Using an Enhanced MDA Model in study of World Englishes Richard Xiao

15/05/2015CRG, Lancaster University2 Overview of the talk Biber’s (1988) MF/MD analytical approach The enhanced multidimensional analysis (MDA) model Variation across 12 registers in 5 varieties of English in the ICE

15/05/2015CRG, Lancaster University3 Factor analysis The key to the multidimensional analysis approach A common data reduction method available in many standard statistics packages such as SPSS Reducing a large number of variables to a manageable set of underlying factors (“dimensions”) Extensively used in social sciences to identify clusters of inter-related variables

15/05/2015CRG, Lancaster University4 Biber’s MF/MD framework Established in Biber (1988): Variation across Speech and Writing (CUP) –Factor analysis of 67 functionally related linguistic features –481 text samples, amounting to 960,000 running words LOB London-Lund Brown corpus A collection of professional and personal letters

15/05/2015CRG, Lancaster University5 Biber’s MF/MD approach Biber’s seven factors / dimensions –Informational vs. involved production –Narrative vs. non-narrative concerns –Explicit vs. situation-dependent reference –Overt expression of persuasion –Abstract vs. non-abstract information –Online informational elaboration –Academic hedging

15/05/2015CRG, Lancaster University6 Biber’s MF/MD approach Influential and widely used –Synchronic analysis of specific registers / genres and author styles –Diachronic studies describing the evolution of registers –Register studies of non-Western languages and contrastive analyses –Research of University English and materials development –Move analysis and study of discourse structure …largely confined to grammatical categories

15/05/2015CRG, Lancaster University7 The enhanced MDA model Enhancing Biber’s MDA by incorporating semantic components with grammatical categories –Wmatrix = CLAWS + USAS –A total of 141 linguistic features investigated 109 features retained in the final model –Five million words in 2,500 text samples, with one million words in 500 samples for each of the 5 varieties of English ICE – GB, HK, India, Singapore, the Philippines 300 spoken written samples 12 registers ranging from private conversation to academic writing

15/05/2015CRG, Lancaster University8 ICE registers and proportions S1A (20%)Spoken – Private S1B (16%)Spoken – Public S2A (14%)Spoken – Monologue – Unscripted S2B (10%)Spoken – Monologue – Scripted W1A (4%)Written – Non-printed – Non-professional writing W1B (6%)Written – Non-printed – Correspondence W2A (8%)Written – Printed – Academic writing W2B (8%)Written – Printed – Non-academic writing W2C (4%)Written – Printed – Reportage W2D (4%)Written – Printed – Instructional writing W2E (2%)Written – Printed – Persuasive writing W2F (4%)Written – Printed – Creative writing

15/05/2015CRG, Lancaster University9 141 linguistic features covered A) Nouns: 21 categories, e.g. –nominalisation, other nouns; 19 semantic classes of nouns (e.g. evaluations, speech acts) B) Verbs: 28 categories, e.g. –Do as pro-verb, be as main verb, tense and aspect markers, modals, passives, 16 semantic categories of verbs C) Pronouns: 10 categories, e.g. –Person, case, demonstrative D) Adjectives: 11 categories, e.g. –Attributive vs. predicative use, 9 semantic categories

15/05/2015CRG, Lancaster University linguistic features covered E) Adverbs: 7 categories F) Prepositions (2 categories) G) Subordination (3 categories) H) Coordination (2 categories) I) WH-questions / clauses (2 categories) J) Nominal post-modifying clauses (5 categories) K) THAT-complement clauses (3 categories) L) Infinitive clauses (3 categories) M) Participle clauses (2 categories) N) Reduced forms and dispreferred structures (4 categories) O) Lexical and structural complexity (3 categories)

15/05/2015CRG, Lancaster University Linguistic features covered P) Quantifiers (4 categories) Q) Time expressions (11 categories) R) Degree expressions (8 categories) S) Negation (2 categories) T) Power relationship (4 categories) U) Definiteness (2 categories) V) Helping/hindrance (2 categories) X) Linear order (1 category) Y) Seem / Appear (1 category) Z) Discourse bin (1 category)

