users.utu.fi · Web viewLog L. 1611 ER 1 198 0.12 9 750 0.50 3 199.9 1610 I 8 534 0.83 31 126 1.59 3 139.1 1609 SHE 337 0.03 5 899 0.30 3 057.0 1608 OH 475 0.05 5 938 0.30 2 620.4

Chapter 8 Overview of Results

8.1 Introduction

In this chapter the most important results of the analyses carried out on both the BEC

and the PMC are presented. They show that both hypotheses under analysis are proved to

be correct - lexis central to and indicative of Business English is presented, and key

differences between the Business English lexis of published materials and the Business

English found in the BEC are given. The amount of data generated by the corpora,

however, has proved so vast that it is only possible in this chapter to give an overview

and brief comments on the key results (a fuller, more detailed presentation and

interpretation of the results is presented in Chapter 9). In each case, the place where the

full results are stored is indicated, along with reference to the section of Chapter 9 where

each result is dealt with in detail. The results of this thesis are stored in two places: in the

Appendices in Vol. II, and on the CD ROM attached to this thesis inside the back cover.

This chapter, then, serves as an overview - showing examples of key results - and a guide

- it designates the place where results can be found. The presentation of the results here is

divided into two main sections: firstly, those results gained from analysis of the BEC,

and secondly, those results gained from the PMC.

8.2 Analysis of the BEC

8.2.1 General Statistics of the BEC

Here the overall statistics for the BEC are presented using the version of the BEC

categorised by macro-genres.

TABLE XV: GENERAL STATISTICS OF THE BEC

Bytes 6 496 472Tokens (words) 1 023 021Types (types of words) 28 232Type/Token Ratio 2.76Standardised Type/Token (as %) 40.01

289

Average word length 4.66Sentences 43 473Sentence length 17.18Standard sentence length 14.75Paragraphs 35 283Paragraph length 28.49Standard paragraph length 91.98Headings 0Heading lengthStandard heading length1-letter words 42 5442-letter words 179 2563-letter words 204 2264-letter words 173 4015-letter words 105 3376-letter words 79 1757-letter words 75 6518-letter words 57 6419-letter words 43 36810-letter words 28 17211-letter words 17 73712-letter words 8 52213-letter words 5 14814(+)-letter words 1 902

8.2.2 BEC frequency list unlemmatised/unedited

This can be found in the CD ROM.

8.2.3 BEC frequency list lemmatised

Here the top 100 most frequent lemmas are shown. A list of the top 1,000 lemmas can

be found in Appendix 1 in Vol. II and on the CD ROM. The frequency list below shows

that in Business English, the most frequent words are still general, non-business words,

with only seven words in the top 100 that could be considered business-related -

company, business, market, work, service, product and price. This is discussed in full in

Section 9.3.1 in the next chapter. It will also be noted that the word yeah has been added

to the lemma yes. This was done in an attempt to give a true frequency value to yes in

comparison to no, which, unlike yes, did not take any other lexical form in the corpus.

TABLE: XVI: BEC LEMMATISED FREQUENCY LIST (TOP 100 LEMMAS)

290

N Word BEC freq. BEC % Lemmas

291

1 THE 52 213 5.102 BE 34 883 3.41 am(286),are(6959),is(11337),was(3893),

were(1525),being(760),been(2148),’m(149)3 TO 29 495 2.884 AND 26 429 2.585 OF 25 614 2.506 A 23 872 2.33 an(3170)7 IN 18 293 1.798 THAT 13 069 1.28 those(821)9 HAVE 10 945 1.07 has(2716),having(383),had(1677)10 FOR 10 415 1.0211 YOU 10 133 0.9912 IT 8 902 0.8713 I 8 534 0.8314 ON 7 781 0.7615 WE 7 492 0.7316 WITH 6 754 0.6617 THIS 6 468 0.63 these(1306)18 AS 6 241 0.6119 DO 5 298 0.52 does(581),doing(567),did(573),done(471)20 AT 4 998 0.4921 OR 4 834 0.4722 BUT 4 471 0.44 buts(1)23 WILL 4 335 0.4224 THEY 4 221 0.4125 YES 4 181 0.41 yeah(3308)26 FROM 4 180 0.4127 BY 4 179 0.4128 NOT 4 074 0.4029 SO 4 012 0.3930 GET 3 622 0.35 gets(103),getting(323),got(1587),gotten(10)31 ALL 3 352 0.3332 IF 3 339 0.3333 WHICH 3 112 0.3034 WHAT 3 074 0.3035 GO 3 060 0.30 goes(178),going(1533),went(184),gone(137)36 IT'S 2 977 0.2937 CAN 2 947 0.2938 COMPANY 2 934 0.29 companies(1092)39 YEAR 2 874 0.28 years(1058)40 SAY 2 851 0.28 says(489),saying(336),said(923)41 BUSINESS 2 837 0.28 businesses(287)42 ONE 2 761 0.27 ones(131)43 THERE 2 656 0.2644 WOULD 2 478 0.2445 ERM 2 443 0.2446 KNOW 2 439 0.24 knows(87),knowing(36),knew(67),known(132)47 THINK 2 428 0.24 thinks(46),thinking(155),thought(272)48 YOUR 2 409 0.2449 MORE 2 390 0.2350 UP 2 365 0.23 ups(44)51 WELL 2 352 0.23

292

52 NO 2 349 0.23 nos(6)53 OUR 2 342 0.2354 MARKET 2 336 0.23 markets(469),marketing(469),marketed(10)55 MAKE 2 333 0.23 makes(221),making(371),made(714)56 WORK 2 234 0.22 works(226),worked(134),working(680)57 ABOUT 2 222 0.2258 RIGHT 2 209 0.22 rights(104),righted(1)59 JUST 2 145 0.2160 OUT 2 089 0.2061 THEIR 2 084 0.2062 ITS 2 077 0.2063 OTHER 1 959 0.19 others(181)64 THAT'S 1 938 0.1965 TIME 1 917 0.19 times(228),timing(39),timed(5)66 BECAUSE 1 916 0.1967 ANY 1 913 0.1968 HE 1 806 0.1869 USE 1 746 0.17 uses(57),using(307),used(572)70 NEW 1 730 0.17 newer(8),newest(4)71 THEM 1 711 0.1772 PEOPLE 1 701 0.17 peoples(8)73 NOW 1 669 0.1674 THEN 1 665 0.1675 VERY 1 642 0.1676 SOME 1 612 0.1677 WHEN 1 578 0.1578 LIKE 1 555 0.15 likes(20),liking(1),liked(19)79 TAKE 1 543 0.15 takes(106),taking(261),took(156),taken(236)80 THAN 1 528 0.1581 MEAN 1 524 0.15 means(319),meaning(22),meant(46)82 NEED 1 493 0.15 needs(317),needing(15),needed(154)83 ALSO 1 476 0.1484 SERVICE 1 461 0.14 services(641),servicing(43),serviced(5)85 COME 1 413 0.14 comes(207),coming(330),came(184)86 WHO 1 404 0.1487 GOOD 1 386 0.14 goods(391)88 SHOULD 1 386 0.1489 PRODUCT 1 385 0.14 products(644)90 SEE 1 360 0.13 sees(23),seeing(66),sawn(2),saw(89),seen(225)91 HOW 1 351 0.1392 TWO 1 318 0.13 twos(9)93 DON'T 1 315 0.1394 PRICE 1 302 0.13 prices(417),pricing(69),priced(20)95 US 1 300 0.1396 MAY 1 294 0.1397 WANT 1 290 0.13 wants(148),wanting(24),wanted(184)98 INTO 1 276 0.1299 THING 1 243 0.12 things(693)100 SYSTEM 1 231 0.12 systems(482)

293

8.2.4 BEC Key words

a) Positive Key Words: Here the BEC top 100 positive key words are presented. Positive

key words are those that appear in the BEC corpus more frequently than in general

English (in the BNC), to a statistically significant level (Log Likelihood p = 0.000001).

The full list of positive key words can be found in Appendix 2 in Vol. II and on the CD

ROM. This list contrasts sharply with the BEC frequency list above. There is a much

greater concentration of pure business-related lexis, e.g. business, company, market and

customer, and also lexis that could be intuitively expected to be found in a Business

English environment, e.g. order, contract, mail and rate. A full discussion on this is

found in Chapter 9, Section 9.3.1.2. The key word lists show the words in order of

keyness, frequency in the smaller corpus (in this case the BEC), percentage of frequency

in the smaller corpus, frequency and percentage in the larger corpus (in this case the

BNC) and finally, the keyness value, expressed as a Log Likelihood score.

TABLE XVII: BEC POSITIVE KEY WORDS (TOP 100)

N Word BEC Freq.

BEC %

BNC Freq.

BNC % KeynessLog L.

1 BUSINESS 2 837 0.28 542 0.03 3 557.72 COMPANY 2 934 0.29 782 0.04 3 118.63 MARKET 2 336 0.23 831 0.04 2 056.14 CUSTOMER 1 199 0.12 147 1 763.05 OK 897 0.09 38 1 635.16 PRODUCT 1 385 0.14 412 0.02 1 377.27 SALE 1 210 0.12 343 0.02 1 239.48 FAX 613 0.06 32 1 085.09 MANAGEMENT 973 0.10 279 0.01 989.610 PRICE 1 302 0.13 586 0.03 941.511 FINANCIAL 780 0.08 237 0.01 765.012 BANK 940 0.09 379 0.02 749.013 BILLION 515 0.05 67 743.414 SERVICE 1 461 0.14 916 0.05 728.715 STOCK 889 0.09 350 0.02 722.516 ORDER 1 224 0.12 681 0.03 709.017 EXECUTIVE 529 0.05 86 707.318 CONTRACT 656 0.06 183 678.319 CLIENT 535 0.05 126 607.420 MAIL 380 0.04 34 607.221 CONTRACTOR 326 0.03 16 582.322 WILL 4 335 0.42 5 038 0.26 572.4

294

23 MANAGER 742 0.07 317 0.02 562.424 PER 1 014 0.10 585 0.03 562.425 SELLER 298 0.03 12 546.626 INVESTMENT 577 0.06 185 546.227 SHARE 1 148 0.11 762 0.04 528.828 INTERNET 249 0.02 1 521.029 COST 1 127 0.11 747 0.04 520.230 TO 29 495 2.88 47 851 2.44 514.531 DATE 782 0.08 389 0.02 512.332 GLOBAL 324 0.03 34 497.633 PROFIT 799 0.08 429 0.02 482.034 SELL 789 0.08 419 0.02 481.835 REGISTER 399 0.04 86 473.336 PROJECT 642 0.06 283 0.01 473.137 PERFORMANCE 507 0.05 175 455.838 YEAR 2 874 0.28 3 184 0.16 445.439 INTERNATIONAL 606 0.06 269 0.01 443.740 ITS 2 077 0.20 2 085 0.11 428.541 MILLION 789 0.08 473 0.02 417.142 CORPORATE 277 0.03 33 410.643 RATE 803 0.08 496 0.03 408.444 BUYER 292 0.03 42 407.945 CREDIT 392 0.04 110 403.846 INDUSTRY 712 0.07 404 0.02 402.847 SUPPLIER 288 0.03 44 393.948 TECHNOLOGY 445 0.04 157 393.749 BUDGET 437 0.04 152 390.750 SHALL 803 0.08 515 0.03 388.251 COPY 430 0.04 152 379.952 ACCOUNT 859 0.08 593 0.03 373.453 OUR 2 342 0.23 2 577 0.13 370.854 DISTRIBUTOR 218 0.02 16 363.555 DELIVERY 291 0.03 56 363.456 CASH 384 0.04 124 361.757 WE 7 492 0.73 10 822 0.55 349.758 COMPANY'S 263 0.03 45 344.759 AGREEMENT 470 0.05 210 0.01 342.060 GROUP 1 153 0.11 991 0.05 341.061 OFFER 733 0.07 491 0.03 333.162 GROWTH 475 0.05 224 0.01 328.363 DIRECTOR 541 0.05 289 0.01 328.264 INFORMATION 835 0.08 622 0.03 321.665 PROPERTY 400 0.04 162 317.566 NETWORK 390 0.04 156 312.867 DIGITAL 185 0.02 13 311.168 SHAREHOLDER 286 0.03 73 311.169 TEL 216 0.02 29 308.770 FOR 10 415 1.02 15 996 0.82 307.371 TERM 887 0.09 703 0.04 306.772 INVESTOR 248 0.02 51 300.773 REVIEW 380 0.04 155 299.874 EMPLOYEE 307 0.03 94 299.5

295

75 TARGET 285 0.03 79 295.776 PC 210 0.02 30 294.077 INCREASE 758 0.07 566 0.03 290.878 INVOICE 182 0.02 17 287.879 COM 160 0.02 8 285.080 INCLUDE 934 0.09 791 0.04 284.681 REGARD 477 0.05 259 0.01 284.182 PAYMENT 321 0.03 115 280.883 TAX 629 0.06 427 0.02 280.384 TRADE 696 0.07 509 0.03 276.385 OR 4 834 0.47 6 757 0.34 276.386 OFFICE 651 0.06 461 0.02 272.187 TELEPHONE 365 0.04 159 271.888 ENGINEER 368 0.04 163 269.989 MEETING 739 0.07 575 0.03 264.190 FIRM 466 0.05 265 0.01 262.991 FINANCE 298 0.03 117 242.792 NEW 1 730 0.17 1 995 0.10 234.393 SYSTEM 1 231 0.12 1 273 0.06 234.194 FOCUS 258 0.03 89 232.095 RECEIVE 534 0.05 369 0.02 231.796 PURCHASE 289 0.03 117 229.497 EXPENSE 236 0.02 73 228.798 TEAM 498 0.05 334 0.02 225.999 STRATEGY 295 0.03 125 225.2100 STRATEGIC 203 0.02 50 225.1

b) Negative Key Words: Here the BEC top 100 negative key words are presented.

