گویش سنجی متغیرهای زبان شناختی زبان گونه های کرمان- شمالی (مقاله علمی وزارت علوم)
درجه علمی: نشریه علمی (وزارت علوم)
آرشیو
چکیده
پژوهش حاضر با اتخاذ رویکردی کمی و کل گرایانه و با اعمال روش های گویش سنجی به تحلیل رایانشی متغیرهای زبان شناختی موجود در گونه های زبانی کرمان-شمالی می پردازد. این پژوهش، از نوع توصیفی- تحلیلی است و داده ها به روش میدانی جمع آوری شده اند. تحلیل داده های گردآوری شده نیز به صورت آماری با بهره گیری از رایانه و گویش سنجی و نقشه نگاری RuG/L04 صورت گرفته است. داده های پژوهش شامل معادل های بومی 205 واژه و 10 جمله پایه مستخرج از پرسش نامه های «فرهنگستان» و «موریس سوادش» است. روایی پرسش نامه مذکور براساس آزمون آلفای کرونباخ، نرخ 96/0 به دست آمده است. جامعه آماری پژوهش را گویشوران بومی 16 شهرستان حوزه شمال استان کرمان شامل 105 دهستان تشکیل می دهند. میانگین سنی گویشوران 60 سال و متوسط سواد آن ها در حد آموزش ابتدایی است که 45% زن و 55% مرد هستند. نتایج حاصل از تحلیل انبوهه داده ها نشان داد که شش خوشه گویشی عمده از هم متمایز هستند و این خوشه های گویشی خود به زیر خوشه هایی تقسیم می شوند. هر یک از خوشه های گویشی دارای ویژگی های آوایی، واجی، صرفی یا نحوی متمایزی هستند که آن ها را از دیگر خوشه ها جدا می کند. بر اساس تحلیل آماری داده ها، از میان خوشه های گویشی شش گانه، تنها یکی از آن ها گویش است و باقی خوشه ها فاقد ویژگی های گویشی می باشند و در نتیجه در سطح لهجه محسوب می شوند.The Dialectometry Variables of Northern- Kerman Language Varieties
Introduction Considering the importance of language and different varieties as the heritage of humanity for the interaction of information, it seems necessary to preserve this heritage. The present study attempts to provide a holistic view of the continuous state of the dialects of the language varieties of the centeral, north, northwest, and southwest regions of Kerman province (Northern- Kerman variety) within the framework of one of the new methods, dialectometry, in the field of dialectology. Dialectometry is the method that uses statistical methods to measure dialect distances and to determine language boundaries. Based on the authors’ review, dialectometric methods have been used in limited studies to investigate Iranian dialects, and the representation of various linguistic varieties of Kerman province have often been summarized in traditional ways and based on the predecessors’ opinion. The present work is new in this respect. Research method, background and purpose In the current research, male and female speakers with an average age of 60 years and a literacy level of primary education, who live in the targeted region, were interviewed. A total of 54 dialect samples were prepared from 54 sites. The data of the study were extracted from the questionnaires of “Iran’s national language atlas project” and “Morris Swadesh basic list words”. The validity of the mentioned questionnaires was 0.96 based on Cronbach’s alpha test. In doing so, 205 words and 10 basic sentences extracted from the mentioned questionnaires. The collected data were statistically analyzed using the dialectometric and mapping software RuG/L04 package. Dialectometric methods adopted in this research include linguistic distance index, clustering and multidimensional scaling. The background of this research is divided into two categories. The first category is the studies related to the linguistic varieties of Northern-Kerman language, which have been conducted using traditional dialectology methods such as; Sotudeh (1335), Baghai (1342), Karbasi Ravari (1365), Babak (1375), Aieene Negini (1381), Anjom Shoae (1381). Hoseini Musa (1384), Farhadi Rad (1382), Ruholaamini (1384), Naghavi (1385), Mowlaei Kuhbanani (1390), Altaha (1394) and Larimer and Golabzade (1395). The second category is the studies which use Dialectometric methods include; Asadpur (1391), Rostambeik Tafreshi (1393), Mollaei Pashaei (1393), Sanayi (1395), Heidari Zadeh (1398) and Ghemat Pur (1399). The purpose of this research is to analyze the cluster of geographical distribution of linguistic variables, and