables entered on step 1: beneficiaryanimacy.
Table 4.7 Variable animacy of beneficiary removed from full model
4.1.3 Pronominality of Theme
The next significant feature
pronominality of theme
was coded to categorical variable in the logistic model theme=pronoun is 1, and theme=non-
pronoun is 2 See Appendices 1 and 2 for the detailed identification and annotating process of the benefactive data. The default of the feature is non-
pronoun, whereas the default of the benefactive construction is benefactive PP. The p value of the feature pronominality of theme reaches the number 0.010 See
Table 4.3 and Appendix 3 which is less than the conventional significance level 0.05. Thus, the feature pronominality of theme is proven to be relevant to the
choice of benefactive construction. The crosstabulation table of pronominality of theme toward ditransitivity
shows that 91.7 of pronoun theme take benefactive PP construction, only the rest 8.3 of pronoun theme take double object construction. However,
benefactive construction is not sensitive toward non-pronoun theme. The result shows that 57.7 of non-pronoun themes take benefactive PP construction, and
67
the rest 42.3 take double object construction. The statistic of pronoun theme strongly suggests that as possible pronoun appears in postverbal position.
Pronominality of Theme toward Ditransitivity Crosstabulation
Ditransitivity Total
benefactive construction
prepositional construction
Pronominality of Theme
pronoun theme
Count 3
33 36
within Pronominality of Theme 8.3
91.7 100.0 within Ditransitivity
1.9 13.6
9.0 of Total
.8 8.3
9.0 non-
pronoun theme
Count 154
210 364
within Pronominality of Theme 42.3
57.7 100.0 within Ditransitivity
98.1 86.4
91.0 of Total
38.5 52.5
91.0 Total
Count 157
243 400
within Pronominality of Theme 39.3
60.8 100.0 within Ditransitivity
100.0 100.0 100.0
of Total 39.3
60.8 100.0
Table 4.8
Crosstabulation of pronominality of theme toward ditransitivity
The table of variables in the equation shows that the feature pronominality of theme possesses negative coefficient B of -2.183. It means that the non-
default pronoun theme favors the default benefactive PP construction. The size of the effect of the feature is explainable through the odds ratio expB of 0.113. It
suggests that pronoun theme is 0.113 times to take non-default double object construction or around 9 times likely to take benefactive PP construction. Given
100 occurrences of pronoun theme, 11 will likely take double object construction, while 89 instances favor benefactive PP construction. The 95 confidence
interval CI supports the claim, showing that pronoun theme tends to choose
68
double object construction between 0.022 to 0.588 times. It means that pronoun theme tends to take benefactive PP construction between almost 2 times and more
than 45 times. In line with this fact, if the theme is non-pronoun, the sentence tendency to appear in the double object construction is bigger than if the theme is
pronoun. The coefficient B, odds ratio expB, and 95 CI above are presented in Table 4.3 See also Appendix 3. The examples below illustrate the
probability of the occurrence of instances possessing non-pronoun and pronoun theme.
9
a. play them pronoun theme for us
more probable
b. play us them unacceptable
10
a. fix it pronoun theme for you
more probable
b. fix you it unacceptable
11
a. get him a shirt non-pronoun theme
more probable
b. get him it unacceptable
12
a. fixing herself some food non-pronoun theme
more probable
b. fixing herself them unacceptable
While the previous studies suggest that in double object construction, pronoun precedes a lexical NP are far more frequent than those in which two
lexical NPs occur Thompson 1990; Collins 1995; Bresnan
et al
2007, this study suggests that when 2 pronouns occur, the theme will come first. As pronoun
theme favors benefactive PP construction, the beneficiary will be positioned after the theme. It means that even when the beneficiary is a pronoun, it should come
after the pronoun theme which comes postverbal.
69
Beneficiary and theme should be in complement Bresnan
et al.
2007 and the result suggests the same way. Although pronominality of beneficiary does
not significantly affect the choice of benefactive construction, its relation with pronominality of theme is in harmony. The coefficient of pronominality of
beneficiary is positive of 1.577 which proposes that non-pronoun beneficiary favors benefactive PP construction. On the other hand, the coefficient of
pronominality of theme is as we know negative of -2.183. This way, the statistic shows balance where non-pronoun beneficiary chooses benefactive PP and
animate theme chooses benefactive PP construction. In benefactive PP construction with pronoun theme and non-pronoun beneficiary, pronoun precedes
non-pronoun. Partially, the feature pronominality of theme has relatively weak effect and
doubtfully accurate toward the choice of benefactive construction. When the feature of pronominality of theme is tested in one on one binary logistic model,
the classification table of the feature pronominality of theme toward the choice of benefactive alternation shows 60.8 of the model accuracy. Ignoring the other
features, the feature pronominality of theme along with the intercept are able to predict the occurrence of the benefactive PP or double object construction with
63.5 accuracy. In addition, the omnibus and model summary tables suggest that the single feature pronominality of theme is quite weak to determine the choice of
benefactive alternation. The evidence shows that the single feature of pronominality of theme only reduces the -2 log likehood of 19.269. The model
with intercept has -2 log likehood of 535.883, while after adding the variable of pronominality of theme the -2 log likehood decreases only 19.269 to 516.614.