Negative key words are those that appear in the BEC corpus less frequently than in

general English to a statistically significant level (Log Likelihood p = 0.000001). The

full list of negative key words can be found in Appendix 4 in Vol. II and on the CD

ROM. The negative key word list differs markedly from the positive key word list: there

is little or no business-related lexis and the words are, for example, concerned with

family (e.g. mum, child, dad), society (e.g. vote, church, police) and the home (e.g.

garden, curtain). A clear divide is thus created between lexis of the business world -

shown in the positive key words - and lexis of the non-business world - shown in these

negative key words. This is discussed in full in Chapter 9, Section 9.3.2.2.

TABLE XVIII: BEC NEGATIVE KEY WORDS (TOP 100)

N Word BEC Freq.

BEC %

BNC Freq.

BNC % KeynessLog L.

1611 ER 1 198 0.12 9 750 0.50 3 199.91610 I 8 534 0.83 31 126 1.59 3 139.11609 SHE 337 0.03 5 899 0.30 3 057.0

296

1608 OH 475 0.05 5 938 0.30 2 620.41607 MM 60 3 480 0.18 2 444.01606 HE 1 806 0.18 10 232 0.52 2 287.41605 HER 259 0.03 3 940 0.20 1 919.91604 COS 7 1 739 0.09 1 384.31603 IT 8 902 0.87 26 079 1.33 1 287.51602 HIS 912 0.09 5 234 0.27 1 187.81601 OKAY 7 1 147 0.06 892.81600 YES 4 181 0.41 13 210 0.67 863.61599 MY 861 0.08 4 349 0.22 825.01598 SAY 2 851 0.28 9 573 0.49 760.51597 HIM 405 0.04 2 703 0.14 731.81596 YOU 10 133 0.99 26 331 1.34 714.81595 ME 978 0.10 4 209 0.21 606.61594 ONE 2 761 0.27 8 830 0.45 600.51593 NO 2 349 0.23 7 784 0.40 593.51592 GET 3 622 0.35 10 875 0.55 589.01591 GO 3 060 0.30 9 168 0.47 492.01590 AH 45 886 0.05 479.91589 MAN 201 0.02 1 538 0.08 476.71588 WELL 2 352 0.23 7 359 0.38 463.81587 GOD 31 784 0.04 461.21586 DON'T 1 315 0.13 4 741 0.24 459.21585 TWENTY 126 0.01 1 212 0.06 452.41584 LIKE 1 555 0.15 5 339 0.27 452.21583 MUM 6 602 0.03 451.01582 FORMULA 35 793 0.04 450.91581 SHE'S 111 0.01 1 088 0.06 411.61580 GONNA 112 0.01 1 086 0.06 407.71579 OOH 3 483 0.02 375.51578 TELL 419 0.04 2 059 0.10 373.91577 KNOW 2 439 0.24 7 231 0.37 371.91576 MOTHER 22 607 0.03 366.01575 SEE 1 360 0.13 4 543 0.23 354.61574 DIDN'T 324 0.03 1 724 0.09 352.81573 POUND 221 0.02 1 381 0.07 347.31572 CHILD 153 0.01 1 133 0.06 340.51571 THERE 2 656 0.26 7 607 0.39 338.11570 VOTE 73 804 0.04 328.71569 NIGHT 117 0.01 979 0.05 328.01568 TWO 1 318 0.13 4 348 0.22 326.41567 GARDEN 11 465 0.02 309.41566 CHURCH 8 440 0.02 306.31565 NICE 100 876 0.04 304.61564 TH 8 431 0.02 299.11563 DO 5 298 0.52 13 343 0.68 294.91562 CURTAIN 4 394 0.02 294.61561 ROUND 156 0.02 1 048 0.05 285.61560 COME 1 413 0.14 4 437 0.23 282.91559 JOAN 3 369 0.02 281.41558 HAIR 16 450 0.02 272.81557 THEN 1 665 0.16 4 999 0.25 270.0

297

1556 LORD 27 506 0.03 269.01555 BOY 25 483 0.02 259.81554 NA 6 367 0.02 259.51553 POLICE 23 468 0.02 256.51552 FATHER 17 432 0.02 254.51551 LEAVE 369 0.04 1 647 0.08 253.91550 EAT 34 519 0.03 253.11549 THIRTY 79 710 0.04 251.91548 I'M 930 0.09 3 136 0.16 251.71547 WHAT 3 074 0.30 8 171 0.42 250.81546 WHEN 1 578 0.15 4 688 0.24 242.81545 LOVE 62 625 0.03 241.11544 KING 27 465 0.02 239.01543 WATER 143 0.01 918 0.05 238.01542 FLOWER 3 316 0.02 237.81541 LITTLE 365 0.04 1 585 0.08 232.21540 HE'S 449 0.04 1 816 0.09 230.51539 HA 6 326 0.02 226.51538 FIVE 401 0.04 1 670 0.09 225.31537 NINETEEN 4 308 0.02 224.41536 EDWARD 6 322 0.02 223.31535 HOUSE 286 0.03 1 335 0.07 222.71534 GOTTA 4 303 0.02 220.31533 PUT 741 0.07 2 558 0.13 219.81532 FABRIC 9 336 0.02 218.01531 BED 36 475 0.02 215.51530 FOUR 381 0.04 1 583 0.08 212.61529 FLAT 34 460 0.02 211.51528 LOOK 1 197 0.12 3 658 0.19 211.31527 GIRL 49 525 0.03 210.91526 REMEMBER 124 0.01 804 0.04 210.81525 EYE 50 522 0.03 206.11524 I'D 129 0.01 807 0.04 203.21523 PLAY 158 0.02 901 0.05 202.51522 DOG 33 440 0.02 200.71521 FORTY 53 524 0.03 199.41520 NINE 100 700 0.04 199.01519 DAD 13 336 0.02 198.91518 FIFTY 57 539 0.03 198.71517 EH 4 276 0.01 198.41516 WOMAN 121 0.01 768 0.04 196.61515 ERM 2 443 0.24 6 471 0.33 194.61514 I'VE 571 0.06 2 042 0.10 193.41513 SEAT 33 427 0.02 191.71512 DOWN 749 0.07 2 487 0.13 190.41511 OLD 288 0.03 1 263 0.06 188.5

8.2.5 Grammatical categorisation of BEC positive key words

298

This list can be found in Appendix 2 in Vol. II. It shows the positive key words of the

BEC categorised by word class as defined by Ljung (1990): noun, verb, adjective,

noun/verb, noun/adjective, verb/adjective, noun/verb/adjective and -ly adverbs. This is

discussed in Chapter 9, Section 9.3.2.1.

8.2.6 Semantic categorisation of BEC positive key words

This categorisation can be found in Appendix 3 in Vol. II and the categorisation is done

separately for the four largest word classes - noun, verb, adjective, noun/verb. This is

discussed in full in Chapter 9, Section 9.3.2.1.

8.2.7 Grammatical categorisation of BEC negative key word list

This list can be found in Appendix 4 in Vol. II. It shows the negative key words of the

BEC categorised by word class as defined by Ljung (1990): noun, verb, adjective,



8.2.8 Semantic categorisation of BEC negative key words




299

8.2.9 Analysis of 50 key words from the BEC

It was noted in the previous chapter (Step 5 a-h), how fifty key words from the BEC

were selected and subjected to various forms of analysis. These analyses are shown in

full in Appendix 6 in Vol. II and a detailed analysis of these words forms a major part of

Chapter 9 (Section 9.3.3 to 9.3.7), where each section is explained and interpreted.

However, an example of one of the fifty words - business - is presented here. In the

example, several different kinds of analysis are shown:

a) Keyness - how key the key word is.

b) Semantic prosody - what lexical/semantic sets the word typically collocates with -

collocating groups are shown both to the left of the main word and to the right.

c) 3-word clusters - typical 3-word clusters the word is found in or near.

d) Macro-generic distribution - the range of use of the word across the macro-genres of

the BEC shown using the Dispersion Plot function of WordSmith.

e) Colligation - how the word typically behaves grammatically, and what grammatical

patterning/meaning correlations there are, using the COBUILD (1995) dictionary as

reference.

f) Associates - key words that co-occur with the main word in a number of texts to a

statistically significant level.

g) Comments - any comments to be made on the above analyses.

EXAMPLE WORD: ÔBUSINESSÕ

a) Keyness

The lemma ‘business’ was the most significant key word in the BEC corpus.

N Word bec freq. bec lst % bnc freq. bnc.lst % Keyness P1 BUSINESS 2,837 0.28 542 0.03 3,557.8 0.000000

b) Semantic Prosody

300

Left: A total of 7 groups were identified. However, the positive and negative groups are small and are shown here to contrast positive and negative usage with the word.

semantic prosody frequency/ 2,551& % examplewhere business takes place(place)

56 - 2.19% Indian businessUK business

where business takes place(macro-level demarcation)

123 - 4.82% internationalworld-wide businessoverseas business

line of business 222 - 9.86% telecoms businesshairdressing businesscontract hire business

nature of business (characteristics)

124 - 4.86% core businessfamily businessdaily business

money/size of business 67 - 2.62% a high-yield businessbig businesssmall business

positive adjectives 50- 1.96% successful businesssound businessstrong business

negative adjectives 7 - 0.27% unviable businesscut-throat businessboring business

Right: Four groups identified.

semantic prosody frequency/ 2,551& % examplepeople and groups of people 145 - 5.68% business agents

business analystbusiness controller

business activities 135 - 5.29 % business administrationbusiness analysisbusiness development

institutions, organisations and companies

129 - 5.05% business conglomeratesbusiness schoolthe business press

macro-level demarcation 89 - 3.48% business areabusiness sectorbusiness segment

c) Three-word clusters

N cluster Freq.1 of the business 852 in the business 633 to the business 314 the business and 295 the business is 296 the business English 247 for the business 208 business and the 19

301

9 in international business 1810 the institute for 1811 a business plan 1712 for global business 1713 institute for global 1714 of business administration 1715 the business of 1616 the business plan 1417 college of business 1318 and the business 1219 business English list 1220 on the business 1221 the business community 1222 business areas and 1123 the business link 1124 as a business 1025 credits international business 1026 for your business 1027 of a business 1028 of business and 1029 of our business 930 that your business 931 with the business 932 about the business 833 any other business 834 business to business 835 out of business 836 to do business 837 a new business 738 and international business 739 business in the 740 business is not 741 from the business 742 in a business 743 into the business 744 of business English 745 of its business 746 out of the 747 the business to 748 the business unit 749 the business world 750 the local business 751 your business is 752 a business and 653 business and computing 654 business as a 655 business at the 656 business of the 657 business on the 658 business unit managers 659 in this business 660 of doing business 6

302

61 of your business 662 ordinary course of 663 part of the 664 run the business 665 some of the 666 the business at 667 the business will 668 the international business 669 the main business 670 the ordinary course 671 when the business 672 within the business 673 your business and 674 a business to 575 a lot of 576 an international business 577 as the business 578 as well as 579 at the business 580 business English and 581 business English customers 582 business English experts 583 business link and 584 develop the business 585 do business with 586 English list is 587 for new business 588 Harvard business review 589 Harvard business school 590 have a business 591 if the business 592 in any business 593 in order to 594 intermediate business English 595 international business concentration 596 it is a 597 lot of business 598 nature of the 599 new business opportunities 5100 start a business 5101 that the business 5102 the business as 5103 the business press 5104 the business that 5105 the business was 5106 the college of 5107 the company's business 5108 the core business 5109 the nature of 5110 the world business 5111 to start a 5112 today's business express 5

303

113 type of business 5114 what the business 5115 which is the 5116 within business 5117 you have a 5118 a business case 4119 a business link 4120 a business that 4121 a number of 4122 all the business 4123 and business areas 4124 as a whole 4125 at the close 4126 at the moment 4127 been in the 4128 business as usual 4129 business development manager 4130 business from the 4131 business is going 4132 business is the 4133 business law # 4134 business link placename 4135 business plan is 4136 by roland gribben 4137 by the business 4138 cent of the 4139 close of business 4140 core property business 4141 course of business 4142 development of the 4143 globalisation of business 4144 go into business 4145 going into business 4146 I’ve been in 4147 if you are 4148 if you have 4149 in terms of 4150 in that business 4151 in the ordinary 4152 in the uk 4153 in your business 4154 international business # 4155 international business and 4156 international business finance 4157 international business program 4158 international business programs 4159 into business with 4160 involved in the 4161 it is not 4162 just the business 4163 knutsford business centre 4164 law # credits 4

304

165 line of business 4166 look at the 4167 main business customers 4168 minor in international 4169 normal business hours 4170 of business life 4171 of business on 4172 of international business 4173 of the institute 4174 one of the 4175 our core business 4176 over the next 4177 parts of the 4178 per cent of 4179 place of business 4180 price for the 4181 record in business 4182 side of the 4183 small business administration 4184 small business owners 4185 sort of business 4186 that's today's business 4187 the business areas 4188 the business has 4189 the business in 4190 the business list 4191 the business mix 4192 the business team 4193 the close of 4194 the end of 4195 the small business 4196 the university of 4197 this business is 4198 to concentrate on 4199 to develop the 4200 to your business 4201 university of akron 4202 volume of business 4203 we do business 4204 with a business 4205 world business review 4

d) Macro-generic distribution

305

N File Words Hits per 1,000 Plot1 combrocs.txt 23 142 217 9.382 uktv.txt 19 335 157 8.123 misc.txt 2 373 19 8.014 jobads.txt 22 119 141 6.375 presrel.txt 21 519 90 4.186 books.txt 53 255 219 4.117 wspa~1.txt 63 895 191 2.998 interv~1.txt 71 828 213 2.979 mags&j~1.txt 78 749 220 2.79

10 reports.txt 62 364 169 2.7111 anreps.txt 32 779 82 2.5012 negoti~1.txt 16 762 38 2.2713 ustv.txt 77 588 171 2.2014 reem~1.txt 29 492 61 2.0715 radio.txt 52 736 107 2.0316 buslet~1.txt 26 749 48 1.7917 meetings.txt 128 543 217 1.6918 prodbr~1.txt 25 984 41 1.5819 emails.txt 28 497 40 1.4020 minutes.txt 34 240 43 1.2621 speeches.txt 18 968 16 0.8422 faxes.txt 23 210 18 0.7823 memos.txt 12 388 7 0.5724 quotatns.txt 8 893 5 0.5625 manuals.txt 20 492 8 0.3926 training.txt 18 104 6 0.3327 jobints.txt 17 783 3 0.1728 phone.txt 31 461 4 0.13

* Each file represents one macro-genre found in the BEC - key to file names in Appendix 19, Vol. II, p.971.

