5. Análisis de resultados
5.2 Regresión lineal
In this section I will address Research Question 1d) What factors in the immediate linguistic context (i.e. the clause) best account for the variation between the forms in each context? The data sets were coded for a number of factor groups, the motivations for which were discussed in Chapter 5 (§5.5). The factors remaining, after exclusions (see §5.5.4), are lexical aspect, sentential aspect, subject person, subject number, object number and transitivity. Since transitivity nearly categorically restricts the use of Ving in the HOME data (to intransitive contexts), it can only be run on the SCHOOL data. I’ll
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% Lenora [N=96] Alysha [N=113] Tiffany
[N=90] Deanna [N=85] [N=126]Simon [N=146]Shamus
Vbat Ving V 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% Alysha
[N=22] Lenora [N=69] [N=35]Daniel Tiffany [N=70] [N=62]Simon Deanna [N=16] Shamus [N=32]
Ving V
first briefly discuss how some of these factor groups required re-working in light of patchy distributions.
When cross-tabulating each factor group with each other, it was discovered that, in both
HOME and SCHOOL contexts, stative verbs do not appear in clauses with habitual/iterative
aspectual semantics8, as shown in the grey cells of Table 6-10. There are a number of
possible explanations for this. It could be a vestige of the coding system wherein ‘durativity’ is potentially coded twice: once as a defining feature of ‘states’ at the lexical level and as a type of sentential aspect9. However, Walker (2000; 2010) using the same
coding system for his early African American English datasets, does find stative verbs with habitual/iterative verbs, so it is not a necessary outcome of this coding structure. A second possibility is that this restriction of statives to durative/continuous (and
punctual) clauses is a feature of child language, or of the particular language varieties under examination here (i.e. it could be reflected in adult Alyawarr English or learner varieties of English more broadly). Thirdly, it could be the result of sampling
inadequacies; that this combination of ‘stative + habitual/iterative aspect’ has just not naturally arisen in the corpus.
Table 6-10: Cross-tabulation of lexical aspect and sentential aspect distributions, HOME and SCHOOL contexts
Sentential Aspect
Context Lexical Aspect Durative/Continuous Habitual/Iterative
Home Stative 164 1
Non-stative 264 105
School Stative 98 0
Non-stative 159 52
Whatever the reason, it is necessary to resolve the lack of independence of these two factor groups, by collapsing statives and sentential durativity into a single factor group. The ‘combined aspect’ factor group now has three factors: Stative durative/continuous (shortened to Stative Durative), Non-stative Durative/Continuous (shortened to Non- stative Durative), and Non-stative Habitual/Iterative (shortened to Non-stative Habitual).
8 An example of a lexically stative verb used in a clause with habitual semantics in English would be ‘I love a good red
every Friday night’ or ‘We always see birds at the creek’
9 Stative verbs did also occur in clauses with punctual aspectual semantics, which had been excluded from analysis
The subject animacy coding also had to be refined. As displayed in Table 6-11 and Table 6-12, the breakdown of 3rd person into the three animacy levels resulted in untenably
low token counts in a lot of the cells, particularly inanimates. As a result, it was decided then to collapse these into the one ‘3rd Person’ category and contrast this with the 1st/2nd
person/Speech Act Participant (SAP) factor, to form a 2-level subject person factor group. This is justified by the data: in all but one case all the 3rd person levels (Human,
Animate and Inanimate) behave the same way with respect to whether they favour or disfavour the verb form. For example, in the HOME data, SAPs disfavour the Ving form
(since the overall rate of occurrence of Ving in the data set is 24%—with respect to this factor group—but the incidence of Ving decreases to 16% in clauses with 1st/2nd person
subjects). Only the patterning for HOME context inanimates runs contrary to the trend,
since it favours the use of V (55%, against an overall rate of 40%), while the other 3rd
person contexts disfavour it (human 25% and animate 34%).
