{ "paper_id": "Y16-3004", "header": { "generated_with": "S2ORC 1.0.0", "date_generated": "2023-01-19T13:47:29.823734Z" }, "title": "The Inner Circle vs. the Outer Circle or British English vs. American English", "authors": [ { "first": "Yong-Hun", "middle": [], "last": "Lee", "suffix": "", "affiliation": { "laboratory": "", "institution": "Chungnam Nation University Hannam University", "location": { "addrLine": "99 Daehak-ro, Gung-dong, Yuseong-gu 70 Hannam-ro, Ojoeng-dong, Daedeok-gu Daejeon 34134", "postCode": "34430", "settlement": "Daejeon", "country": "Korea, S. Korea" } }, "email": "" }, { "first": "Ki-Suk", "middle": [], "last": "Jun", "suffix": "", "affiliation": { "laboratory": "", "institution": "Chungnam Nation University Hannam University", "location": { "addrLine": "99 Daehak-ro, Gung-dong, Yuseong-gu 70 Hannam-ro, Ojoeng-dong, Daedeok-gu Daejeon 34134", "postCode": "34430", "settlement": "Daejeon", "country": "Korea, S. Korea" } }, "email": "" } ], "year": "", "venue": null, "identifiers": {}, "abstract": "In this paper, the use of two modals (can and may) in four varieties of English (British, India, Philippines, and USA) was compared and the characteristics of each variety were statistically analyzed. After all the sample sentences were extracted from each component of the ICE corpus, a total of twenty linguistic factors were encoded. Then, the collected data were statistically analyzed with R. Through the analysis, the following facts were observed: (i) India and Philippine speakers used can more frequently than natives, (ii) Three linguistic factors interacted with CORPUS, and (iii) The distinctions between American and British were more influential than those of the Inner Circle vs. the Outer Circle.", "pdf_parse": { "paper_id": "Y16-3004", "_pdf_hash": "", "abstract": [ { "text": "In this paper, the use of two modals (can and may) in four varieties of English (British, India, Philippines, and USA) was compared and the characteristics of each variety were statistically analyzed. After all the sample sentences were extracted from each component of the ICE corpus, a total of twenty linguistic factors were encoded. Then, the collected data were statistically analyzed with R. Through the analysis, the following facts were observed: (i) India and Philippine speakers used can more frequently than natives, (ii) Three linguistic factors interacted with CORPUS, and (iii) The distinctions between American and British were more influential than those of the Inner Circle vs. the Outer Circle.", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "Abstract", "sec_num": null } ], "body_text": [ { "text": "As English has spread worldwide, new varieties of English have emerged and they got independent status accordingly. In order to systematically classify them, Kachru (1992) introduced the three concentric circles as way of conceptualizing this pluri-centricity. There should be a distinction between American English (AmE) and British English (BrE) as well.", "cite_spans": [ { "start": 158, "end": 171, "text": "Kachru (1992)", "ref_id": "BIBREF1" } ], "ref_spans": [], "eq_spans": [], "section": "Introduction", "sec_num": "1" }, { "text": "Out of the varieties of English, we chose four different ones and statistically analyzed their properties. To this end, we picked out four components of the International Corpus of English (ICE; Greenbaum, 1996) , which are the varieties of British, India, Philippines, and USA. Then, all the sentences with two modal auxiliaries can and may were extracted. Then, a total of twenty linguistic factors were encoded to the extracted ones, and the encoded data were statistically analyzed with R, with the theoretical basis of Competition Model MacWhinney, 1982, 1989) . In addition, two statistical analysis methods were adopted. One was a logistic regression with which the properties of each component were closely investigated. The other was a Behavior Profile (BP) analysis where the four components were clustered by their similarity.", "cite_spans": [ { "start": 195, "end": 211, "text": "Greenbaum, 1996)", "ref_id": "BIBREF18" }, { "start": 542, "end": 565, "text": "MacWhinney, 1982, 1989)", "ref_id": null } ], "ref_spans": [], "eq_spans": [], "section": "Introduction", "sec_num": "1" }, { "text": "In short, we selected two modal auxiliaries can and may for comparison for the following reasons. As several of the previous studies (Leech, 1969 , Coates, 1983 Collins, 2009) pointed out, these two modal verbs have similar meanings, and the native speakers interchange them in similar contexts. However, the distributions of these two are systematic, even in native speakers' writings. Then, what happens in non-native