This dispersion plot shows:File: The rank frequency order of macro-genres where business appeared (thus, for example, business was most frequent in Company Brochures - Combrocs.txt, and second most frequent in UK television programmes - uktv.txt).Words: The number of words in each macro-genre - one file for each macro-genre.Hits per 1,000: How many hits of the word business per 1,000 words there were in each macro-genre/filePlot: Each time the word business occurs in a macro-genre/file it is marked by a small black line, thus showing its distribution of occurrence over all the texts in each macro-genre. For example, in company brochures we see heavy usage at the right-hand side, indicating that business occurred in these texts very often, and less in others, creating an uneven distribution across the company brochures macro-genre.

e) Colligation

COBUILD Sense 1 (work relating to the buying and selling of goods)1,351 instances 52.95% of samplePatterns: Uncount nounwe put together a business plan... greatly affected the way they did business

306

carried out in cooperation with our business partners

COBUILD Sense 2 (how many products/services a company is able to sell)163 instances 6.38% of samplePatterns: Uncount nounbusiness fell by a third

COBUILD Sense 3 (a company/firm)523 instances 20.5% of sample Patterns: Count noun We go into a business and try and rescue itYou must think of the pros and cons of starting a business from scratch

COBUILD Sense 4 (what you do for your job and not for pleasure)8 instances 0.31% of samplePatterns: Uncount nounTravel agencies have special departments dealing with business travela business dinner to end all business dinners

COBUILD Sense 5 (line of business)436 instances 17.09% of samplePatterns: Singular nountelecoms business, hairdressing business, contract hire business, my line of business

COBUILD Sense 7 (important matters you have to deal with)3 instances 0.11% of samplePatterns: Uncount nounconduct the following business, any other business?

COBUILD Sense 8 (my own business - no-one else’s concern)2 instances 0.07% of samplePatterns: Uncount nounIts not my business to manage a business

COBUILD Sense 9 (an event, situation or activity)4 instances 0.15% of samplePatterns: Singular noun with the forty pound businessthe business of liststhe business of making strategic choices

COBUILD Sense 10 (an unpleasant or costly task)3 instances 0.11% of samplePatterns: Singular nounIll health - a costly businessit’s always been a dangerous business

COBUILD Sense 11 (big business/show business)big business: 8 instances 0.31% of sampleshow business: 1 instance 0.03% of sample

COBUILD Sense 12 (do business - companies/people that do business with each other)13 instances 0.5% of samplePatterns: Phrase with noun

307

N Concordance7 you before that recommend strongly f course. But we would do business and certainly with overseas companies, that y8 from refraining (v) Israel; supports to any organization which doing business in or with Israel or with any person who doe9 to people good are they l partners look for reassurance that do business with before they look at the deal itself. Orga

10 to forward look I wave. with the products supplied by Heat doing business with you and Companyname. Sincerely, 11 to happy I'm know, you worked with for a while that I trust, do business with them, I would prefer to put all the busines

COBUILD Sense 14 (in business: a company that is currently operating or trading)9 instances 0.35% of samplePatterns: verb + link phraseyou’ve already been in business for a period of timeyou may find after a year in business that you need bigger premises

COBUILD Sense 16 (to mean business)1 instance 0.03% of samplePatterns: Verb (inflect)gives further evidence that Daimler means business

COBUILD Sense 20 (out of + business)8 instances 0.31% of samplePatterns: phrase after verb

N Concordance1 gone has supplier the because tract is not fulfilled, perhaps out of business, you may still be able to sue TIFCO. If you2 effectively now are banks - merchant country's 30 out of business. The remaining banks must sub3 went us like people most , Gantcher says: "After Mayday, out of business. We were able to survive when we should h4 went companies smaller the of through the industry, many out of business, while others were forced to merge. Those 5 be we'd costs running our inroads into paying out of business because we didn't have that la6 forced be can You penalty. will meet a significant financial out of business for not paying a debt as low as Z50, so it i7 knocked then was it Unfortunately erty back into business. out of business by a hurricane after I left. I've also run the 8 go to about aren't we - things may be difficult right now, but out of business." As it becomes impossible to deny t

COBUILD Sense 22 (business as usual)4 instances 0.15% of samplePatterns: usually verb link phraseBusiness as usual is a common refrain ...

ADDITIONAL Senses:

Conversational filler: 2 instances 0.07% of sampleall this sort of businessthat sort of business, you know. The usual story

Other COBUILD entries:business card: 2 instances business class: 5 instances business hours: 5 instances Other patterns:

i) In the BEC, ‘business’ occurs in an end of sentence position 267 times, (10.46% of sample).‘Business’ in the PMC occurs 157 times (15.49%) of sample.... to show that we mean business.... a climate for creativity in business.

ii) possessive pronoun + business:163 instances 6.38% of sample

308

In the PMC there were 68 instances 6.81% of samplemy own business, your business

iii) definite article the + business 485 instances 19.01% of sampleThere are links between definite article usage and COBUILD senses 3 & 5:The minimum target for the business to survive is £250 million (sense 3)How did you come into the business then originally, the car business? (sense 5)

iv) indefinite article a + business 127 instances 4.97% of sampleThere are links between indefinite article usage and COBUILD Sense 3:The skills that are needed to start a business

Points iii) and iv) above are true except when ‘business’ is used as part of a noun group:the business community, the business mix for 1993 was 65.5% personal ....a business magazine

v) noun group + of + business (these refer to process/activity/people/place/amount related to business)150 instances 5.88% of sampleprinciple place of business, major branch of business, close of business

vi) do + business41 instances 1.6% of sampleThis compares to 59 instances in the PMC - 5.81% of sample.

f) Associates

N WORD NO. OF FILES AS %1 BUSINESS 109 100.002 COMPANY 27 24.773 WE 21 19.274 CUSTOMER 19 17.435 MANAGEMENT 19 17.436 BUSINESSES 18 16.517 MARKET 18 16.518 CUSTOMERS 18 16.519 COMPANIES 17 15.6010 SALES 16 14.6811 ITS 15 13.7612 FINANCIAL 13 11.9313 GROUP 13 11.9314 SERVICES 12 11.0115 SHARE 11 10.0916 PROFIT 11 10.0917 OR 11 10.0918 COST 11 10.0919 SYSTEMS 11 10.0920 PER 10 9.1721 PEOPLE 10 9.1722 ARE 10 9.1723 WILL 10 9.1724 PRODUCTS 10 9.1725 SO 10 9.17

309

26 CASH 10 9.1727 OUR 10 9.1728 MILLION 10 9.1729 OK 9 8.2630 GLOBAL 9 8.2631 CORE 9 8.2632 REPORTING 9 8.2633 BILLION 9 8.2634 INDUSTRY 8 7.3435 NEW 8 7.3436 MANUFACTURING 8 7.3437 MARKETS 8 7.3438 YEAR 8 7.3439 GROWTH 8 7.3440 FIRMS 8 7.3441 PRODUCT 8 7.3442 DEVELOPMENT 8 7.3443 ASSETS 8 7.3444 CORPORATE 8 7.3445 BE 8 7.3446 BANK 8 7.3447 MARKETING 7 6.4248 IS 7 6.4249 INTERNET 7 6.4250 SUPPLIERS 7 6.4251 SOLUTIONS 7 6.4252 TAX 7 6.4253 TEAM 7 6.4254 ORGANISATION 7 6.4255 MAY 7 6.4256 SELL 7 6.4257 PRICE 7 6.4258 YOUR 7 6.4259 ERM 7 6.4260 CEO 7 6.4261 INCREASE 7 6.4262 CAPITAL 7 6.4263 EXECUTIVES 7 6.4264 IN 7 6.4265 EXECUTIVE 7 6.4266 EARNINGS 7 6.4267 INTERNATIONAL 7 6.4268 BANKS 7 6.4269 COMPETITIVE 7 6.4270 DIRECTORS 6 5.5071 SHAREHOLDERS 6 5.5072 SHARES 6 5.5073 COSTS 6 5.5074 SERVICE 6 5.5075 PERFORMANCE 6 5.5076 DO 6 5.5077 TOTAL 6 5.50

310

78 THEY 6 5.5079 BECAUSE 6 5.5080 WE'VE 6 5.5081 AVERAGE 6 5.5082 ACCOUNTING 6 5.5083 BUDGET 6 5.5084 SOFTWARE 6 5.5085 SIGNIFICANT 6 5.5086 STRATEGIC 6 5.5087 STOCK 6 5.5088 YOU 6 5.5089 NET 6 5.5090 MR 6 5.5091 EQUITY 6 5.5092 OPERATING 6 5.5093 INFORMATION 6 5.5094 INVESTMENTS 6 5.5095 MANAGERS 6 5.5096 MANAGER 6 5.5097 INVESTMENT 6 5.5098 EMPLOYEE 6 5.5099 BOOK 5 4.59100 LEADERSHIP 5 4.59101 TECHNOLOGIES 5 4.59102 PERCENT 5 4.59103 MANAGING 5 4.59104 BOOKS 5 4.59105 STRATEGY 5 4.59106 IMPORTANT 5 4.59107 INCREASED 5 4.59108 THERE'S 5 4.59109 DIVISION 5 4.59110 IT'S 5 4.59111 ORGANIZATIONAL 5 4.59112 TEND 5 4.59113 TECHNOLOGY 5 4.59114 THAT 5 4.59115 TERM 5 4.59116 ACTIVITIES 5 4.59117 RESULTS 5 4.59118 RESEARCH 5 4.59119 CO 5 4.59120 COMMERCIAL 5 4.59121 SELLING 5 4.59122 PROFITS 5 4.59123 PRICES 5 4.59124 COMPANY'S 5 4.59125 PURCHASE 5 4.59126 DEAL 5 4.59127 SHOULD 5 4.59128 NEED 5 4.59129 FINANCE 5 4.59

311

130 OPPORTUNITIES 5 4.59131 HAS 5 4.59132 CLIENTS 5 4.59133 OF 5 4.59134 DIRECTOR 5 4.59135 OBVIOUSLY 5 4.59

Comments (these focus both on the BEC and also on BEC/PMC differences)

1. Phrases in the BEC not included or under-represented in the PMC: close of business, place of business, business as usual, business hours

2. Any other business: used much more widely than in the PMC. In the PMC it is used solely in terms of agendas/meetings, i.e. AOB. In the BEC it is only used twice like this and otherwise to refer to other businesses, e.g. as a computer business or any other business.

3. On business: Again the prepositional phrase ‘on business’ has a much broader usage than is represented in the PMC. There it is used almost solely for Sense 4, i.e. to be on business rather than pleasure (19/21 instances). In the BEC (15 instances 0.58% of sample), it is not used once in this sense but rather as connective preposition, e.g. VAT on business expenses, advising them on business plans.

8.2.10 BEC 3-6 word cluster frequency lists

In this section, examples of 3-6 word frequency clusters from the BEC are presented. A

minimum cut-off level of 10 occurrences was used for the 5- and 6-word clusters, as their

number was considerably less than the 3- and 4-word clusters. For the 3- and 4-word

clusters, a minimum cut-off level of 50 instances was used. Fuller lists of the clusters can

be found on the CD ROM. Two points can be made here about these clusters. Firstly, that

the longer clusters (5-6 word) show a low overall frequency and seem to be highly genre-

specific, and secondly, that the short clusters (3-word) are much higher in frequency and

appear much less tied to any specific genre. This is discussed in detail in Chapter 9,

Section 9.3.6.

TABLE XIX: 6-WORD FREQUENCY CLUSTERS

N Word Freq.1 A DIVISION OF COMPANYNAME PLC REGISTERED 362 DIVISION OF COMPANYNAME PLC REGISTERED OFFICE 363 AT THE END OF THE DAY 324 HAVE ANY DIFFICULTY RECEIVING THIS TRANSMISSION 305 IF YOU HAVE ANY DIFFICULTY RECEIVING 306 YOU HAVE ANY DIFFICULTY RECEIVING THIS 307 A DIVISION OF COMPANYNAME HOLDINGS PLC 218 DIVISION OF COMPANYNAME HOLDINGS PLC REGISTERED 219 OF COMPANYNAME HOLDINGS PLC REGISTERED OFFICE 21

312

10 LOOK FORWARD TO HEARING FROM YOU 2011 PLEASE DO NOT HESITATE TO CONTACT 2012 DO NOT HESITATE TO CONTACT ME 1913 PERSONNAME TOTAL PAGES INCLUDING THIS PAGE 1914 DIFFICULTY RECEIVING THIS TRANSMISSION PLEASE ADVISE 1415 HOW TO BUY RUN A 1416 RECEIVING THIS TRANSMISSION PLEASE ADVISE AT 1417 THIS TRANSMISSION PLEASE ADVISE AT ONCE 1418 TO BUY RUN A SHOP 1419 TEXT DECODER WITH # PAGE MEMORY 1320 THE SUPPLIER SHALL ESTABLISH AND MAINTAIN 1321 AT THE END OF THE YEAR 1222 FIM # # MILLION IN # 1223 NINE ELMS LANE LONDON SW# #DR 1224 A DIVISION OF COMPANYNAME COMPANY REGISTERED 1125 CRISPINS DUKE STREET NORWICH NR# #PD 1126 DIVISION OF COMPANYNAME COMPANY REGISTERED NUMBER 1127 ENGLAND NO # INVESTOR IN PEOPLE 1128 FIM # # MILLION FIM # 1129 IN ENGLAND NO # INVESTOR IN 1130 MILLION FIM # # MILLION IN 1131 PRESS RELEASE IS TRANSMITTED ON BEHALF 1132 REGISTERED IN ENGLAND NO # INVESTOR 1133 RELEASE IS TRANSMITTED ON BEHALF OF 1134 ST CRISPINS DUKE STREET NORWICH NR# 1135 THIS PRESS RELEASE IS TRANSMITTED ON 1136 A COMPANY LIMITED BY GUARANTEE REGISTERED 1037 ARE PROJECTED TO INCREASE BY # 1038 BETWEEN THE BUYER AND THE SELLER 1039 BY GUARANTEE REGISTERED IN ENGLAND NO 1040 COMPANY LIMITED BY GUARANTEE REGISTERED IN 1041 COMPANYNAME INTERNAL MEMO COMPANYNAME LIMITED