more specifically, the main dialect clusters of Northern- Kerman variety are identified by certain dialectometric methods and their linguistic distance are measured to compare the results with the findings of traditional studies of Northern- Kerman varieties. Discussion and review The findings of the clustering of language varieties based on linguistic distance index (chart 1) and multidimensional scaling (chart 2) showed that six dialect clusters can be distinguished in the geographical scope of the research, which will be used as letters ‘A’, ‘B’, ‘C’, ‘D’, ‘E’ and ‘F’. Cluster ‘A’ has the highest dialectal difference with a language distance index 0.34. Other dialect clusters have the least difference with a minimal distance. According to the distance index matrix and the two-dimensional scaling map, it can be concluded that only cluster ‘A’ is a dialect and the other clusters should be considered accents. Dialect cluster ‘A’ is distinguished from other clusters due to some distinctive features including the use of some Baluchi words, /Iə/ and /ʊə/ diphthongs, the trill phoneme of /r/, consonance cluster // of Ancient Iranian, the plural suffix /-on/, the continuous prefix / ʔæ-/, the noun-forming and adjective-forming suffixes (/-æ/, /-æg/, /-æk/ ), debuccalization process and ergative construction. Cluster ‘B’ is different from other clusters due to the high frequency of the vowel lengthening process of the first syllable. Cluster ‘C’ is different from other dialect clusters due to the insertion of the glide /j/ at the end of words ending in a vowel, but it is similar to clusters ‘D’ and ‘E’ in two syntactic features; the first person singular pronoun /-om/and the first person singular pronoun as /mo/. The cluster ‘D’ is similar to the cluster ‘E’ in the vowel lengthening of the negative prefix /næː-/ in the simple past tense and the negative imperative. The cluster ‘E’ is different from other clusters in the elimination of the consonant phoneme /m/ and, of course, the lengthening of the preceding syllable, but it is common with ‘C’, ‘D’ and ‘F’ clusters in the application of the process of changing obstruent, such as the conversion of /q/ to /ɤ / in the vowel environment or the beginning and end of the syllable. Cluster ‘F’ is similar to clusters ‘B’, ‘D’ and ‘E’ in the degemination process. Finally, in the analysis of dialect clusters’ data, it was found that the dialect clusters ‘B’, ‘C’, ‘D’, ‘E’ and ’F’ are common in the application of the compensatory lengthening process. Conclusion Adopting a computational linguistic approach, the current research has been analyzed the linguistic variables in the Northern- Kerman language varieties. According to the findings of the language clustering of language varieties (chart 1) and two-dimensional scaling (chart 2) in the geographical scope of the research, six major dialect clusters are distinguished from each other. Each of the dialect clusters has distinct phonetic, phonological, morphological and syntactic features that distinguish it from other clusters. Based on the statistical analysis of the data, among the six dialect clusters, only cluster ‘A’ is a dialect, and the rest of the clusters have no dialect characteristics and are considered accents. For example, cluster ‘A’ is different from other clusters due to its features such as special words in the Baluchi language, /Iə/ and /ʊə/ diphthongs, the trill phoneme of /r/, consonance cluster // of Ancient Iranian, debuccalization process and the usage of ergative construction. Other clusters differ from each other due to limited differences such as the use of vowel lengthening in the first syllable like cluster ‘B’, the insertion of the glide /j/ at the end of words ending in a vowel like cluster ‘C’, the elimination of the consonant phoneme /m/ and, of course, the lengthening of the preceding syllable like cluster ‘E’, but they are similar in the compensatory lengthening process.
تبلیغات