15/05/2015CRG, Lancaster University12 Procedure of data analysis 1) Data clean-up 2) Grammatical and semantic tagging with Wmatrix 3) Extracting the frequencies of 141 linguistic features from 2,500 corpus files 4) Building a profile of normalised frequencies (per 1,000 words) for each linguistic feature 5) Factor analysis –Factor extraction (Principal Factor Analysis) –Factor rotation (Pramax) –Optimum structure: 9 factors 6) Interpreting extracted factors 7) Computing factor scores 8) Using the enhanced MDA model in exploration of variation across registers and language varieties

15/05/2015CRG, Lancaster University13 The enhanced MDA model Nine factors established in the new model –1) Interactive casual discourse vs. informative elaborate discourse –2) Elaborative online evaluation –3) Narrative concern –4) Human vs. object description –5) Future projection –6) Personal impression and judgement –7) Lack of temporal / locative focus –8) Concern with degree and quantity –9) Concern with reported speech Robustness of the model in register analysis

15/05/2015CRG, Lancaster University14 1) Interactive casual discourse vs. informative elaborate discourse Private conversation is most interactive and casual Academic writing is most informative and elaborate Spoken registers are generally more interactive and less elaborate than written registers F= p< R 2 =77.4%

15/05/2015CRG, Lancaster University15 2) Elaborative online evaluation Public dialogue (e.g. broadcast discussion / interview, parliamentary debate) has the most prominent focus on elaborative online evaluation Unscripted monologue also involves a high level of elaborative online evaluation Persuasive writing may relate to elaborative evaluation but is not restricted by real- time production Private conversation is least elaborative even if the evaluation is made online Evaluation is not a concern in creative writing F= p< R 2 =31.1%

15/05/2015CRG, Lancaster University16 3) Narrative concern Unscripted monologue (e.g. demonstrations, presentations, commentaries) has a narrative concern Unsurprisingly, creative writing is also narrative Not a concern in academic writing, non-professional writing (student essays and exam scripts), and instructional writing F= p< R 2 =37.3%

15/05/2015CRG, Lancaster University17 4) Human vs. object description Private conversation is most likely to have a focus on people Correspondence (social letters and business letters) also involves human description Instructional writing tends to give concrete descriptions of objects Academic and non-academic writings can also be concrete when an object or substance is described F=44.03 p< R 2 =16.3%

15/05/2015CRG, Lancaster University18 5) Future projection Persuasive writing (e.g. press editorials, trying to influence people’s future attitudes and actions) has the most prominent focus on future projection Correspondence and public dialogue also involve future projection to varying extents Academic writing (timeless truth?) is least concerned with future projection F=28.10 p< R 2 =11.1%

15/05/2015CRG, Lancaster University19 6) Personal impression / judgement Factor score of creative writing is by far greater than any other register –Frequent use of possessive and reflective pronouns, as well as adjectives of judgement / appearance Instructional writing, private conversation, and student essays display low scores –They do not have a focus on personal impression and judgement Scripted and unscripted monologue, public dialogue and news reportage also tend to avoid expressions of personal impression and judgement F= p< R 2 =35.8%

15/05/2015CRG, Lancaster University20 7) Lack of temporal / locative focus Student essays and persuasive writing do not have a temporal / locative focus (not concerned with concepts such as when, how long, and where) Such specific information is of vital importance in correspondence (social and business letters) F=89.55 p< R 2 =28.4%)

15/05/2015CRG, Lancaster University21 8) Concern with degree / quantity Non-academic popular writing has the greatest concern of degree and quantity Persuasive writing also displays a high propensity for expressions of degree and quantity Such expressions tend to be avoided in instructional writing (e.g. administrative documents) and correspondence F=19.33 p< R 2 =7.9%

15/05/2015CRG, Lancaster University22 9) Concern with reported speech News reportage has the greatest concern with reported speech (both direct and indirect speech) Reported speech is also very common in creative writing (fictional dialogue) Instructional writing and academic prose do not appear to have a concern with reported speech F=80.02 p< R 2 =26.1%