COMPANYADDRESS10

42 FACSIMILE #-# # E-MAIL 1043 GUARANTEE REGISTERED IN ENGLAND NO # 1044 I LOOK FORWARD TO HEARING FROM 1045 LIMITED BY GUARANTEE REGISTERED IN ENGLAND 1046 MANCHESTER M# #KI TELEPHONE #-# 1047 SUPPLIER SHALL ESTABLISH AND MAINTAIN PROCEDURES 1048 TELEPHONE #-# # FACSIMILE # 10

TABLE XX: 5-WORD FREQUENCY CLUSTERS

N Word Freq.1 AT THE END OF THE 722 A MEMBER OF COMPANYNAME INTERNATIONAL 573 A DIVISION OF COMPANYNAME PLC 364 DIVISION OF COMPANYNAME PLC REGISTERED 365 OF COMPANYNAME PLC REGISTERED OFFICE 366 TOTAL PAGES INCLUDING THIS PAGE 36

313

7 THE END OF THE DAY 338 COMPANYADDRESS REGISTERED IN ENGLAND NO 329 ANY DIFFICULTY RECEIVING THIS TRANSMISSION 3010 HAVE ANY DIFFICULTY RECEIVING THIS 3011 IF YOU HAVE ANY DIFFICULTY 3012 YOU HAVE ANY DIFFICULTY RECEIVING 3013 AS A RESULT OF THE 2914 DO NOT HESITATE TO CONTACT 2515 FOR THE ATTENTION OF MR 2416 FORWARD TO HEARING FROM YOU 2317 THE END OF THE YEAR 2318 A DIVISION OF COMPANYNAME HOLDINGS 2119 A LEVEL # PERFORMER WILL 2120 COMPANYNAME HOLDINGS PLC REGISTERED OFFICE 2121 DIVISION OF COMPANYNAME HOLDINGS PLC 2122 OF COMPANYNAME HOLDINGS PLC REGISTERED 2123 PLEASE DO NOT HESITATE TO 2124 COMPANYNAME LIMITED COMPANYADDRESS ENGLAND TEL 2025 LOOK FORWARD TO HEARING FROM 2026 NOT HESITATE TO CONTACT ME 1927 PERSONNAME TOTAL PAGES INCLUDING THIS 1928 MORE THAN # PER CENT 1729 THE INSTITUTE FOR GLOBAL BUSINESS 1730 ARE PROJECTED TO INCREASE BY 1631 CHAMBER OF COMMERCE INDUSTRY 1632 SHARING IN THE BOARDROOM # 1633 THE YEAR ENDED #ST MARCH 1534 YOU KNOW WHAT I MEAN 1535 BUY RUN A SHOP 1436 DIFFICULTY RECEIVING THIS TRANSMISSION PLEASE 1437 HOW TO BUY RUN 1438 RECEIVING THIS TRANSMISSION PLEASE ADVISE 1439 THIS TRANSMISSION PLEASE ADVISE AT 1440 TO BUY RUN A 1441 TRANSMISSION PLEASE ADVISE AT ONCE 1442 AND THAT SORT OF THING 1343 BY THE END OF # 1344 BY THE END OF THE 1345 DECODER WITH # PAGE MEMORY 1346 DUKE STREET NORWICH NR# #PD 1347 HOW LONG HAVE YOU WORKED 1348 I LOOK FORWARD TO HEARING 1349 IT WAS AGREED THAT THE 1350 NINE ELMS LANE LONDON SW# 1351 ST CRISPINS DUKE STREET NORWICH 1352 SUPPLIER SHALL ESTABLISH AND MAINTAIN 1353 TEXT DECODER WITH # PAGE 1354 THE SUPPLIER SHALL ESTABLISH AND 1355 A COMPANY LIMITED BY GUARANTEE 1256 CRISPINS DUKE STREET NORWICH NR# 1257 ELMS LANE LONDON SW# #DR 1258 FIM # # MILLION IN 12

314

59 NEED TO BE ABLE TO 1260 PROJECTED TO INCREASE BY # 1261 THE BUYER AND THE SELLER 1262 THE PRICE OF THE GOODS 1263 THE PROFIT AND LOSS ACCOUNT 1264 THE SELLER SHALL BE ENTITLED 1265 A DIVISION OF COMPANYNAME COMPANY 1166 AGREED IN WRITING BETWEEN THE 1167 AT THE ANNUAL GENERAL MEETING 1168 AT THE END OF # 1169 DIVISION OF COMPANYNAME COMPANY REGISTERED 1170 ENGLAND NO # INVESTOR IN 1171 FIM # # MILLION FIM 1172 FOR THE FIRST TIME IN 1173 IF YOU ARE GOING TO 1174 IF YOU WOULD LIKE TO 1175 IN ENGLAND NO # INVESTOR 1176 IS TRANSMITTED ON BEHALF OF 1177 MEMO COMPANYNAME LIMITED COMPANYADDRESS TEL 1178 MILLION FIM # # MILLION 1179 NO # INVESTOR IN PEOPLE 1180 NOTES TO CONSOLIDATED FINANCIAL STATEMENTS 1181 OF COMPANYNAME COMPANY REGISTERED NUMBER 1182 ONE OF THE THINGS THAT 1183 PRESS RELEASE IS TRANSMITTED ON 1184 REGISTERED IN ENGLAND NO # 1185 RELEASE IS TRANSMITTED ON BEHALF 1186 THE DOW JONES INDUSTRIAL AVERAGE 1187 THIS PRESS RELEASE IS TRANSMITTED 1188 WE HAVE A LOT OF 1189 AT THE BEGINNING OF THE 1090 BETWEEN THE BUYER AND THE 1091 BRITISH EMBASSY COMMERCIAL SECTION BUDAPEST 1092 BY GUARANTEE REGISTERED IN ENGLAND 1093 COMPANY LIMITED BY GUARANTEE REGISTERED 1094 COMPANYNAME INTERNAL MEMO COMPANYNAME LIMITED 1095 FACSIMILE #-# # E 1096 GUARANTEE REGISTERED IN ENGLAND NO 1097 IN THE SECOND HALF OF 1098 INTERNAL MEMO COMPANYNAME LIMITED COMPANYADDRESS 1099 JULIAN HULSE # OXFORD STREET 10100 LIMITED BY GUARANTEE REGISTERED IN 10101 MANCHESTER M# #KI TELEPHONE # 10102 MEMBER OF THE GROUPNAME GROUP 10103 OF THE BANK OF ENGLAND 10104 SHALL ESTABLISH AND MAINTAIN PROCEDURES 10105 TELEPHONE #-# # FACSIMILE 10106 THE ARCHITECTTHE CONTRACT ADMINISTRATOR SHALL 10107 THE CONTRACTOR UNDER THIS CONTRACT 10108 TO MAKE SURE THAT THE 10109 WE ARE GOING TO DO 10

315

TABLE XX1: 4-WORD FREQUENCY CLUSTERS

N Word Freq.1 AT THE END OF 1272 THE END OF THE 1173 AT THE SAME TIME 854 TO BE ABLE TO 765 REGISTERED IN ENGLAND NO 706 AS A RESULT OF 697 A DIVISION OF COMPANYNAME 688 WE ARE GOING TO 649 A LEVEL # PERFORMER 5710 A MEMBER OF COMPANYNAME 5711 IF YOU HAVE ANY 5712 MEMBER OF COMPANYNAME INTERNATIONAL 5713 IN ACCORDANCE WITH THE 5314 IF YOU WANT TO 4815 THE REST OF THE 4816 ON THE BASIS OF 4717 A LOT OF PEOPLE 4518 BY THE END OF 4319 COMPANYADDRESS REGISTERED IN ENGLAND 4220 IS GOING TO BE 4121 THANK YOU FOR YOUR 4122 THAT SORT OF THING 4123 IS ONE OF THE 3924 WILL BE ABLE TO 3825 IN THE UNITED STATES 3726 THE MARKETING WORKING GROUP 3727 TO MAKE SURE THAT 3728 YOU ARE GOING TO 3729 A WIDE RANGE OF 3630 COMPANYNAME PLC REGISTERED OFFICE 3631 DIFFICULTY RECEIVING THIS TRANSMISSION 3632 DIVISION OF COMPANYNAME PLC 3633 OF COMPANYNAME PLC REGISTERED 3634 PAGES INCLUDING THIS PAGE 3635 PLEASE ADVISE AT ONCE 3636 THE BANK OF ENGLAND 3637 TOTAL PAGES INCLUDING THIS 3638 A COPY OF THE 3539 IN THE CASE OF 3540 IT'S GOING TO BE 3541 PER CENT OF THE 3542 END OF THE DAY 3443 FOR THE ATTENTION OF 3444 FOR THE FIRST TIME 3445 THE END OF # 3446 A BIT OF A 3347 THANK YOU VERY MUCH 33

316

48 AS WELL AS THE 3249 OR SOMETHING LIKE THAT 3250 THEY ARE GOING TO 32

TABLE XXII: 3-WORD FREQUENCY CLUSTERS

N Word Freq. bec %1 A LOT OF 451 0.042 ONE OF THE 329 0.033 THE END OF 249 0.024 AT THE MOMENT 225 0.025 BE ABLE TO 224 0.026 GOING TO BE 221 0.027 AS WELL AS 219 0.028 I DON'T KNOW 210 0.029 IN ORDER TO 190 0.0210 ARE GOING TO 175 0.0211 SOME OF THE 173 0.0212 IN TERMS OF 169 0.0213 PART OF THE 167 0.0214 A NUMBER OF 163 0.0215 THERE IS A 163 0.0216 END OF THE 152 0.0117 I DON'T THINK 152 0.0118 IN THE UK 151 0.0119 WE NEED TO 148 0.0120 AT THE END 140 0.0121 YOU HAVE TO 140 0.0122 MORE THAN # 136 0.0123 YOU WANT TO 131 0.0124 OF THE COMPANY 127 0.0125 IF YOU HAVE 120 0.0126 IT WOULD BE 119 0.0127 NEED TO BE 118 0.0128 TO BE A 117 0.0129 OUT OF THE 114 0.0130 WE HAVE TO 114 0.0131 AND I THINK 113 0.0132 IN THE PAST 108 0.0133 THIS IS A 108 0.0134 WE HAVE A 108 0.0135 A COUPLE OF 107 0.0136 HAVE TO BE 105 0.0137 THE FACT THAT 105 0.0138 WOULD LIKE TO 104 0.0139 IF YOU ARE 10140 IN ACCORDANCE

WITH101

41 THE UNITED STATES

101

317

42 YOU'VE GOT TO 10143 AS A RESULT 10044 IS GOING TO 9945 YOU NEED TO 9746 AT THE SAME 9647 I THINK THE 9648 THERE WAS A 9649 TO HAVE A 9650 IT WILL BE 94

8.2.11 Key BEC 3-word clusters

Here, the key 3-word clusters of the BEC are presented. Only the top 50 are shown. For a

fuller list see the CD ROM. These 3-word clusters differ from the 3-word frequency

clusters above by being much less frequent and seemingly more genre- or business area-

specific. See Chapter 9, Section 9.3.6.1 for a fuller discussion on this.

TABLE XXIII: KEY BEC 3-WORD CLUSTERS

N Word BECFreq.

BEC % BNCFreq.

BNC%

KeynessLog L.

1 REGISTERED IN ENGLAND 85 0 182.02 A DIVISION OF 74 0 158.53 IN ENGLAND NO 70 0 149.94 DIVISION OF

COMPANYNAME69 0 147.7

5 OF THE GOODS 72 3 131.56 A LEVEL # 58 0 124.27 PLC REGISTERED OFFICE 57 0 122.08 MEMBER OF

COMPANYNAME57 0 122.0

9 OF COMPANYNAME INTERNATIONAL

57 0 122.0

10 LEVEL # PERFORMER 57 0 122.011 ARE GOING TO 175 0.02 82 121.712 OF THE BUSINESS 83 11 119.113 IN THE BUSINESS 63 2 118.714 IN THE UK 151 0.01 65 113.715 COMPANYNAME LIMITED

COMPANYADDRESS52 0 111.3

16 THE EXECUTIVE COMMITTEE

51 0 109.2

17 BY THE SELLER 50 0 107.118 THE PHARE PROGRAMME 50 0 107.119 TERMS AND CONDITIONS 46 0 98.5

318

20 THE SUPPLIER SHALL 46 0 98.521 THE = THE 45 0 96.422 MARKETING WORKING

GROUP44 0 94.2

23 BY THE BUYER 43 0 92.124 COMPANYADDRESS

REGISTERED IN42 0 89.9

25 THE BUYER SHALL 42 0 89.926 OF THIS AGREEMENT 41 0 87.827 IN ACCORDANCE WITH 101 37 86.928 THE MARKETING

WORKING40 0 85.6

29 INCLUDING THIS PAGE 40 0 85.630 THE PROPERTY WILL 39 0 83.531 IF YOU ARE 101 39 83.432 PAGES INCLUDING THIS 38 0 81.433 OF COMPANYNAME PLC 38 0 81.434 ON WALL STREET 38 0 81.435 OF THE SELLER 38 0 81.436 COMPANYNAME PLC

REGISTERED37 0 79.2

37 AND = AND 37 0 79.238 IF YOU HAVE 120 0.01 60 78.239 PLEASE ADVISE AT 36 0 77.140 SHALL NOT BE 36 0 77.141 TOTAL PAGES INCLUDING 36 0 77.142 DIFFICULTY RECEIVING

THIS36 0 77.1

43 RECEIVING THIS TRANSMISSION

36 0 77.1

44 ADVISE AT ONCE 36 0 77.145 OF THE COMPANY 127 0.01 68 76.846 TO THE CONTRACTOR 35 0 74.947 THE SELLER SHALL 35 0 74.948 TO THE BUYER 41 2 73.349 FIM # # 34 0 72.850 YOU HAVE ANY 72 21 72.4

8.2.12 Analysis of five key 2-word clusters from the BEC

Five 2-word clusters were chosen (discussed in Chapter 7, Step 5 f) and subjected to the

same analysis as the single words shown in Section 8.2.9 above. These clusters can be

found in full in Appendix 7 in Vol. II and fuller treatment is given in Chapter 9, Section

9.3.6.2. An example, interest rates, is shown below:

EXAMPLE 2-WORD CLUSTER: ÔINTEREST RATESÕ

319

a) Keyness

‘Interest rates’ was the seventy-first most significant 2-word cluster in the BEC corpus.