Table 6-11: Distribution of V, Ving and Vbat per SUBJECT PERSON, HOME context
[significant (SAP v. 3p) χ2(2, N=564)=34.9143, p<.001]
V Ving Vbat Total
% N % N % N 1st/2nd Person (SAP)10 44 153 16 55 41 143 351 3rd person 33 70 38 80 30 63 213 Human 25 31 38 47 37 45 123 Animate 34 17 42 21 24 12 50 Inanimate 55 22 30 12 15 6 40 Total 40 223 24 135 37 206 564
Note: Unexpressed subjects or otherwise un-codeable tokens excluded [N=103]
10 The breakdown of SAP per person/number is as follows: 1sg N=225, 1pl N=21, 2sg N=85, 2pl N=20. The majority
of tokens are therefore 1sg, followed by a substantial proportion of 2sg. These pattern the same way as each other when compared to 3rd person.
Table 6-12: Distribution of V and Ving per SUBJECT PERSON, SCHOOL context [significant (SAP v. 3p) χ2(1, N=268)=51.9581, p<.001] V Ving Total % N % N 1st/2nd Person (SAP)11 72 96 28 37 133 3rd person 28 38 72 97 135 Human 23 17 77 56 73 Animate 35 8 65 15 23 Inanimate 33 13 67 26 39 Total 50 134 50 134 268
Note: Unexpressed subjects or otherwise un-codeable tokens excluded [N=53]
After these reconfigurations, the factors now available for the variable rule analysis are combined (sentential and lexical) aspect, subject person, subject number, object number (transitive clauses only) and transitivity (SCHOOL data only). I’ll first examine the HOME
data, followed by the SCHOOL data.
The variant that occurs with about the same frequency in HOME transitive (46%) and
intransitive clauses (39%) is V. Table 6-13 shows the results of two variable-rule analyses (VRAs) comparing V in transitive (left section) and intransitive (right section) clauses. The ‘input’ probabilities of .41 (transitive) and .38 (intransitive) indicate the “overall tendency for the dependent variable to surface in the data” (Tagliamonte 2012:127. See also Young & Bailey 1996) or in other words, represents the likelihood that the variant V will occur (as opposed to Ving and Vbat) in the whole HOME data set. The corrected
mean should be similar to the overall raw rates (given in brackets). Changes in this global input value in comparative analyses have been interpreted as reflecting a change in dominance of the form within the variable system (e.g. Tagliamonte & D’Arcy 2007). The arrangement of factor groups in this table reflects their relative contribution to the overall variation (from top to bottom)12. Aspect accounts for most of the variation out of
the factor groups tested in both the transitive and intransitive data. Subject person is also significant for the transitive data, but not the intransitive data (as indicated by the square brackets instead of factor probabilities). Subject number was not significant for
11 The breakdown of SAP per person/number is as follows: 1sg N=99, 1pl N=11, 2sg N=19, 2pl N=4. The majority of
tokens are therefore 1sg. All of these pattern the same way as each other when compared to 3rd person. 12 As indicated by the range. Both the range, and the order in which factors are added to the model during the
statistical analysis are indicative of their relative strength and the two should coincide (and they do in each VRA presented in this thesis). By convention, the order presented in the tables reflects the range.
either data set, nor was object number for the transitive data (not run in the intransitive data).
Table 6-13: Two variable-rule analyses of the contribution of various factors to the choice of V against other verb forms, transitive (~Vbat) and intransitive (~Vbat and Ving), HOME context.