speakers' counterparts and how can the phenomena be explained? We are to present one possible type of answer to these questions.", "cite_spans": [ { "start": 133, "end": 145, "text": "(Leech, 1969", "ref_id": "BIBREF6" }, { "start": 146, "end": 160, "text": ", Coates, 1983", "ref_id": "BIBREF8" }, { "start": 161, "end": 175, "text": "Collins, 2009)", "ref_id": "BIBREF12" } ], "ref_spans": [], "eq_spans": [], "section": "Introduction", "sec_num": "1" }, { "text": "The term 'World Englishes', not 'World English', refers to emerging localized/indigenized varieties of English, especially the varieties which have developed in territories influenced by the United Kingdom (Great Britain) or the United States. The primary goals of World Englishes are (i) to identify the varieties of English in diverse sociolinguistic contexts and (ii) to analyze how the sociolinguistic factors (histories, multi-cultural backgrounds and contexts of function) influence the use of English in different regions of the world.", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "World Englishes", "sec_num": "2.1" }, { "text": "There are several theoretical models to explain the spread of English, but the three concentric circles model by Kachru is probably the most influential one. In this model, the spread of English is classified and grouped into three different categories of regional varieties of English. These three categories are called the Inner Circle, the Outer Circle, and the Expanding Circle (Kachru, 1992:356) . Figure 1 illustrates the three concentric circles. The Inner Circle of English took shape first and spread across the world in the first diaspora. In this early spread of English, speakers from England carried the language to the colonies, such as Australia, New Zealand, North America, and so on. The English language in this circle represents the traditional historical and sociolinguistic bases in the regions where it is now used as English as the Native Language (ENL): the United Kingdom, the United States, Australia, New Zealand, Ireland, Canada, South Africa, and some of the Caribbean territories. In these countries, English is the native language or mother tongue for most people. The total number of English speakers in this circle is estimated to be as many as around 380 million.", "cite_spans": [ { "start": 382, "end": 400, "text": "(Kachru, 1992:356)", "ref_id": null } ], "ref_spans": [ { "start": 403, "end": 411, "text": "Figure 1", "ref_id": "FIGREF0" } ], "eq_spans": [], "section": "World Englishes", "sec_num": "2.1" }, { "text": "The Outer Circle of English was made during the second diaspora of English, which diffused the language through the expansion of Great Britain.", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "World Englishes", "sec_num": "2.1" }, { "text": "In the areas such as Asia and Africa, English is not the native language, but it serves as a useful lingua franca between various ethnic and language groups. Some people with higher education, the legislature and judiciary, national commerce, and others may speak English for practical purposes. The countries in this circle include India, Nigeria, Bangladesh, Pakistan, Malaysia, Tanzania, Kenya, non-Anglophone South Africa, the Philippines and others. The total number of English speakers is estimated to range from 150 million to 300 million.", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "World Englishes", "sec_num": "2.1" }, { "text": "The Expanding Circle includes the countries in which English plays no historical or governmental role but is widely used as a medium of international communication. This includes much of the rest of the world's population not categorized as either of the other two circles: China, Russia, Japan, most of Europe, Korea, Egypt, Indonesia, etc. It is difficult to estimate the total number of people in the Expanding Circle, but the estimates range from 100 million to one billion.", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "World Englishes", "sec_num": "2.1" }, { "text": "In addition to the three concentric circles in Kachru (1992) , one of the most influential classifications of English is that of British English and American English.", "cite_spans": [ { "start": 47, "end": 60, "text": "Kachru (1992)", "ref_id": "BIBREF1" } ], "ref_spans": [], "eq_spans": [], "section": "British English and American English", "sec_num": "2.2" }, { "text": "British English (BrE) refers to the form of English primarily used in the Great Britain, but it includes all the dialects used in other areas which were the former colonies of Great Britain. Likewise, American English (AmE) is the form of English mainly used in the United States, but