N Word bec freq. bec.lst % bnc freq. bnc.lst % Keyness P71 INTEREST

RATES127 0.01 37 - 127.9 0.000000

b) Semantic Prosody

Left: Five groups identified. An interesting, though not surprising factor, is the semantic prosody concerning the upward and downward movement of interest rates. Where higher interest rates are mentioned they are often accompanied by very negative language:

N Concordance18 high extremely meant has it ecause interest rates." Those high interest r19 high murderously having by problem, another interest rates. And that is typical of the kind o20 high Those rates." interest high mely interest rates have been disastrous for the he21 high using tactics similar when d in East Asia interest rates were used unsuccessfully last y

Conversely, where lower interest rates are mentioned these examples are often accompanied by positive co-text:

N Concordance61 low news – economic favorable Market-.77. interest rates, more dealmaking in the bankin62 low platter: a on managers lly been handed to interest rates, modest wage increase63 Low Stanley. Morgan at Pavoncelli tion," says interest rates in many countries are also a co64 low very inflation, low very overall economy – interest rates, very low unemployment, the lo65 low with climate--economic favorable interest rates and benign labor costs--the co66 lower 1993, During 1994. in nancing activities interest rates increased the amount of servici67 lower current the of advantage wers are taking interest rates by issuing longer-term bonds an

A third semantic group contains the lexis of containment:

N Concordance86 peg to promise to England ing for the Bank of interest rates for a fixed period amid growing f

N Concordance1 and inflation keeping growth, economic in US interest rates in check. Maria. MARIA BAR

N Concordance58 keep help and expansion American moderate interest rates in check. + The RUPIAH soa

Thus, interest rates can be seen as an evil to be contained: feared on the rise and celebrated on the fall.

semantic prosody frequency/ 127 & % examplemovement upwards/high level

46 - 36.22%* higher interest ratesrise in interest ratesRussia raised interest rates

movement downwards/low level

18- 14.17% if it reduces interest ratesit is the decline in interest ratesfalling interest rates

time 10 - 7.87% long-term interest ratesshort-term interest rates

320

containment/control 7 - 5.51% set interest ratespeg interest rates

decisions 7 - 5.51% The decision to raise interest rates from 7pc to 7.25pc

* Included here are two instances of right of the node lexis, e.g. forced interest rates up sharply.

Right: No groups identified.


N cluster Freq.1 higher interest rates 122 in interest rates 113 low interest rates 114 term interest rates 105 high interest rates 96 interest rates and 97 of interest rates 88 interest rates are 79 on interest rates 610 interest rates by 511 interest rates in 512 raise interest rates 513 interest rates have 414 interest rates to 415 interest rates up 416 interest rates will 417 rise in interest 4


N File Words Hits per 1,000 Plot1 radio.txt 52 732 32 0.612 speeches.txt 18 967 11 0.583 newspa~1.txt 63 893 32 0.504 minutes.txt 34 238 9 0.265 mags&j~1.txt 78 742 19 0.246 prodbr~2.txt 25 981 6 0.237 ustv.txt 77 580 11 0.148 anreps.txt 32 773 2 0.069 books.txt 53 246 3 0.06

10 presrel.txt 21 516 1 0.0511 combrocs.txt 23 141 1 0.04

e) Colligation

i) noun + in + interest rates: (the nouns show movement - mostly upwards)11 instances - 8.66% of sample (upwards movement verbs 8/11)

321

N Concordance39 in decline the is it Among these gift horses, interest rates that has done the mo40 in hike term short-a terms of political stability, interest rates is profoundly more tolerable tha41 in increase cent per 1/4 he Bank announced a interest rates, to 6 1/4 per cent, at 11am that 42 in increases five the to ontinue to ebb, thanks interest rates - with perhaps one or two more 43 in move next the on betting billions of pounds interest rates, have become obsessed with th44 in reductions recent the to nt positive reaction interest rates. Competition for high quality st45 in rise a or slowdown the event of a business interest rates, it would pop right bac46 in rise a morning that the Bank recommended interest rates of 1/4 percentage point. 32.In di47 in rise point quarter a independence with interest rates - the message again h48 in rise some expecting clearly l markets were interest rates. They were anticipating a rise of49 in rises five the after ers may have taken fright interest rates since May and are refusing to s

f) Associates

‘Interest rates’ was key in 12 files. The only associate of frequency > =5 was ‘interest rates’ itself.

Comments

1. The semantic prosody category decisions was gained using a 10:10 span concordance search. It has typical patterns: noun-on-noun or noun-to-inf-noun:

N Concordance1 for responsibility operational give to cision, in May, interest rates to the Bank of England - essentially, 2 Interest rates: the eight men who will decide By 3 on decide to due is d's Monetary Policy Committee interest rates on Thursday. In theory, the MPC is s4 on decisions Committee's Policy Monetary that the interest rates are announced immediately; and that5 on Decisions framework. structured a ducted within interest rates are taken by a Monetary Policy Com6 raise to was do to had decided that the right thing interest rates by a 1/4 per cent, as the Governor re7 raise to decision THE Correspondent interest rates from 7pc to 7.25pc last

8.2.13 Analysis of five 3-word clusters from the BEC

Five 3-word clusters were chosen (discussed in Chapter 7, Step 5 f), and subjected to the

same analysis as the fifty single words noted in Section 8.2.9 above. These clusters can

all be found in Appendix 8 in Vol. II. They are discussed in more detail in Chapter 9,

Section 9.3.6.2. An example, in order to, is shown below:

EXAMPLE 3-WORD CLUSTER: ÔIN ORDER TOÕ

a) Keyness

‘In order to’ was the fifty-fifth most significant key three-word cluster in the BEC corpus.

N Word bec freq. bec.lst % bnc freq. bnc.lst % Keyness P55 IN

ORDER TO

190 0.02 151 - 65.3 0.000000

322

b) Semantic Prosody

Left: No groups identified.

Right: One group identified. The verbs following ‘in order to’ were quite diverse, but the members of the group all showed a positive goal, result or outcome of the action. Even seemingly negative phrases had a positive connotation, e.g. in order to + avoid: specifying how to pre-empt difficult situations (5 instances in the sample):

N Concordance1 commissions - raise and deals - agency toughest in order to avoid fines for anti-competitive behaviou2 2.4 ropes. metallic of instead tiled by fiber slings In order to avoid water stagnation, rolled steel plat3 framing end and side lower the lid overlapping the in order to avoid rain infiltration. For weights over 4 material screening other or plywood protected by in order to avoid handling 2. WELDING ELECT5 bag barrier the inside produced al vacuum shall be in order to avoid moisture penetration. Bamer bag

semantic prosody frequency/ 191 & % examplepositive goal, result or outcome 137 - 71.72% in order to achieve a 25%

increasein order to allow maximum exploitation of the box in order to continuously improvein order to win businessin order to secure airline contracts

c) Clusters

6-word: No clusters of frequency >=3.

5-word:

N cluster Freq.1 in order to provide the 42 in order to achieve a 33 in order to ensure that 34 in order to get the 35 in order to keep the 36 in order to make the 37 in order to update the 3

4-word:

N cluster Freq.1 in order to make 82 in order to achieve 73 in order to ensure 64 in order to keep 65 in order to avoid 56 in order to provide 57 but in order to 4

323

8 in order to allow 49 in order to compete 410 in order to determine 411 in order to get 412 in order to maintain 413 in order to obtain 414 order to provide the 4


324

N File Words Hits per 1,000 Plot1 misc.txt 2 373 3 1.262 manuals.txt 20 493 17 0.833 memos.txt 12 401 10 0.814 minutes.txt 34 239 24 0.705 reports.txt 62 360 28 0.456 uktv.txt 19 335 7 0.367 faxes.txt 23 211 7 0.308 presrel.txt 21 517 6 0.289 buslet~1.txt 26 747 7 0.26

10 emails.txt 28 495 7 0.2511 anreps.txt 32 775 8 0.2412 prodbr~2.txt 25 982 6 0.2313 speeches.txt 18 965 4 0.2114 combrocs.txt 23 143 4 0.1715 mags&j~1.txt 78 740 13 0.1716 jobads.txt 22 117 3 0.1417 agreem~1.txt 29 491 4 0.1418 books.txt 53 249 6 0.1119 quotatns.txt 8 892 1 0.1120 ustv.txt 77 579 8 0.1021 interv~1.txt 71 822 6 0.0822 newspa~1.txt 63 889 4 0.0623 radio.txt 52 729 3 0.0624 meetings.txt 128 532 5 0.04

e) Colligation

i) in order to-inf191 instances 100% of sample.

f) Associates

‘In order to’ was key in five files. The only associate of frequency >5 was ‘in order to’ itself.

Comments

1. This cluster has an overwhelmingly positive semantic prosody. Over 70% of the examples are directly positive and the rest are neutral.

N Concordance61 me. by approved and Director d in advance by the relevant In order to effectively monitor current and future claims, the 62 grant after years seven and ntitlement unexercised until five in order to encourage long term commitment to the compan63 additive based petroleum a contain ogens. It does, however, in order to enhance hydrophobicity and resistance to salt w64 initiatives common such just encourage when necessary to in order to enhance the effectiveness of international trading65 and forgoing, the of view the durability of these finishes. In in order to enhance the appearance of these cabinets we w66 poor the robbing is That the expense of poor people. in order to enrich the rich. Shortly afterw67 organization D & R Corporate name must invest in a strong in order to: Ensure long-range vision and perspective for Co68 operations fleet their reviewing currently sed businesses are in order to ensure the best financial and operational structur69 support Companyname strong for looking rsonname, who is in order to ensure that Companyname get Companyname 70 product the of design the in procedures to control and verify in order to ensure that the specified requirements are met. 71 future the in EU the order projects with partner countries of in order to ensure synergy with other EU support program72 overstated). not were accounts the anyname so the sales in In order to ensure the accounts remain correct I propose th73 Eskimo an like sometimes in rdingly. So you need to come in order to er to keep warm. And, OK that that might not s

325

8.2.14 BEC Key key-word database

Here the 100 most significant key key-words are presented. Key key-words are those

words that are key ‘in a large number of texts of a given type’ (Scott 1997:237). Below

we see the word, how many files it was key in, e.g. business was a key word in 111 files

out of 877, and the same statistic as a percentage value of the total number of files. A

fuller list of key key-words can be found on the CD ROM. It can be seen from the list

here, that, as with the previous positive key word list, there is a high concentration of

business-related lexis. See Chapter 9, Section 9.3.7 for more on this.

TABLE XXIV: BEC KEY KEY-WORDS (TOP 100)

N WORD OF 877 AS %1 BUSINESS 111 12.662 COMPANY 81 9.243 OK 80 9.124 SALES 58 6.615 FAX 56 6.396 WE 51 5.827 MARKET 45 5.138 COMPANIES 45 5.139 CUSTOMER 43 4.9010 YEAH 41 4.6811 MANAGEMENT 39 4.4512 CUSTOMERS 36 4.1013 PRODUCT 36 4.1014 RIGHT 36 4.1015 FINANCIAL 33 3.7616 STOCK 33 3.7617 PRODUCTS 33 3.7618 BILLION 33 3.7619 PER 33 3.7620 YOU 33 3.7621 ITS 32 3.6522 OUR 32 3.6523 WILL 31 3.5324 INTERNET 29 3.3125 MARKETS 29 3.3126 PRICE 29 3.3127 SO 28 3.1928 ERM 28 3.1929 GROUP 28 3.19

326

30 OR 27 3.0831 BANK 26 2.9632 YEAR 25 2.8533 MILLION 25 2.8534 SERVICES 25 2.8535 GLOBAL 23 2.6236 PRICES 23 2.6237 TAX 23 2.6238 SYSTEMS 23 2.6239 MR 22 2.5140 BUSINESSES 22 2.5141 MARKETING 22 2.5142 INTERNATIONAL 20 2.2843 CREDIT 20 2.2844 SHARES 20 2.2845 OF 20 2.2846 TRAINING 20 2.2847 BE 20 2.2848 BANKS 20 2.2849 ORDER 20 2.2850 THE 19 2.1751 EXECUTIVE 18 2.0552 EQUIPMENT 18 2.0553 ECONOMY 18 2.0554 SOFTWARE 18 2.0555 SHARE 18 2.0556 GROWTH 17 1.9457 PROFIT 17 1.9458 PAYMENT 17 1.9459 INDUSTRY 17 1.9460 BECAUSE 17 1.9461 SERVICE 17 1.9462 PROJECT 17 1.9463 CORPORATE 17 1.9464 SHALL 17 1.9465 ARE 17 1.9466 MANAGER 17 1.9467 TEAM 17 1.9468 COST 16 1.8269 COSTS 16 1.8270 TRADE 16 1.8271 BUDGET 16 1.8272 MEAN 16 1.8273 CASH 16 1.8274 RATES 16 1.8275 COMPANY'S 16 1.8276 WE'VE 16 1.8277 YOUR 15 1.7178 INVESTMENT 15 1.7179 TECHNOLOGY 15 1.7180 REVIEW 15 1.7181 MAIL 15 1.71

327

82 INFORMATION 15 1.7183 BY 15 1.7184 DO 15 1.7185 JUST 15 1.7186 THAT'S 15 1.7187 TRADING 14 1.6088 PROJECTS 14 1.6089 FIRMS 14 1.6090 MEETING 14 1.6091 CONSUMERS 14 1.6092 DESIGN 14 1.6093 PERCENT 14 1.6094 REPORTING 14 1.6095 AUDIT 14 1.6096 DELIVERY 14 1.6097 PERFORMANCE 14 1.6098 THAT 14 1.6099 AGREEMENT 14 1.60100 DIRECTOR 14 1.60

8.2.15 Analysis of five key words words from the BNC corpus

Five words were chosen from the BNC Sampler corpus and subjected to the same

analysis as the single words in the BEC (as in Chapter 7, Step 5 a-h) in order to provide a

comparison of usage between Business English and general English. All five words

analysed in the BNC can be found in Appendix 9 in Vol. II. An example, manage, is

shown below:

EXAMPLE WORD FROM BNC ANALYSIS: ‘MANAGE'

a) Keyness

The lemma ‘manage’ was the one hundred and forty-fourth most significant key word in the BEC corpus.