Vtransitive V intransitive
input (overall rate) .41 (46%) .38 (39%)
total N 345 302 Prob. %V N Prob. %V N Aspect Stative Durative .75 68 103 .71 60 57 Non-stative Durative .54 48 90 .43 32 184 Non-stative Habitual13 .21 18 67 0% Range = 54 Range = 28 Subject Person SAP .51 44 213 [ ] 47 125 other (3rd Person) .48 25 67 [ ] 27 140 Range = 3 Subject Number Singular [ ] 43 253 [ ] 40 212 Plural/Mass [ ] 36 31 [ ] 40 57 Object Number Singular [ ] 50 154 Plural/Mass [ ] 40 37
The first column in each section (labelled ‘Prob.’, an abbreviation of ‘probability’) shows the probability value returned by the logistic regression analysis. A value closer to 1 indicates favouring of V, and a value closer to 0 indicates that V is disfavoured. Probabilities that significantly favour the variant are given in bold for ease of reading. For example, in transitive clauses Stative Durative aspect favours the use of V forms, returning the probability of .75. In the next column (here titled ‘%V’), the raw percentage of V tokens in that condition is given: the rate of V in Stative Durative transitive verbs is 68%. In the final column (titled ‘N’) the total number of tokens (of all verb types) for that condition is given: the number of Stative Durative transitive clauses (both marked V and Vbat) is 103. This same pattern is replicated in intransitive clauses, where V (now compared to both Vbat and Ving combined) is favoured by Stative
13 Note that there are no Non-stative Habitual-Iterative clauses in the intransitive data. This is not true of the SCHOOL
data, as we’ll see below. A possible explanation for this is that the HOME data is (impressionistically) more ‘iterative’
than ‘habitual’ (recall that the factor groups is actually ‘habitual/iterative’), whereas the SCHOOL data is not. In the HOME play contexts iterative acts were often repeated actions within the context of one toy acting on another (e.g. in the game of knights there was some ‘battling’), which tend to be transitive. The SCHOOL data contained more
genuinely habitual discussion, in particular one activity describing the advantages of going hunting. I see this as a discrepancy more likely due to sampling, than a natural language fact.
Durative aspect, with a probability of .71 (rate of 60%). In the transitive data, Non- stative Durative contexts appear to mildly favour V as well, with a probability of .54, while this condition disfavours the use of V in intransitive clauses (probability of .43). The probabilities of V occurring in each of these three aspectual conditions, in both the transitive and intransitive data, is graphed in Figure 6-8.
Figure 6-8: Probabilities of V occurring in three aspectual conditions, HOME transitive and HOME intransitive contexts. (Data from Table 6-13)
Subject Person is also a significant factor group to the choice of transitive V, although the probabilities are very close to .50 (SAP = .51; other = .48) so it is not possible to draw
a confident conclusion regarding the direction of effect based on the probabilities alone14. However, the percentages demonstrate that the same direction of effect in both
the transitive and intransitive data sub-sets. Moreover the impact of subject person is much lower than aspect in both data sub-sets: in the intransitive data it does not even
reach significance, and in the transitive data the range is very low. This is also the opposite of what we see for Vbat, below, as is expected. As stated above, no other factor
groups were significant.
When variables of only two variants are entered into a variable rule analysis, the output is presented in terms of only one of those variables. In the left section of Table 6-13 transitive V was run against transitive Vbat, but the results were expressed in terms of
14 I will take the cautious approach of refraining from concluding directionality for probabilities in the range of .45 to
.55 0 0,1 0,2 0,3 0,4 0,5 0,6 0,7 0,8 0,9 1
Stative Durative Habitual
V. The results for Vbat are in fact the inverse of results for V, and so can also be inferred from this table. So Vbat is strongly favoured in Non-stative Habitual/Iterative
conditions, with the probability the inverse of that for V in this condition (i.e. 1 - .21 =
.79; rate of82%)15. This supports the hypothesis, derived from descriptions of Kimberly
Kriol, that Vbat expresses specific iterative semantics. As with the results for V, the results for Vbat are also inconclusive for directionality in Non-Stative Durative aspect, and with respect to Subject Person (since the probabilities are close to .50). The variable grammar of the aspect portion of the HOME transitive data is graphed in Figure 6-9. The
vertical axis plots the probabilities retrieved from the regression analyses presented in Table 6-13 (left section), and the horizontal axis contains the three aspect conditions: Stative (Durative), (Non-stative) Durative, and (Non-stative) Habitual. This graph clearly shows the strong favouring of V in stative clauses, and Vbat in habitual clauses, with durative clauses containing close to the same rate of both V and Vbat forms.