it includes all the dialects used in other areas like the former colonies of the United States.", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "British English and American English", "sec_num": "2.2" }, { "text": "As the Great Britain expanded its territories by colonization, the United States of America (USA) also established a few colonies in Asian countries. Accordingly, English in these countries was influenced by its superpower. Nowadays, as the influences of the USA increased in many other countries, the importance of AmE increased as well.", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "British English and American English", "sec_num": "2.2" }, { "text": "English in Australia, Canada, Ireland and New Zealand belongs to BrE. In addition, most of Africa (including Egypt and South Africa), South Asia (Pakistan, India, and Bangladesh), Malta, some countries in Southeast Asia (Myanmar, Singapore, Malaysia, and Thailand), and Hong Kong still use BrE. On the other hand, most of Eastern Europe (including Russia), most East Asian countries excluding Hong Kong (China, Japan, and Korea), Philippines, most American countries (except Canada, Jamaica and the Bahamas), and some African countries (Liberia and Namibia) still use AmE.", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "British English and American English", "sec_num": "2.2" }, { "text": "There have been quite a few studies on the differences between BrE and AmE (McArthur, 2002; Tottie, 2002; Crystal, 2003; Hargraves, 2003; Peters, 2004; Algeo, 2006; Trudgill et al. 2013 ). The differences between these two types of English cover various areas including phonetics, phonology, morphology, syntax, semantics, and so on. However, most of the previous studies were focused on lexical differences and did not adopt any statistical methods in their analyses.", "cite_spans": [ { "start": 75, "end": 91, "text": "(McArthur, 2002;", "ref_id": "BIBREF23" }, { "start": 92, "end": 105, "text": "Tottie, 2002;", "ref_id": "BIBREF7" }, { "start": 106, "end": 120, "text": "Crystal, 2003;", "ref_id": "BIBREF2" }, { "start": 121, "end": 137, "text": "Hargraves, 2003;", "ref_id": "BIBREF10" }, { "start": 138, "end": 151, "text": "Peters, 2004;", "ref_id": "BIBREF11" }, { "start": 152, "end": 164, "text": "Algeo, 2006;", "ref_id": "BIBREF9" }, { "start": 165, "end": 185, "text": "Trudgill et al. 2013", "ref_id": "BIBREF13" } ], "ref_spans": [], "eq_spans": [], "section": "British English and American English", "sec_num": "2.2" }, { "text": "The Competition Model (CM), on which this paper is theoretically based, is a psycholinguistic theory of language acquisition and sentence processing. This model was developed by Elizabeth Bates and Brian MacWhinney. The most important idea of the CM is that the meaning of a language must be and can be interpreted by comparing a number of linguistic factors within a sentence. In addition, a language is acquired and/or learned through the competition of basic cognitive mechanisms with a rich linguistic environment.", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "Competition Model", "sec_num": "2.3" }, { "text": "The CM claims that human beings understand the meaning of a sentence by taking into account various factors, such as word order, morphology, and semantic characteristics (e.g. animacy), and so on. Thus, when people articulate a sentence, they unconsciously calculate the probabilities of each meaning and choose the one with the highest value. We adopted this model as a theoretical basis because two modal auxiliaries can and may occur in similar linguistic environments and that they compete with each other. As a result of the competition, one of them is chosen as a winner in the given linguistic environments. The winner has more probability than the other in the given environments. Then, the question is which factor would decide the winner. We investigated the decision mechanisms with a statistical analysis.", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "Competition Model", "sec_num": "2.3" }, { "text": "Our research proceeded as follows. First, four corpora were selected from the ICE: British, India, Philippines, and USA. Each corpus included about 1 million of word tokens, and the composition of each corpus was nearly identical. They are listed as in Table 1 . Next, all the sentences with the two modal auxiliaries were extracted from the four corpora, using NLPTools (Lee, 2007) .", "cite_spans": [ { "start": 371, "end": 382, "text": "(Lee, 2007)", "ref_id": "BIBREF24" } ], "ref_spans": [ { "start": 253, "end": 260, "text": "Table 1", "ref_id": null } ], "eq_spans": [], "section": "Research Procedure", "sec_num": "3.1" }, { "text": "The OuterCircle BrE Britain India AmE USA Philippines Table 1 : Classification of Four Corpora Since there were so many sentences in each variety, we extracted 1,000 sentences per each corpus with random sampling. Then, twenty different linguistic factors were manually encoded into them, following Deshors (2010) and Deshors and Gries (2014) . Lastly, a statistical analysis of the corpus data was done with the help of R (R Core Team, 2016). Table 2 illustrates the encoded factors, used in this paper. Following Atkins (1987) , each linguistic factor and its level are called ID tag and ID tag levels. The variables were used in the statistical analysis. 