N Word bec freq. bec.lst % bnc freq. bnc.lst % Keyness P144 MANAGE 377 0.04 246 0.01 177.9 0.000000

b) Semantic Prosody

No groups identified but see colligation section below.


328

N cluster Freq.1 did you manage 92 how did you 83 going to manage 44 have to manage 45 I could manage 46 those who manage 4


‘Manage’ was used in 48 out of 185 files.

e) Colligation

Manage n = 88

COBUILD Sense 1 (controlling a system, organisation) 17 instances 19.31% of samplePattern: Verb/ Verb-Nounmanage a network of UK resellers

N Concordance51 who those by introduced politics quent operational manage the operation. Managers who do not work52 actually don't I theory in and yet I've been, manage them. That's right, yeah. Plus 53 to someone of need desperate 're doing and are in manage them. I have, however, pointed out that th54 to going they're and Government mp sum from the manage themselves and make a going concern of55 sectors economic or enterprises let ying that it will manage themselves,; he says. But the people tryi

COBUILD Sense 3 (to manage to do something)38 instances 43.18% of samplePattern: Verb to-inf/Verb-Noun

N Concordance59 you did how Er scales. next to the erm manage to get two sides of that so perfectly straig60 quite didn't We design. the made a little fault with manage to construct the er item concerned adequ61 to energy the almost was laces and all the rest., it manage to do it, a hundred percent of the time an62 to have we But difficult. us, it's it Transportation is manage to find out how these people think, how w63 you how know don't really do this, you know, yo I manage to run up a bill like that. And I said, well I 64 we how wondering be you'll s out of thirty nine and manage to lead the council. Well, rightly or wrongl65 always I and something or 'd got the gift of the gab manage to wind people round my finger and alway66 don't I as long so ccustomed to them. I know that manage to count up to one hundred before the sp67 areas peripheral the as reduced, been or are being manage to offer sites that are as competitive as th68 we speaking generally but day, g the stories of the manage to get a full list of your dedications in. Ca69 I'd that instead myself telling t some point—; kept manage to hold it in until I was back in the flat, an70 services the unless year next ll kill the programme manage to iron out serious flaws. The electronic j71 all They temples. important are department stores manage to look much the same. Go into Printemp

COBUILD Sense 4 (to manage to cope with a difficult situation)32 instances 36.36% of samplePatterns: Verb

329

N Concordance11 you did how family, own Now what about your manage, how did you make ends meet with the er12 could I But that. watch what I mean? So I've got to manage. I could certainly manage to have a half d13 even might we mm, Mm, eeting and. manage, I mean, we, we might talk later on about 14 could lapillus N. that observation Connell's (1961) manage I.l s. balanoides a day in summer, whilst 15 probably Association, Sports Water Suffolk Geoff manage, is that better? You'll be on the

Other patterns:

i) modal/auxiliary + manage: (this group expresses likelihood/necessity/ability)27 instances 30.68% of sample

N Concordance8 can I I drink. a 's right darling. manage see me any time you want. No9 can I yes oh hold you want Have a little manage that for short distances. I think perhaps t

10 can I (a) follows: as en by non-users were manage without it. (b) I prefer to ask the s11 can't really we otherwise years, n up with over the manage the concept. And this is where all our pro12 certainly could I manage. could o watch that. But I manage to have a half day. Yeah. 13 could I But that. watch what I mean? So I've got to manage. I could certainly manage to have a half d14 could I think I what? &oslashller. And d'you know manage two!; Does it always rain on M&o15 could I sob. a stifling mmer,; she said aloud then, manage —; of course I could! The cottage is mine16 could I think don't I gging that big box. I manage it. I can see fits being had by party. 17 could lapillus N. that observation Connell's (1961) manage I.l s. balanoides a day in summer, whilst 18 couldn't just they they i, we, no we broaden it i manage on the sea ones. Cor there's lo

This compares to modal usage in the BEC where only 7 examples were found, 8.53% of the sample in the BEC.

Comments

1. In this sample from the BNC, we see a reversal of the frequency of the senses when compared to the BEC. In the BEC, Sense 1 was 54.87% of the sample, in the BNC it was 19.31%. In the BEC Sense 3 was 14.63% of the sample, in the BNC it was 43.18%. Additionally in the BEC there were no examples of Sense 4 found.

2. Many of the examples found in the BNC were negative ones: I can’t manage, he could not manage. Negativity is not referred to in COBUILD.

8.2.16 Collocates of the 50 key words shown by MI statistic.

It was noted in Chapter 7 that the MI statistic is not considered a sole reliable source of

information when determining collocational significance - it tends to over-stress highly

infrequent collocates. Thus, in this research it has not played a large part. However, the

MI statistics for all the 50 key words under analysis were computed. They are presented

on the next pages. This list is also to be found in Appendix 10 in Vol. II.

330

TABLE XXV: COLLOCATES OF THE KEY WORDS AND MI SCORE

Word Collocates & MI Scorecustomer acknowledges 4.66 consciousness 4.59 satisfaction 4.17 hereunder 3.78 assistant 3.46 refund 3.42

base 3.28 preferences 3.27 elt 3.27 confidentiality 3.27manager cfi 5.72 workÕs 5.39 medal 4.55 enc 4.32 oversee 3.81 branch 3.43 incÕs 3.22 booksellers 3.22supplier furnish 6.86 establish 5.19 tier 4.99 intends 4.74 dcs 4.33 terminal 3.86 leading 3.67 shall 3.52

records 3.07distributor notify 4.85 nz 4.79 angus 4.70 terminate 4.33 appointed 3.10shareholder tsr 6.15 return 4.41 value 3.92 total 3.82 release 3.64 rights 3.15 partner 3.10 approval 3.06employee counselling 5.13 ownership 4.79 satisfaction 4.35 agent 4.16 involvement 3.62 owners 3.5

official 3.42 representative 3.16 relations 3.06staff siteon 4.87 forum 4.36 dining 4.02 employing 3.78 trusted 3.61 recruiting 3.46

junior 3.25 bed 3.13partner pegge 7.45 cazenove 6.45 pw 5.33 ernst 5.22 willing 4.03 senior 3.73. venture 3.24

shareholder 3.10boss incÕs 5.88 indians 4.70 americaÕs 3.56management timebased 5.60 mercury 4.55 templeton 4.13 resolute 3.87 krigline 3.87 expatriate 3.87

guru 3.55 ems 3.55 deloitte 3.55 buyout 3.55business roland 3.47 gribben 3.47 clydebank 3.47 knutsford 3.05investment realized 5.52 comcast 5.37 inward 5.32 consisted 5.22 slashed 4.96 grade 4.74 incremental 4.64

banker 4.44 trusts 4.37 boosting 3.96delivery conveyance 6.85 tendered5.85 notwithstanding 5.04 constitute 4.53 calculating 4.26

shorter 4.15 instalments 4.15 consignment 4.04 quoted 3.65 exclusively 3.53payment lump 5.58 validity 4.43 prompt 4.16 hereof 3.92 cleared 3.92 sum 3.33 deposit 3.26development counsellors 5.36 umts 5.19 counsellor 5.03 accelerated 4.36 cycles 4.19 electrolux 3.50

sustainable 3.49 nera 3.45 accelerate 3.45 research 3.10production rationalising 5.75 automated 4.90 defective 4.81 commenced 4.58 indicator 4.42

installation 4.26 virgin 3.66 valued 3.66 inefficient 3.66 environments 3.42communication interpersonal 5.45 hyperion 5.06 excellent 3.91 skills 3.34 feedback 3.31competition karel 6.48 foreshorten 6.39 stiff 6.22 fierce 5.63 commissioner 5.34 union's 4.63 intense 4.55

paths 4.48 stages 3.99 faces 3.48takeover distillers8.43 guinness's 7.85 speculation 5.53 fear 5.53 panel 5.47 battle 4.59 bid

4.50 code 3.98 america's 3.94distribution nfc 4.60 channels4.54 revenue 4.37 midlands 4.27 expanded 3.84 elsewhere

3.07sell eager 4.50 rollers 3.25 offs 3.11manage strategically 5.62 efficiently 5.43 awareness 4.38 relationships 3.26 grow 3.04receive she'd 6.13 charities 5.28 elect 5.23 complimentary 4.81 delegate 4.55 elected 4.28

seminar 3.93 entitled 3.81 compensation 3.48 hercules 3.04confirm morton 6.47 bailey's 5.37 pleased 4.25 definition 3.79 acceptance 3.30provide bowls 5.55 canteen 5.13 bedding 5.13 dsp 3.81 detection 3.63send cv 4.05 paste 3.69 cheque 3.47develop mwg 5.37 careers 5.18 motivate4.59 strategically 4.37 implement 3.95 instruction 3.37

attract 3.32discuss kaarina 5.63 pgw 5.47 nbr 5.13 wish 4.34 doug 4.04 files 3.94 aspect 3.24achieve goals 4.70 desired 4.48 consensus 3.87 goal 3.81 objectives 3.21 budgets 3.06improve continuously 4.74 productivity 4.60 division's 4.57 twg 4.16 efficiency 4.04 liquidity

3.93 definition 3.25 education 3.04high wycombe 5.40 hdpe 5.40 molecular 5.08 seas 5.01 fliers 4.81 douper 4.81 tech 4.71

viscosity 4.40 polyethylene 4.32 density 4.02big rallies 4.85 ifs 4.59 egg 4.59 headline 4.01 caps 4.01 bucks 4.01 victory 3.78 bang

3.59 highlight 3.01 boys 3.01low permanently 5.70 exceptionally 5.38 commodities 5.11 artificially 5.11 voltage 4.70 wage 4.15

pollution 4.11 incomes 3.89 inflation 3.84 flying 3.65global trans 6.25 seamless 5.86 prioritize 5.86 strategist 5.45 jad 5.45 custody 5.45

deflation 4.64 ambitions 4.36 institute 4.32 polish 3.99international aerosystems 4.74 hampton4.54 nova 4.22 linkage 4.22 oriflame 3.96 credits 3.89

division 3.59 undergraduate 3.54 mercedes 3.37 concentration 3.37local roots 5.14 expatriate 5.14 devalued 4.82 authorities 3.93 authority 3.57 residential

3.34 monopolies 3.34 governments 3.21 angus 3.06competitive devaluations 5.85 edges 5.59 disadvantage 5.43 climate 4.78 edge 4.59 advantage 4.44

globally 4.43 anti 4.22 pressures 3.74 dead 3.47corporate governance 6.16 strategists 5.35 unity 4.86 nestle 4.50 identity 4.09 headquarters 4.05

uniform 3.97 counselling 3.86 recovery3.72 landscape 3.50strategic thinker 6.27 choices 4.80 planning4.41 alternatives 4.12 vision 3.75 logic 3.66

priorities 3.53 partnerships 3.53 restricted 3.48 structural 3.35financial ifas 4.59 commentator 4.18 statements 4.15 schroders 3.86 institutions 3.63

entrepreneurship 3.59 controller 3.51 cnn 3.42 consolidated 3.30 turmoil 3.22sale varityperkins 6.11 proceeds 4.63 reed 3.41

merger mania 6.59 equals 5.81 cibc's 5.81 unichem5.59 csx 4.49 mega 4.33 citicorp 4.14talks 4.12 guinness3.93 worldcom 3.87

trade mercosur 5.48 missions4.84 unions 4.65 supranational 4.48 secrets 4.48 exhibitions 4.32offs 3.99 journals 3.95 barriers 3.84 references 3.56

package brokered 6.45 rescue 5.45 relocation 4.86 reporting 3.71 dimensions 3.69 remuneration3.36 rewards 3.20

export promoter 7.87 counsellors 7.04 counsellor 6.72 vouchers 6.45 cfi 6.45 quotas 6.23department's 6.13 advisor 6.13 dept 5.45 import 4.90

service personalized 4.61 faxbroadcast 4.61 briefings 4.61 figtree 4.19 directories 4.19 atmospheric4.19 mg 3.87 premier 3.53 franking 3.19 entrance 3.19

market capitalisation 3.88 newsprint 3.76 capitalization 3.54earnings diluted 6.08 oppenheimer's 5.34 retained 5.21 enhancing 4.34 ratios 4.24 beat 3.69 grew

3.27 underlying 3.24 share 3.23 fully 3.04performance promotes 4.82 expatriate 4.82 asz 4.82 subsidiary's 4.50 stimulating 4.50 sporting

4.50 economy's 4.50 candidate's 4.40 manager's 4.23 criteria 3.88product nonconforming 5.25 conforms 5.25 selector 4.25 sffeco 3.84 badger 3.79 widest 3.67

cycles 3.67 fastrax 3.51 launches3.38 conformance 3.38

8.3 Analysis of the PMC

8.3.1 PMC general statistics

Here the general statistics of the PMC are presented.