Figure 6-9: Probabilities of V and Vbat occurring in three aspectual conditions, HOME transitive
contexts. (Data from Table 6-13)
Now that I have examined V (transitive and intransitive) and transitive Vbat, what about intransitive Vbat? To find out what Vbat is doing in intransitive clauses, another variable-rule analysis is needed, because in the above analysis intransitive V is run against the combined Ving and Vbat data. The following analysis, presented in Table 6-14, separates out Ving and Vbat in intransitive clauses, and allows us to see on what grounds speakers make a choice between them in the HOME intransitive contexts. Ving
15 Similarly, the rate of incidence can be determined as 100-68=32%. The N is the same.
0 0,1 0,2 0,3 0,4 0,5 0,6 0,7 0,8 0,9 1
Stative Durative Habitual
is the ‘application variant’ which means results are presented in terms of it, with the results of Vbat derivable as the inverse. Ving is the more dominant variant over Vbat in intransitive clauses, with an overall rate of use of 70%, adjusted to .82 in the model. The results per factor group indicate that even though Ving is more likely to be used overall in intransitive clauses, the likelihood is higher still in some situations. There are three clausal elements for which this discrepancy between Ving and Vbat was found to be significant: aspect, subject person, and subject number. As noted above, the
arrangement of factor groups in this table reflects their relative contribution to the overall variation (from top to bottom). Aspect makes the strongest contribution (Range = 42), with the other factor groups coming in with range values less than half that of aspect (subject person Range = 24; subject number Range = 15).
Table 6-14: Variable-rule analysis of the contribution of various factors to the choice of Ving (against Vbat) in HOME intransitive contexts.
input (overall rate) .82 (70%)
total N 183 Prob. %Ving N Aspect Stative Durative .16 48 23 Non-Stative Durative .58 86 125 Non-stative Habitual 0% Range = 42 Subject Person SAP .36 64 66 other .60 80 93 Range = 24 Subject Number Singular .53 74 128 Plural/Mass .38 65 34 Range = 15
First, I will examine aspect. Clauses with Non-Stative Durative aspect mildly favour the choice of Ving (prob=.58; rate of 86%)16, while clauses with Stative Durative aspect
strongly favour Vbat (prob=.84; rate of 52%). Recall above that V is also favoured in intransitive clauses of Stative Durative aspect (when compared to both Ving and Vbat), so there appears to be some job sharing between V and Vbat here.
16 While the rate is 86% for this factor, recall that the overall rate of Ving in the intransitive data set is 70% (compared
to Vbat). This overall rate is therefore the yardstick against which each factor is measured: 86% is not that much higher than 70% resulting in a probability of .58 for this factor (i.e. above the mid-point .50, but not great in magnitude).
Subject Person is also significant, with speech act participants (SAPs) favouring Vbat (prob=.64; rate of 36%), and non-SAP subjects favouring Ving (prob=.60; rate of 80%). The finding that Ving is associated with non-SAP subjects concurs with the results of Walker (2000), whose coding for this factor was inspirational in including it here. The alignment of Ving with both durative aspect and non 1st and 2nd person subjects (and the
inverse, that Vbat aligns with stativity and 1st/2nd person pronouns), could reflect a
discursive tendency for speakers to comment on one’s own states (which favour Vbat), and other’s actions.
Subject number is also significant with plural/mass subjects favouring Vbat (prob=.62; rate of 35%). Recall that part of the analysis of Vbat in Kimberley Kriol was that
iterativity in the clause could arise from plural participants, and the Vbat ending would respond to this. It seems when there is a direct choice between Ving and Vbat, this might be the case here. The findings from the three factor groups are represented graphically in Figure 6-10.