15/05/2015CRG, Lancaster University23 12 registers along 9 factors Factor 1 is the dimension along which the 12 registers demonstrate the sharpest contrasts –Interactive casual discourse vs. informative elaborate discourse: a fundamental aspect of variation across registers Robustness of the model

15/05/2015CRG, Lancaster University24 5 English varieties across 9 factors Both differences and similarities This general picture may blur many register-based subtleties –Language can vary across registers even more substantially than across language varieties (cf. Biber 1995)

15/05/2015CRG, Lancaster University25 1) Interactive casual discourse vs. informative elaborate discourse Indian English displays the lowest score in nearly all registers - it is less interactive but more elaborate –Sanyal (2007): “clumsy Victorian English [that] hangs like a dead Albatross around each educated Indian’s neck” Modern BrE appears to be most interactive and least elaborate (e.g. S1A, S1B, W2D) 3 varieties of English used in East and Southeast Asia are very similar F=9.04, 4 d.f. p<0.001

15/05/2015CRG, Lancaster University26 2) Elaborative online evaluation BrE generally shows a higher score than non-native varieties of English (e.g. W2A, W1B, S2B) Non-native English varieties tend to be very close in most registers F= d.f. p<0.001

15/05/2015CRG, Lancaster University27 3) Narrative concern BrE demonstrates a greater propensity for narrative concern –Most noticeably in news reportage (W2C) and instructional writing (W2D) Indian English is least concerned with narrative –Esp. in registers like correspondence (W1B), instructional writing (W2D), and unscripted monologue (S2A) F= d.f. p<0.001

15/05/2015CRG, Lancaster University28 4) Human vs. object description Very close in a number of registers (e.g. S2B, W1B, W2E) Indian English and BrE show similarity in a greater range of registers HK and Singapore Englishes display great similarity (except W1A) Creative writing (W2F) is very similar in non-native varieties of English F= d.f. p<0.001

15/05/2015CRG, Lancaster University29 5) Future projection BrE has the highest score in all printed written registers (W2A–W2F) Indian English shows the lowest score in nearly all registers F= d.f. p<0.001

15/05/2015CRG, Lancaster University30 6) Personal impression / judgement Very similar in many registers…with most noticeable differences in non- printed written registers (W1A, W1B), non-academic writing (W2B), and news reportage (W2C) HK English displays a distribution pattern similar to Singapore English in spoken registers (S1A–S2B) and unpublished written registers (W1A, W1B), but it is very close to Philippine English in printed writing (W2A–W2F) F= d.f. p<0.001

15/05/2015CRG, Lancaster University31 7) Lack of temporal / locative focus Overall difference is not significant statistically –…but there are noticeable differences in some registers (e.g. W1B, W2D) Interestingly, Indian English demonstrates a consistently higher score in spoken registers (S1A-S2B) –…but a lower score in unpublished writing (e.g. W1B) F= d.f. p=0.058

15/05/2015CRG, Lancaster University32 8) Concern with degree / quantity BrE generally displays a higher score in nearly all registers HK English does not appear to be concerned with degree and quantity (e.g. W2D) Similarly Indian English also lacks a focus on degree and quantity (e.g. W1B) F= d.f. p<0.001

15/05/2015CRG, Lancaster University33 9) Concern with reported speech Overall difference is not significant …in spite of noticeable difference in news reportage (W2C) –East and Southeast Asian English varieties show a greater propensity for concern with reported speech than BrE and Indian English F= d.f. p=0.196

15/05/2015CRG, Lancaster University34 Summary and future research Summary –Seeking to enhance Biber’s MDA model with semantic components –Introducing the new model in research of World Englishes Directions for future research –More native English varieties from the Inner Circle –A wider and more balanced coverage of geographical regions –Including socio-culturally relevant semantic categories –Making “sense” of corpus finding by combining corpora and more traditional resources in socio-cultural studies and historical research …adequately descriptive + sufficiently explanatory…

15/05/2015CRG, Lancaster University35 Thank you!