TABLE XXVI: GENERAL STATISTICS OF THE PMC

Text File OVERALLBytes 3 483 807Tokens (words) 593 294Types (types of words) 19 738Type/Token Ratio 3.33Standardised Type/Token (as %)

41.83

Average word length 4.49Sentences 25 150Sentence length 15.55Standard sentence length 14.72Paragraphs 14 809Paragraph length 40.04Standard paragraph length 77.271-letter words 28 7712-letter words 106 3713-letter words 117 2044-letter words 104 6685-letter words 65 4936-letter words 48 1497-letter words 43 1818-letter words 29 2259-letter words 22 31510-letter words 13 17311-letter words 7 68212-letter words 3 82613-letter words 2 16314(+)-letter words 718

8.3.2 PMC frequency list unlemmatised

This can be found on the CD ROM attached to the back cover of this thesis.

8.3.3 PMC frequency list lemmatised

This can be found on the CD ROM attached to the back cover of this thesis.

8.3.4 PMC positive key words (BNC reference corpus)

Here, the top 100 positive key words in the PMC are presented. They are key in

comparison to the BNC corpus. The full list can be found on the CD ROM attached to

the back cover of this thesis. This list shows how the Business English of published

materials differs from general English, and it displays a high frequency of business lexis

(e.g. company, market, product), a number of words typical to a business environment

(e.g. fax, order), but also words concerned with politeness in speech and writing (e.g.

please, sincerely, dear, sorry). Thus, this list differs from the positive key words

computed from the BEC. These differences are covered in full in Chapter 9, Section

9.4.1.

TABLE XXVII: PMC POSITIVE KEY WORDS (TOP 100) - BNC REFERENCE

N WORD FREQ. PMC.LST %

FREQ. BNC.LST %

KEYNESSLog L.

1 COMPANY 2 045 0.34 782 0.04 3 054.42 MARKET 1 478 0.25 831 0.04 1 739.63 OUR 2 539 0.43 2 577 0.13 1 687.74 SALE 968 0.16 343 0.02 1 501.75 PRODUCT 1 006 0.17 412 0.02 1 447.16 BUSINESS 1 084 0.18 542 0.03 1 382.87 MANAGER 811 0.14 317 0.02 1 196.38 PLEASE 1 079 0.18 659 0.03 1 193.09 WE 5 837 0.98 10 822 0.55 1 192.710 OK 483 0.08 38 1 158.511 PRICE 949 0.16 586 0.03 1 040.212 YOUR 2 949 0.50 4 670 0.24 912.213 CUSTOMER 528 0.09 147 912.214 BANK 694 0.12 379 0.02 833.515 EMPLOYEE 411 0.07 94 764.616 FAX 288 0.05 32 649.917 YOU 10 587 1.78 26 331 1.34 594.818 MEETING 697 0.12 575 0.03 587.819 DEPARTMENT 456 0.08 232 0.01 574.820 ORDER 747 0.13 681 0.03 564.921 CREDIT 342 0.06 110 555.222 LTD 332 0.06 103 547.8

23 AFRAID 358 0.06 145 517.924 SINCERELY 204 0.03 11 514.725 JOB 755 0.13 752 0.04 513.226 DIRECTOR 464 0.08 289 0.01 504.927 OFFICE 568 0.10 461 0.02 487.028 PRODUCTION 362 0.06 167 485.629 THANK 877 0.15 1 015 0.05 484.930 INVOICE 203 0.03 17 482.131 DISCOUNT 225 0.04 36 466.632 NEW 1 332 0.22 1 995 0.10 465.333 UM 168 0.03 4 454.734 BRAND 270 0.05 82 449.635 PER 619 0.10 585 0.03 448.736 TELEX 167 0.03 6 438.737 DELIVERY 237 0.04 56 435.838 TO 17 365 2.93 47 851 2.44 421.039 PERSONNEL 219 0.04 50 407.640 I'M 1 759 0.30 3 136 0.16 401.341 ADVERTISE 274 0.05 110 398.342 ENCLOSE 186 0.03 27 395.443 SELL 487 0.08 419 0.02 392.744 MANAGEMENT 398 0.07 279 0.01 392.245 PAYMENT 266 0.04 115 370.946 INTEREST 716 0.12 865 0.04 370.447 FLIGHT 225 0.04 72 366.148 AGREE 482 0.08 443 0.02 361.049 YOURS 302 0.05 166 360.950 REF 134 0.02 5 350.951 COST 632 0.11 747 0.04 338.352 SUPPLIER 184 0.03 44 336.953 COMPANY'S 181 0.03 45 326.754 HELLO 303 0.05 192 325.255 CORPORATE 164 0.03 33 318.356 OFFER 481 0.08 491 0.03 316.857 MEET 456 0.08 457 0.02 307.558 TELEPHONE 270 0.05 159 306.859 I'D 634 0.11 807 0.04 301.160 LONDON 470 0.08 505 0.03 289.061 INTERVIEW 197 0.03 78 288.562 EXECUTIVE 200 0.03 86 279.763 INTERNATIONAL 328 0.06 269 0.01 278.264 GOOD 1 456 0.25 2 754 0.14 278.065 MILLION 443 0.07 473 0.02 274.866 CAN 2 545 0.43 5 606 0.29 273.867 CONSIGNMENT 91 0.02 0 265.768 CENT 375 0.06 364 0.02 263.169 DATE 386 0.07 389 0.02 258.470 UK 288 0.05 224 0.01 257.671 EXPORT 173 0.03 67 256.372 PRESENTATION 168 0.03 62 255.273 US 1 186 0.20 2 165 0.11 252.574 ACCOUNT 488 0.08 593 0.03 250.1

75 HOW 1 385 0.23 2 666 0.14 249.976 DEAR 360 0.06 353 0.02 249.577 WORK 1 519 0.26 3 009 0.15 248.778 SALARY 126 0.02 25 245.679 SORRY 447 0.08 537 0.03 233.380 SURE 501 0.08 652 0.03 229.081 CONTRACT 242 0.04 183 222.482 STAFF 437 0.07 535 0.03 221.383 INCREASE 452 0.08 566 0.03 220.684 FAITHFULLY 79 0.01 1 220.585 WILL 2 243 0.38 5 038 0.26 220.386 FOR 6 062 1.02 15 996 0.82 217.587 SHARE 544 0.09 762 0.04 217.488 MACHINE 293 0.05 274 0.01 215.089 MR 1 041 0.18 1 920 0.10 214.890 MANUFACTURE 199 0.03 126 213.791 FINANCE 192 0.03 117 212.592 FIRM 286 0.05 265 0.01 212.293 CLOTHES 72 0.01 0 210.294 YEAR 1 532 0.26 3 184 0.16 210.195 PERFORMANCE 229 0.04 175 208.496 MANUFACTURER 138 0.02 53 205.497 OPTION 195 0.03 128 203.398 CASH 191 0.03 124 200.999 PROBLEM 697 0.12 1 136 0.06 200.9100 GOODBYE 103 0.02 21 199.1

8.3.5 PMC positive key words (BEC reference corpus)

Here, the top 100 positive key words in the PMC are presented. They are key in

comparison to the BEC corpus. The full list can be found on the CD ROM attached to the

back cover of this thesis. This list shows how the Business English of the published

materials differs from the Business English found in the BEC. It displays a high

frequency of words related to personal communication (e.g. personal/possessive

pronouns you, I’m, our, we), words related to politeness (e.g. thank, please) and words

related to forms of communication (e.g. telex, letter, meeting, presentation). These

matters are discussed in Chapter 9, Section 9.4.1.

TABLE XXVIII: PMC POSITIVE KEY WORDS (TOP 100) - BEC REFERENCE

N WORD FREQ. PMC.LST %

FREQ. BEC.LST %

KEYNESS

Log L.1 YOU 10 587 1.78 10 133 0.99 1 800.62 I'M 1 759 0.30 930 0.09 910.33 YOUR 2 949 0.50 2 409 0.24 744.24 I'D 634 0.11 129 0.01 695.85 AFRAID 358 0.06 38 502.16 ME 1 399 0.24 978 0.10 479.47 OUR 2 539 0.43 2 342 0.23 474.78 MY 1 240 0.21 861 0.08 429.99 THANK 877 0.15 502 0.05 409.110 PLEASE 1 079 0.18 715 0.07 404.711 SORRY 447 0.08 166 0.02 331.912 LIKE 1 666 0.28 1 555 0.15 301.113 I'LL 721 0.12 461 0.05 286.214 WE 5 837 0.98 7 492 0.73 284.015 FLIGHT 225 0.04 38 268.616 COULD 1 317 0.22 1 176 0.11 268.017 ABOUT 2 096 0.35 2 222 0.22 252.318 GOOD 1 456 0.25 1 386 0.14 248.719 SEE 1 398 0.24 1 360 0.13 223.920 HOW 1 385 0.23 1 351 0.13 220.021 CAN 2 545 0.43 2 947 0.29 213.922 TELEX 167 0.03 25 209.123 YOURS 302 0.05 134 0.01 190.024 LETTER 356 0.06 185 0.02 187.925 LTD 332 0.06 163 0.02 187.326 JOB 755 0.13 627 0.06 183.127 MEET 456 0.08 294 0.03 178.628 MRS 161 0.03 33 176.029 MORNING 328 0.06 174 0.02 168.830 GOODBYE 103 0.02 6 165.531 MR 1 041 0.18 1 025 0.10 160.532 MANAGER 811 0.14 742 0.07 154.733 LET'S 274 0.05 135 0.01 154.034 PERSONNEL 219 0.04 90 148.535 LUNCH 167 0.03 52 142.336 TELL 527 0.09 419 0.04 140.737 DEPARTMENT 456 0.08 339 0.03 139.438 SINCERELY 204 0.03 84 138.139 HELLO 303 0.05 177 0.02 137.440 OKAY 89 0.02 7 134.741 FINE 315 0.05 193 0.02 133.442 ADVERTISE 274 0.05 154 0.02 130.943 SURE 501 0.08 403 0.04 130.444 NAME 510 0.09 414 0.04 130.145 SIR 191 0.03 81 125.746 US 1 186 0.20 1 300 0.13 125.647 DRINK 180 0.03 72 125.248 EMPLOYEE 411 0.07 307 0.03 124.5

49 AIRPORT 122 0.02 29 123.450 MACHINE 293 0.05 182 0.02 121.551 INTERVIEW 197 0.03 92 117.552 OH 544 0.09 475 0.05 117.153 CHOCOLATE 69 0.01 3 116.154 NICE 204 0.03 100 115.355 HEAR 271 0.05 167 0.02 113.756 TOO 520 0.09 452 0.04 113.257 PRODUCTION 362 0.06 267 0.03 112.358 COURSE 591 0.10 546 0.05 109.859 CONSIGNMENT 91 0.02 15 109.760 AH 134 0.02 45 107.961 POINT 692 0.12 679 0.07 107.862 ARRIVE 208 0.04 112 0.01 105.063 LEAVE 436 0.07 369 0.04 101.264 FIRST 919 0.15 1 011 0.10 95.965 ENCLOSE 186 0.03 99 95.366 IDEA 427 0.07 369 0.04 94.267 VERY 1 362 0.23 1 642 0.16 94.068 QUESTION 454 0.08 404 0.04 93.169 LET 373 0.06 306 0.03 93.070 LOOK 1 045 0.18 1 197 0.12 92.071 ASK 539 0.09 515 0.05 91.072 MISS 146 0.02 66 90.173 HOUR 350 0.06 285 0.03 88.774 PREMISE 44 0 88.275 MMM 44 0 88.276 SPEAK 351 0.06 288 0.03 87.477 TAKE 1 269 0.21 1 543 0.15 83.878 MEETING 697 0.12 739 0.07 83.779 FACTORY 199 0.03 123 0.01 83.180 ENJOY 163 0.03 88 82.081 HERE 719 0.12 773 0.08 82.082 PRESENTATION 168 0.03 93 81.983 WORKER 176 0.03 102 80.784 FIGURE 326 0.05 269 0.03 80.285 EXCUSE 91 0.02 27 80.286 AFTERNOON 146 0.02 74 79.487 MANPOWER 62 0.01 9 78.588 DEAR 360 0.06 316 0.03 76.489 ROAD 231 0.04 165 0.02 76.190 AGREE 482 0.08 472 0.05 75.691 INTEREST 716 0.12 789 0.08 74.292 CAN'T 408 0.07 381 0.04 73.593 MEAL 75 0.01 19 73.194 STAFF 437 0.07 419 0.04 73.095 DISCOUNT 225 0.04 163 0.02 72.296 ADVERTISEMENT 65 0.01 13 71.997 FAITHFULLY 79 0.01 23 70.598 SEAT 91 0.02 33 68.999 SOON 249 0.04 199 0.02 65.7100 CANDIDATE 132 0.02 72 65.6

8.3.6 Grammatical categorisation of PMC positive key words (BNC reference)


PMC categorised by word class as defined by Ljung (1990): noun, verb, adjective,



8.3.7 Semantic categorisation of PMC positive key words (BNC reference corpus)




8.3.8 Grammatical categorisation of PMC positive key words (BEC reference)


PMC categorised by word class as defined by Ljung (1990): noun, verb, adjective,



8.3.9 Semantic categorisation of PMC positive key words (BEC reference corpus)




8.3.10 Analysis of five key words from the PMC

The steps of this analysis were discussed in Chapter 7, Section 7.3 (i). The analysis of all

the five words can be found in Appendix 17 in Vol. II. Here an example word, product,

is presented.

EXAMPLE WORD FROM PMC: ÔPRODUCTÕ

a) Keyness

The lemma ‘product’ was the fifth most significant key word in the PMC corpus when compared to the BNC.

N Word pmc freq. pmc.lst %

bnc freq. bnc.lst % Keyness bec freq.

