The figure given by log. likelihood
must be in relation to the maximum amount proposed by the programme under Maximum possible
likelihood. If these two figures are similar, then this is an initial guarantee that the
theory fits and that the rule is actually in place.
The second
test c2, seen earlier in the U&D, is used in many statistical analyses. The amount
required to find out whether the results fit the theory is that following the letter p;
the closer it is to 0, the more reliable the rule.
Finally, the
scattergram of the data presents these results as a diagram. If the points of convergence
between the theoretical model and the real data follow the line of the diagram, the
confidence level of the analysis is very high.
It is clear
from this brief introduction that, in order to obtain an analysis with a high confidence
level using the Goldvarb programme, we need to present the Input of application of the
initial rule and one of the tests guaranteeing the likelihood of the theoretical model
constructed from the iteration of independent variables. Subsequently, we can move on to
interpret the data, which is always related to the figure, 0.5. Thus, we can determine
when a factor favours the presence of the initial rule (in this case, maintenance of the
solution [a]) and when it does not facilitate application of the initial rule, as seen
with factors o (of the variable 1) and 4, 5 and 6 (of the variable 3).
Finally, it is
important to bear in mind that, although probabilistic analysis enables us to observe
future tendencies, it does not provide an exhaustive analysis of all possible combinations
of factors. It is therefore often interesting to complete the analysis by cross tabulating
factors to detail the connections of the percentages obtained on each independent factor
according to the different crossovers of variables. One of the applications of the above
programme allows the creation of crosstables of factors using the cross tabulation
instruction, once the condition, cell and results files have been created. Thus, Goldvarb
permits analysis of different features using the same initial classification of data.
5. Goldvarb in variationist
sociolinguistics
Variationism
has taken significant steps towards adapting a method capable of providing rigorous
analyses and reliable linguistic interpretations, and the Goldvarb programme is one of the
results.
As we have
seen, this programme enables us to obtain descriptive statistics and to find out the
inference statistics of variable phenomena very accurately. However, we need to be aware
beforehand of the factors susceptible to variation (which can arise from
phonetic/phonological, morphological, lexical, semantic or syntactic elements of grammar)
and, above all, we need to know how to find the linguistic and extralinguistic factors
that can explain, in one way or another, the different variable phenomena. To reach these
intuitions, we need to carry out prior qualitative analyses on the variation and nature of
the diverse phenomena to be analysed.
While finding
the variable and explanatory factors of variation is important, knowing how to combine
these adequately in order to obtain the most representative results of the variable
reality is no less relevant. This means that we need to look and, eventually, know how to
find the best combination of explanatory factors which is very often reached by redoing
the analysis time and time again.
In short, the
Goldvarb programme allows us to explain any process of variation, so long as the initial
theory is good and is accompanied by a series of factors capable of bearing it out.
6. Bibliography
CARRERASABATÉ,
J. (1999) L’Alternança a/e al Segrià. Doctoral thesis. University of Barcelona.
Barcelona.
CARRERASABATÉ,
J. (2001) La normativització del català modifica els hàbits fonètics dels parlants?
Llengua i literatura, 12: 175199.
CEDERGREN, H.
J.; SANKOFF, D. (1974) Variable rules: Performance as a statistical reflection of
competence. Language. 50: 333355.
KAY, P.;
McDANIEL, C. (1979) On the logic of variable rules. Language in Society. 8: 151187.
LABOV, W.
(1969) Contraction, Deletion, and Inherent Variability of the English Copula. Language.
45: 715762.
LABOV, W.
(1994) Principles of linguistic change. Internal factors. Blackwell. Cambridge.
LÓPEZ
MORALES, H. (1989) Sociolingüística. Gredos. Madrid.
MORENO, F.
(1994) Status quaestionis: sociolingüística, estadística e informática. Lingüística.
6: 95154.
SANKOFF, G.
(1988) Variable Rules. U. Ammon; N. Dittmar; K. J. Mattheier (eds.) Sociolinguistics. An
international handbook of the science of language and society. Walter de Gruyter. Berlin
& New York: 984997.
Josefina
CarreraSabaté
jcarrera@filcat.udl.es
carrera@lincat.ub.es
University of Lleida
University of Barcelona
