Oldal 120 [120]
OCR
CHAPTER 6 METHOD Optimality Theory for analyzing bilingual grammar premises that the actual surface representation is always the one that the most optimally serves the sociopragmatic function — in competition with other candidates — instantiated by a particular situation. Therefore, representing the interaction of constraints in algorithmic tableaux, the community specific ranking of the sociopragmatic constraints governing the mechanism of code-switching can be set up. The five sociopragmatic functions mentioned above also act as constraints filtering the candidates competing for surface representation. That is why code-switched instances have also been examined as fulfilling various sociopragmatic functions filtered by a hierarchically ranked set of constraints. The interaction of the constraints has been demonstrated in algorithmic tableaux. Computing the results of the interactions algorithmically, the specific ranking of the examined Hungarian-American community has been set up (Chapter 7). The objective of the quantitative sociolinguistic survey is to find statistically significant correlations between subjects’ sociolinguistic characteristics, such as (English and Hungarian) language use patterns, attitudes to English, to Hungarian languages, to code-switching, and to being a Hungarian-American that could provide an explanation for the underlying factors influencing the mechanism of code-switching in this particular Hungarian-American community. Relying on the results of previous sociolinguistic research conducted in Hungarian-American immigrant communities’, sociolinguistic characteristics are expected to differ along the lines of intergenerational affiliation. Hence, the aim of this quantitative survey is to find those measurable (sociolinguistic, language use, attitude, motivational) variables which determine first- (G1) and second-generation (G2) speakers’ notion of Hungarian and English languages and that of code-switching exerting considerable influence on their speech patterns as well. All quantified data in the survey have been analyzed with the help of statistical software (Jump and SPSS) to provide a sociolinguistic analysis of the examined community and to detect salient differences in Gl and G2 groups’ sociolinguistic characteristics (Chapter 7). Originally, I set out to explore statistically significant correlations between the frequency of code-switched instances of G1 speakers and their sociolinguistic variables. However, since the frequency of code-switched instances produced too sparsely distributed data, no statistically significant correlations have been found. 273 Fishman, Hungarian Language Maintenance in the US; Papp, Hungarian Americans and Their Communities of Cleveland; Kontra, Fejezetek a South Bend-i magyar nyelvhasznalatböl; Bartha, Social and linguistic characteristics of immigrant language shift, Acta Linguistica Hungarica, 405-431; Fenyvesi, Hungarian in the USA; Koväcs, Katonalevelek; Papp, Beszedből világ e 118"