5 PRODUCT 1,006 0.17 412 0.02 1447.1 1,385

b) Semantic Prosody

Left: Two groups identified.

semantic prosody frequency/ 526 & % exampleage (new only) 62 - 11.78% new productpositive 26 - 4.94% a classic product

an excellent producta perfect product

Right: Two groups identified.

semantic prosody frequency/ 526 & % examplerange/choice of products 24 - 4.56% product lines

product rangebusiness activities 40 - 7.6% product management

product sampling


N cluster Freq.1 a new product 192 the new product 143 of the product 124 the product is 85 this product is 86 a high product 67 product or service 68 product to the 69 that the product 610 the end product 611 to launch a 612 for this product 513 gross domestic product 514 new product range 5

15 of a product 516 of new product 517 of your product 518 that this product 519 the product or 520 the product range 521 the product to 522 the product was 523 a product of 424 a product that 425 a product's profile 426 and a high 427 bought the product 428 commands a higher 429 high product profile 430 launch a new 431 led rather than 432 new product development 433 of this product 434 our new product 435 product augmented product 436 product in # 437 product is the 438 product of the 439 product's profile and 440 profile and a 441 this product in 442 type of product 443 with the product 444 your product is 4


N File Words Hits per 1,000 Plot1 busl&s.txt 11 743 28 2.382 idioms.txt 37 647 82 2.183 presful2.txt 10 262 20 1.954 busmat~1.txt 18 982 33 1.745 devbusco.txt 14 634 23 1.576 ebcful.txt 12 240 18 1.477 buclaful.txt 51 960 75 1.448 fineng.txt 9 080 13 1.439 presf&f.txt 8 827 11 1.25

10 prwkful.txt 7 026 8 1.1411 intbuful.txt 53 794 59 1.1012 keywrds.txt 32 890 33 1.0013 negot.txt 9 498 9 0.9514 m&d~1.txt 7 636 6 0.7915 inatd.txt 7 936 5 0.6316 bbcbus2.txt 40 557 25 0.6217 insigful.txt 31 136 19 0.6118 longpr.txt 10 229 6 0.5919 fullbop.txt 14 636 7 0.4820 busbas~1.txt 15 175 7 0.4621 buopful.txt 20 615 9 0.4422 buschall.txt 13 827 6 0.4323 survival.txt 15 804 6 0.3824 buseng~1.txt 3 941 1 0.2525 corres.txt 46 704 11 0.2426 cotoco3.txt 6 627 1 0.1527 busgam.txt 6 975 1 0.1428 engb&f.txt 19 848 2 0.1029 persful.txt 32 029 2 0.06

* Key to file names in Appendix 20, Vol. II, p. 972.

e) Colligation

COBUILD Sense 1 (something that is produced and sold in large quantities)Patterns: Count noun100% of sample

ADDITIONAL sense not noted in COBUILD: (products denoted collectively)2 instances - 0.38% of samplePatterns: Uncount nounWe need to new product , we need new product because ...See Comment 2 below for more discussion on this.

Other patterns:

i) (verb/noun) + possessive pronoun + product:56 instances - 10.64% of sample

N Concordance1 sold has Moore Alexander-Dounne HOT TIP: her product to the nation through adroit PR. 2 and herself sell to managed a's. Dounne has her product to the nation through adroit PR A3 or his how out point s of people and who can her product will benefit each individual custo4 or his that believe should ne. A salesperson her product has certain advantages over the 5 for ready too all be huge black market would her product. 'I've no intention of giving up. Th

f) Associates

N WORD NO. OF FILES AS %1 PRODUCT 15 100.002 SALES 15 100.003 COMPANY 14 93.334 MARKET 13 86.675 BUSINESS 11 73.336 COMPANIES 11 73.337 MARKETING 11 73.338 PRODUCTION 11 73.339 PRICE 9 60.0010 CUSTOMERS 9 60.0011 OK 9 60.0012 PRODUCTS 9 60.0013 OUR 8 53.3314 MEETING 8 53.3315 WE 8 53.3316 DELIVERY 8 53.3317 MANAGER 7 46.6718 MANAGEMENT 7 46.6719 SALARY 7 46.6720 TO 7 46.6721 PER 7 46.6722 YOUR 7 46.6723 AFRAID 7 46.6724 EMPLOYEES 7 46.6725 HOW 7 46.6726 ADVERTISING 7 46.6727 COMPANY'S 6 40.0028 PRICES 6 40.0029 CORPORATE 6 40.0030 PERSONNEL 6 40.0031 DIRECTOR 6 40.0032 SELL 6 40.0033 SHARE 6 40.0034 ABOUT 6 40.0035 ARE 6 40.0036 QUALITY 6 40.0037 YOU 6 40.0038 I'D 6 40.0039 NEW 6 40.0040 MANAGERS 6 40.00

41 FAX 6 40.0042 I'M 6 40.0043 SECTOR 5 33.3344 GOODS 5 33.3345 AGREE 5 33.3346 PROFIT 5 33.3347 THAN 5 33.3348 SORRY 5 33.3349 INVOICE 5 33.3350 IS 5 33.3351 YEAR 5 33.3352 PAYMENT 5 33.3353 MORE 5 33.3354 PLEASE 5 33.3355 ORDER 5 33.3356 DEPARTMENT 5 33.3357 OFFICE 5 33.3358 MARKETS 5 33.3359 BRAND 5 33.3360 BANK 5 33.3361 PLEASED 5 33.3362 MEET 5 33.33

Comments

1. In the PMC there is more emphasis on the personal aspects or personal relationships of the participants to the products. Possessive pronouns are used 26 times in the BEC (3.5% of the sample). In the PMC they are used 56 times (10.64% of the sample).

2. The use of ‘product’ as a non-count noun is almost totally missing from the PMC with only 2 examples (0.38% of the sample), found from Presenting in English (Powell 1996) We need to new product, we need new product because ... Powell also has one other example found in Business Matters (Powell 1996), image outsells product every time, which leans in this direction, but is not a clear example.

There were 106 instances of this use of ‘product’ in the BEC (14.3% of the sample). ‘Product’ used in this way acts as a replacement for ‘products’ in the plural, and cannot be used in conjunction with an article. In all of these instances ‘product’ is not post-modified as in product group or product development. It therefore represents a different usage than is represented in the PMC. This sense is missing from the COBUILD dictionary.

Examples of ‘product’ used as a non-count noun from the BEC are: We are on the point of having to source product externally. But you’ve got product on there that nobody wants.... preserve and segregate product from time of receipt.we’ve had to go to Asics in Denmark and buy product from them.

3. New product: The phrase new product occurred 32 times in the BEC (4.31 of BEC sample of product). In the PMC, the corresponding figures were 62 instances - 11.78% of the sample. This shows an over-emphasis in the PMC on new products. Moreover, three senses of the word product are found in the BEC, to only one COBUILD sense in the PMC, showing an overall lack of lexical diversity.

8.3.11 PMC 3-word cluster frequency list

This list shows the most frequent 3-word clusters found in the PMC. Here the top 50 are

presented. A fuller list can be found on the CD ROM attached to the back cover of this

thesis. It is evident from this list that the focus on politeness in the PMC, already noted

with the single-word lists, is a key feature of the lexis (e.g. thank you for, would you like,

look forward to). This is covered in Chapter 9, Section 9.4.5.

TABLE XXIX: PMC 3-WORD CLUSTER FREQUENCY LIST

N Word Freq. %1 I'D LIKE TO 342 0.062 A LOT OF 258 0.043 THANK YOU FOR 204 0.034 WOULD YOU LIKE 200 0.035 BE ABLE TO 199 0.036 ONE OF THE 172 0.037 THE END OF 170 0.038 LOOK FORWARD TO 163 0.039 WHAT DO YOU 158 0.0310 WOULD LIKE TO 154 0.0311 HOW DO YOU 148 0.0212 AT THE MOMENT 144 0.0213 DO YOU THINK 143 0.0214 TO MEET YOU 139 0.0215 YOU FOR YOUR 128 0.0216 DO YOU DO 120 0.0217 I THINK WE 117 0.0218 WE HAVE TO 117 0.0219 WE NEED TO 115 0.0220 AS SOON AS 114 0.0221 YOU LIKE TO 114 0.0222 A NUMBER OF 109 0.0223 IN THE UK 108 0.0224 YOU VERY MUCH 104 0.0225 THANK YOU VERY 103 0.0226 GOING TO BE 101 0.0227 YOU TELL ME 100 0.0228 LOOK AT THE 97 0.0229 YOU CAN SEE 95 0.0230 IF YOU COULD 94 0.0231 YOU WANT TO 94 0.0232 I DON'T THINK 93 0.0233 SOME OF THE 92 0.0234 THERE IS A 92 0.0235 DO YOU HAVE 91 0.0236 THINK WE SHOULD 90 0.02

37 ON THE OTHER 88 0.0138 A GOOD IDEA 87 0.0139 PART OF THE 87 0.0140 I WOULD LIKE 86 0.0141 THE NUMBER OF 86 0.0142 HOW ARE YOU 85 0.0143 IN ORDER TO 85 0.0144 AT THE END 81 0.0145 END OF THE 80 0.0146 FIRST OF ALL 80 0.0147 AS WELL AS 78 0.0148 IN TERMS OF 78 0.0149 PER CENT OF 77 0.0150 TO BE A 77 0.01

8.3.12 PMC key 3-word clusters (BEC reference)

This shows the key 3-word clusters of the PMC (BEC reference corpus) using Log

Likelihood: p = 0.000001. Here the top 50 clusters are presented. A fuller list can be

found on the CD ROM (also key 3-word clusters BNC reference) attached to the back

cover of this thesis. The politeness noted in the lexis of the frequency 3-word clusters is

again found here in the key 3-word clusters. This is discussed in Chapter 9, Section 9.4.5.

TABLE XXX: PMC KEY 3-WORD CLUSTERS - BEC REFERENCE

N WORD PMCFREQ.

PMC3WRDLST %

BECFREQ.

BEC3WRDLST %

1 I'D LIKE TO 342 0.06 15 574.92 WOULD YOU LIKE 200 0.03 25 266.83 TO MEET YOU 139 0.02 8 223.84 DO YOU DO 120 0.02 9 183.55 THANK YOU FOR 204 0.03 63 174.86 YOU LIKE TO 114 0.02 10 168.17 PLEASED TO MEET 70 0.01 0 140.38 I'M AFRAID I 73 0.01 2 129.79 YOU TELL ME 100 0.02 14 128.310 LETTER OF # 65 0.01 2 114.111 HOW DO YOU 148 0.02 53 113.312 LOOK FORWARD TO 163 0.03 66 112.113 WHAT DO YOU 158 0.03 63 110.214 YOUR LETTER OF 75 0.01 7 108.915 YOU FOR YOUR 128 0.02 44 101.216 HOW ARE YOU 85 0.01 15 99.617 NICE TO MEET 49 0 98.218 TO SEE YOU 74 0.01 11 92.9

19 THINK WE SHOULD 90 0.02 23 87.320 DO YOU THINK 143 0.02 66 86.321 SEE YOU AGAIN 43 0 86.222 THANK YOU VERY 103 0.02 34 84.023 COULD YOU TELL 72 0.01 13 83.524 YOU VERY MUCH 104 0.02 36 81.825 I HELP YOU 60 0.01 9 75.126 CAN YOU TELL 52 5 74.927 IF YOU COULD 94 0.02 32 74.928 JUST A MOMENT 37 0 74.229 KIND OF YOU 36 0 72.230 I'D LIKE YOU 36 0 72.231 CAN I HELP 59 10 70.332 INFORM YOU THAT 34 0 68.233 VERY KIND OF 34 0 68.234 FIRST OF ALL 80 0.01 25 68.035 FOR YOUR LETTER 48 5 67.736 LIKE TO SPEAK 31 0 62.137 MOVE ON TO 50 8 61.038 TO SEEING YOU 42 4 60.739 FORWARD TO SEEING 44 5 60.540 AFRAID I CAN'T 30 0 60.141 I HAVE YOUR 29 0 58.142 MAY # = 29 0 58.143 LIKE TO GO 29 0 58.144 I AM WRITING 48 8 57.645 WHY DON'T YOU 38 3 57.446 I LOOK FORWARD 72 0.01 25 56.547 WOULD LIKE TO 154 0.03 104 0.0148 VERY PLEASED TO 27 0 54.149 YOU SPELL THAT 27 0 54.150 DO YOU WORK 27 0 54.1

8.3.13 PMC Key key-word database

Here the top 50 key key-words found in the PMC (BEC reference corpus) are presented.

A full list can be found on the CD ROM attached to the back cover of this thesis.

TABLE XXXI: PMC KEY KEY-WORDS (TOP 50) - BEC REFERENCE

N WORD OF 33 AS %1 YOU 21 63.64

2 I'M 20 60.613 I'D 20 60.614 AFRAID 18 54.555 YES 17 51.526 MY 16 48.487 COULD 15 45.458 YOUR 15 45.459 LIKE 15 45.4510 SORRY 14 42.4211 ME 14 42.4212 I'LL 13 39.3913 HOW 13 39.3914 ABOUT 13 39.3915 THANK 12 36.3616 LET'S 11 33.3317 SEE 11 33.3318 PLEASE 11 33.3319 GOOD 11 33.3320 FINE 10 30.3021 WE 10 30.3022 MORNING 10 30.3023 OUR 9 27.2724 FLIGHT 8 24.2425 MANAGER 8 24.2426 HERE 8 24.2427 LOOK 8 24.2428 AGREE 8 24.2429 CAN 8 24.2430 MEET 7 21.2131 MEETING 7 21.2132 STAFF 7 21.2133 NAME 7 21.2134 WHAT 7 21.2135 DO 7 21.2136 COURSE 7 21.2137 DEPARTMENT 7 21.2138 TOO 7 21.2139 SPEAK 7 21.2140 DRINK 7 21.2141 MR 7 21.2142 HELLO 7 21.2143 GOODBYE 7 21.2144 THAT'S 7 21.2145 PLEASED 7 21.2146 VERY 6 18.1847 NICE 6 18.1848 MARKET 6 18.1849 AFTERNOON 6 18.1850 CALL 6 18.18

8.4 The next chapter

As can be seen from this chapter, there is a large volume of results to be dealt with, of

which only small samples have been presented here. These results now need to be

discussed and analysed, and it will be seen that they have both linguistic and pedagogical

implications.

Documents

users.utu.fi · Web viewLog L. 1611 ER 1 198 0.12 9 750 0.50 3 199.9 1610 I 8 534 0.83 31 126 1.59 3 139.1 1609 SHE 337 0.03 5 899 0.30 3 057.0 1608 OH 475 0.05 5 938 0.30 2 620.4