Figure 6-10: Probabilities of Ving and Vbat occurring in three aspectual conditions, two subject person conditions and two subject number conditions, HOME intransitive contexts. (Data from
Table 6-14).
When the results for intransitive Vbat and Ving are combined with those for
intransitive V17, the following picture (graphed in Figure 6-11) of the variable grammar
17 Note that when intransitive Ving was run against the combination of intransitives V + Vbat, the results were very
similar to the results presented here (where Ving is only compared to Vbat). When intransitive Vbat was run against the combination of intransitives V + Ving, the model failed to converge, likely because of the large discrepancy in tokens of the application and non-application variants that this produced (the combination of V+Ving [N=248]
0 0,1 0,2 0,3 0,4 0,5 0,6 0,7 0,8 0,9 1
Stative Durative Habitual
Aspect Vbat Ving 0 0,1 0,2 0,3 0,4 0,5 0,6 0,7 0,8 0,9 1 SAP other Subject Person Vbat Ving 0 0,1 0,2 0,3 0,4 0,5 0,6 0,7 0,8 0,9 1 singular plural Subject Number Vbat Ving
of the aspect portion of the HOME intransitive data is visible. Speakers are more likely to
choose V in Stative Durative clauses (over Ving or Vbat), but when speakers want to use an aspectual marker like Ving or Vbat, they are more likely to choose Vbat in stative contexts. A verb with an aspectual marker (Ving or Vbat) is more likely to be chosen in Non-stative Durative clauses than a V form, but when the choice between these forms is modelled, Ving is the more likely form.
Figure 6-11: Probabilities of V, Vbat and Ving occurring in two aspectual conditions, HOME
intransitive contexts. (Data from Table 6-13 and Table 6-14.)
In summary, the HOME system is fundamentally divided per transitivity, with Ving only
appearing on intransitive verbs. Likewise, Vbat is a minor form in intransitive clauses. This asymmetry is suggestive of a categorical transitivity split potentially in
development in the children’s L1 grammar (this will be discussed further below). Table 6-15 presents a summary of the findings of the three variable-rule analyses discussed above. In transitive clauses, V is most closely associated with Stative Durative aspect, and Vbat with the Habitual aspect condition. The results were inconclusive regarding transitive Non-Stative Duratives, and it is this factor which most strongly aligns with Ving in the intransitive data. In the absence of any intransitive Non-stative Habitual clauses in the sample, V and Vbat are both significantly associated with Stative Durative clauses. Subject Person and Subject number provide a basis on which speakers choose between Ving and Vbat in intransitive clauses.
resulted in 5 times as many tokens than Vbat [N=54]). Because of this, and also because it seems plausible that speakers choose directly between Ving and Vbat, I continue to use the model that first puts V against (Ving+Vbat), and then directly compares Ving to Vbat.
0 0,1 0,2 0,3 0,4 0,5 0,6 0,7 0,8 0,9 1
Stative Durative Habitual
Table 6-15: Summary of favoured verb forms in each factor condition, HOME context.
Transitive Intransitive
V~Vbat V~{Ving~Vbat}*
Aspect
Stative Durative V V / Vbat
Non-Stative Durative (V) Ving
Non-stative Habitual Vbat -
Subject Person
SAP (V) Vbat
other (Vbat) Ving
Subject Number
singular [ ] (Ving)
plural/mass Vbat
Notes: Bracketed () forms indicate that the probability is within the range of .45-.55.
Square brackets [] indicate the factor group is not significant.
*Results for Ving and Vbat are from direct comparison of Ving v. Vbat (rather than with V). See footnote 17.
Turning now to the SCHOOL data. Recall that by contrast to the HOME data, transitivity
does not categorically constrain any of the variants in the SCHOOL data. This means that
transitivity can be included in the variable-rule analysis to give some idea if it is still a