70
Applying the variable of pronominality of theme in the model will only be able to explain the choice of benefactive construction as Nagelkerke R square suggests of
0.064. The very small number of Nagelkerke R square tell us that when appears alone, pronominality of theme is barely able to explain the choice of benefactive
construction. The model fit accuracy, -2 log likehood, and Nagelkerke R square are presented in Appendix 3. The coefficient and the odds ratio of the feature
pronominality of theme is stable at around -2 and 0.1 to -2.088 and 0.124 from the ones when it was applied with the other thirteen features.
Variables in the Equation of Theme Pronominality
B S.E.
Wald df
Sig. ExpB 95 C.I.for
EXPB Lower Upper
Step 1
a
themepronominality -2.088
.612 11.626 1
.001 .124
.037 .412
Constant 4.486
1.211 13.727 1
.000 88.733 a. Variables entered on step 1: themepronominality.
Table 4.9 Variable pronominality of theme removed from the full model
4.1.4 Definiteness of Theme
The next significant feature
definiteness of theme
was coded to categorical variable in the logistic model theme=definite is 1, and theme=indefinite is 2
See Appendices 1 and 2 for the detailed identification and annotating process of the benefactive data. The default of the feature is indefinite, whereas the default
of the benefactive construction is benefactive PP. The p value of the feature definiteness of theme reaches the number 0.04 See Table 4.3 and Appendix 3
which is less than the conventional significance level 0.05. Thus, the feature
71
definiteness of theme is proven to be relevant to the choice of benefactive construction.
The crosstabulation table of definiteness of theme toward ditransitivity shows that 87.7 of definite theme take benefactive PP construction, only the rest
12.5 of definite theme take double object construction. On the other hand, the effect of indefinite theme seems to be a little bit weaker toward benefactive
construction. The result shows that 56.3 of indefinite themes take double object construction construction, and the rest 43.7 take benefactive PP. The statistic of
definiteness of theme suggests that as possible definite argument appears in before indefinite one.
Definiteness of Theme toward Ditransitivity Crosstabulation
Ditransitivity Total
benefactive construction
prepositional construction
Definiteness of Theme
definite theme
Count 19
136 155
within Definiteness of Theme 12.3
87.7 100.0 within Ditransitivity
12.1 56.0
38.8 of Total
4.8 34.0
38.8 indefinite
theme Count
138 107
245 within Definiteness of Theme
56.3 43.7 100.0
within Ditransitivity 87.9
44.0 61.3
of Total 34.5
26.8 61.3
Total Count
157 243
400 within Definiteness of Theme
39.3 60.8 100.0
within Ditransitivity 100.0
100.0 100.0 of Total
39.3 60.8 100.0
Table 4.10 Crosstabulation of definiteness of theme toward ditransitivity
72
The result in the table of variables in the equation shows that the feature pronominality of theme possesses negative coefficient B of -1.340. It means that
the non-default definite theme favors the default benefactive PP construction. The size of the effect of the feature is explainable through the odds ratio expB of
0.262. It suggests that definite theme is 0.262 times to take non-default double object construction or around 4 times likely to take benefactive PP construction.
Given 100 occurrences of definite theme, 26 will likely take double object construction, while 74 instances favor benefactive PP construction. The 95
confidence interval CI supports the claim, showing that definite theme tends to choose double object construction between 0.105 to 0.656 times. It means that
definite theme tends to take benefactive PP construction between almost 2 times and more than 9 times. Equally, if the theme is indefinite, the sentence tendency to
appear in the double object construction is bigger than if the theme is definite. The coefficient B, odds ratio expB, and 95 CI above are presented in Table 4.3
See also Appendix 3. The examples below illustrate the probability of the occurrence of instances possessing indefinite and definite theme.
13
a. fixed the dinner definite theme for her family
more probable
b. fixed her family the dinner less probable
14
a. make the frames definite for Dodge Ram pickup more probable b. make Dodge Ram pickup the frames
less probable 15
a. get me a stove indefinite theme
