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J. MARSHALL which comes nearest to touching all of them. The measure of regression is then based on how much distance there is between the regression line and the actual points on the graph. Correlations are shown in the following manner: a perfect negative correlation will show as minus 1, and a perfect positive correlation as plus 1. Scores close to zero will show no significant correlation. The reader will bear in mind that these correlation tests are only first measures. The first batch of Pearson’s Correlations reveal the following: phovar ssscor lexrec lifmod socnet soclas attdia natpri age 0.734 0.659 0.764 0.558 0.186 -0.432 0.334 -0.083 Those that correlate significantly are in bold. These correlation coefficients show that: AGE is correlated positively with 1) PHOVAR, 2) SSSCOR, 3) LEXREC, 4) LIFMOD, and negatively with 5) SOCLAS. The correlation between age and the linguistic scores comes as no surprise: the dialect is being lost, and younger speakers do not have access to the range of dialect features that the older ones do. As age is highly correlated with many variables, and as it is not included in the hypothesis, its effects will have to be removed during the model-building process in the regression analysis. Age also correlates highly with LIFMOD. This shows that older people are less mentally urbanised than younger ones generally. The effect of age has been smoothed out during the model-building phase, so that correlations between LIFMOD alone and the linguistic scores could be more rigorously tested. Age correlates negatively with social class. This shows that younger folk are not only more educated, but also read more national newspapers, and aspire to greater things vocationally, for example. Next the correlations between LIFMOD and the other variables were considered: phovar ssscor lexrec age socnet soclas attdia natpri lifmo 0.782 0.767 0.704 0.558 0.186 -0.553 0.468 0.242 From this we can see that LIFMOD is positively correlated with PHOVAR, SSSCOR, LEXREC, AGE, and ATTDIA, and negatively with SOCLAS. This seems to show that, at this stage of the analysis at least, LIFMOD is a strong 160
SOCIAL NETWORKS IN A RURAL SETTING predictor of language use, and is also linked to some of the other social variables. The following scatterplots show the trend: a strongly positive orientation to the local rural community (i.e. a low degree of mental urbanisation) yields a high dialect score. LIFMODPHOVAR 60 50 40 PHOVAR 30 PHOVAR 20 10 0 0 5 10 15 20 25 30 35 40 LIFMOD ssscor lifmo 0.767 LIFMODSSSCOR 1.2 1 0.8 SSSCOR 0.6 SSSCOR 0.4 0.2 0 0 5 10 15 20 25 30 35 40 45 LIFMOD lexrec lifmo 0.704 161
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Reading Working Papers in Linguisti
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Reading Working Papers in Linguisti
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K ALJENAIE testing ground. To what
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K ALJENAIE causative form is basica
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K ALJENAIE person diagram, the two
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K ALJENAIE 3.2 Data Analysis The sa
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K ALJENAIE Table 4 Osama’s longit
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K ALJENAIE The asterisk indicates t
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K ALJENAIE which is the transitive
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K ALJENAIE confirming Hyams (1986)
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K ALJENAIE Table 12 Sara’s realiz
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K ALJENAIE Table 15 Number of Infle
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K ALJENAIE masculine forms are cons
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K ALJENAIE Motar, A. (1969). Khasai
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P. COUTSOUGERA Plural Plural Singul
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P. COUTSOUGERA e.g. [peδja'] *[pe
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P. COUTSOUGERA Tableau 1: Opacity i
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P. COUTSOUGERA As can be seen, in r
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P. COUTSOUGERA 6.1 Selection of the
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P. COUTSOUGERA /alevr-I-a/ Tableau
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P. COUTSOUGERA different areas of t
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P. COUTSOUGERA ruled out as it viol
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P. COUTSOUGERA operation McCarthy p
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P. COUTSOUGERA Tableau 6: Applicati
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P. COUTSOUGERA References Anderson,
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R. INGHAM cognitive deficits. They
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R. INGHAM 2. Subjects and hypothese
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R. INGHAM good as their CA matches
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R. INGHAM 100 90 80 70 60 50 40 30
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R. INGHAM Did the [+LD] group perfo
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R. INGHAM using the Wilcoxon ranked
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R. INGHAM representations but also
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R. INGHAM Van der Lely, H., & L. St
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P. KERSWILL & A. WILLIAMS some vene
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P. KERSWILL & A. WILLIAMS far soone
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P. KERSWILL & A. WILLIAMS outside l
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P. KERSWILL & A. WILLIAMS 3. Intern
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P. KERSWILL & A. WILLIAMS • Varia
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P. KERSWILL & A. WILLIAMS Despite s
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P. KERSWILL & A. WILLIAMS naturalne
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P. KERSWILL & A. WILLIAMS apparent
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P. KERSWILL & A. WILLIAMS Summary f
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P. KERSWILL & A. WILLIAMS Table 2 T
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P. KERSWILL & A. WILLIAMS regard it
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P. KERSWILL & A. WILLIAMS The ‘gr
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P. KERSWILL & A. WILLIAMS Table 4 (
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P. KERSWILL & A. WILLIAMS sociodemo
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P. KERSWILL & A. WILLIAMS Bardovi-H
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P. KERSWILL & A. WILLIAMS språkfö
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S. KULKARNI in the Indian caste hie
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S. KULKARNI ideologies, each emphas
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S. KULKARNI century. The Sabha was,
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S. KULKARNI The main study includes
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S. KULKARNI 4. Quantitative Analyse
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S. KULKARNI comparatively lower (in
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S. KULKARNI Table 3: Percentage use
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Page 120 and 121: S. KULKARNI Marathi the kin term /m
Page 122 and 123: S. KULKARNI not by the less-privile
Page 124 and 125: S. KULKARNI Bapuji, B.R. (1994).
Page 126 and 127: S. KULKARNI Sastry, J.V. (1993). Re
Page 128 and 129: J. MARSHALL 2. Change versus Resist
Page 130 and 131: J. MARSHALL have become more expose
Page 132 and 133: J. MARSHALL anthropologists. As man
Page 134 and 135: J. MARSHALL for data such as Milroy
Page 136 and 137: J. MARSHALL To some extent, [networ
Page 138 and 139: J. MARSHALL these close-knit ties a
Page 140 and 141: J. MARSHALL Life mode 1. Life modes
Page 142 and 143: J. MARSHALL There are, however, som
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Page 146 and 147: J. MARSHALL Pedersen therefore, lik
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Page 150 and 151: J. MARSHALL 6. Research Question an
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Page 154 and 155: J. MARSHALL 6.5. Morphological Vari
Page 156 and 157: J. MARSHALL 4 Do you work/go to sch
Page 158 and 159: J. MARSHALL 8) I never eat brose or
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Page 162 and 163: J. MARSHALL 3. LEXREC. This is an i
Page 166 and 167: J. MARSHALL LIFMODLEXREC 60 50 40 L
Page 168 and 169: J. MARSHALL the different tests wer
Page 170 and 171: J. MARSHALL PHOVAR = 21.1 + 0.573 A
Page 172 and 173: J. MARSHALL There is no significant
Page 174 and 175: J. MARSHALL 7.6. SOCNET as a Predic
Page 176 and 177: J. MARSHALL SOCNET is again not sig
Page 178 and 179: J. MARSHALL integrated sociolinguis
Page 180 and 181: I. SINKA, M. GARMAN AND C. SCHELLET
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