1", "cite_spans": [ { "start": 299, "end": 313, "text": "Deshors (2010)", "ref_id": "BIBREF17" }, { "start": 318, "end": 342, "text": "Deshors and Gries (2014)", "ref_id": null }, { "start": 515, "end": 528, "text": "Atkins (1987)", "ref_id": "BIBREF0" } ], "ref_spans": [ { "start": 54, "end": 61, "text": "Table 1", "ref_id": null }, { "start": 444, "end": 451, "text": "Table 2", "ref_id": "TABREF1" } ], "eq_spans": [], "section": "The Inner Circle", "sec_num": null }, { "text": "We also carried out a multi-factorial analysis, in which not only the effects of each factor but also the interactions among the factors are statistically analyzed. The multi-factorial analyses of linguistic data are supported by many studies in cognitive linguistics. Langacker (2000:3) mentioned that \"to conceive of [linguistic] entities in connection with one another (e.g., for the sake of comparison, or to assess their relative position), not just as separate, isolated experiences. This is linguistically important because relationships figure in the meaning of almost all expressions, many of which (e.g., verb, adjectives, prepositions) designate relationships.\" Gries (2003) also conducted the multi-factorial analysis to analyze the distributions of particle placement in native speakers' English. Deshors (2014:11) also mentioned that \"The multi-factorial approach also helps the authors make a connection between degrees of grammatical complexity of speakers' utterances and learners' lexical choices during second language production. For instance, they observe that can rather than may is more frequently used by French English learners (compared to native speakers) in more complex grammatical environments such as negated or subordinated linguistic contexts.\"", "cite_spans": [ { "start": 269, "end": 287, "text": "Langacker (2000:3)", "ref_id": null }, { "start": 673, "end": 685, "text": "Gries (2003)", "ref_id": "BIBREF20" } ], "ref_spans": [], "eq_spans": [], "section": "Statistical Analysis", "sec_num": "3.3" }, { "text": "As a multi-factorial approach, we used a Generalized Linear Model (GLM) with logistic regression, since it is one of the simplest and most widely-adopted analyses. For regression analysis, Deshors (2014:11) mentioned that \"Binary logistic regression is a confirmatory statistical technique that allows the analyst to identify possible correlations between the dependent and the independent factors/variables. Ultimately, this statistical approach allows us to see what factors influence learners' choices of may and can.\"", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "Statistical Analysis", "sec_num": "3.3" }, { "text": "During the analysis process, a stepwise model selection procedure was adopted as follows. First, an initial model was constructed with all of the factors and their interactions. Second, a new model was constructed in which only one factor or one interaction was deleted from the previous model. Third, the newly constructed model was compared with the previous one with an ANalysis Of VAriance (ANOVA). Fourth, an optimal model was chosen according to some criteria such as significance testing or information ones: If a model m 1 contained a factor f or an interaction i but a model m 2 did not contain f or i, and (i) when the pvalue of the ANOVA test was significant (p<.05), it implied that the factor f or an interaction i must NOT be deleted from the model and the model m 1 was selected consequently, and (ii) when the pvalue of ANOVA was NOT significant (.05" }, "TABREF2": { "num": null, "type_str": "table", "html": null, "text": "", "content": "
: Initial Model
Then, model selection procedures were applied (cf.
Section 3.3) and the final (optimal) model was
selected. Table 4 shows the final model.
FORM~CORPUS+SUBJMORPH+MOOD+SENTTYPE+
CLTYPE+VENDLER+CORPUS:SUBJMORPH+CORPU
" }, "TABREF3": { "num": null, "type_str": "table", "html": null, "text": "", "content": "" }, "TABREF5": { "num": null, "type_str": "table", "html": null, "text": "Analysis Results", "content": "
" } } } }