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  • Language status | Ethnologue
    1 National focus on the level of recognition and use given to the language by government Beyond purely official use however the focus includes the widespread use of the language in media and the workplace at either the provincial sub national or national levels EGIDS 0 International is a category reserved for those few languages that are used as the means of communication in many countries for the purposes of diplomacy and international commerce Because the Ethnologue organizes the language entries by country EGIDS 1 National is the strongest vitality level that we report The EGIDS levels are hierarchical in nature With only one exception the scale assumes that each stronger level of vitality entails the characteristics of the levels below it Thus for example a language cannot be characterized as EGIDS 5 Developing if it cannot also be characterized as being at EGIDS 6a Vigorous A language with written materials which is not used for day to day communication by all generations and which is not being passed on to all children cannot be categorized as EGIDS 5 Developing The one exception to this principle is EGIDS 3 Wider Communication where the vehicularity of languages of wider communication is counted as being weightier than the existence of an orthography and the use of the language in education Some languages that are widely used for intergroup communication are not used in formal education and have no written materials Were these languages to lose that vehicularity they would drop directly to EGIDS 6a Vigorous Methodology The EGIDS levels reported in this edition of the Ethnologue were initially arrived at by inspecting our database and analyzing the factors that we categorized as indicators of vitality In many cases we had sufficient data to allow an initial EGIDS evaluation Where the data were not sufficient we set the EGIDS default value at EGIDS 6a The initial estimates were then distributed to a large number of correspondents who were asked to review the data and make corrections based on their knowledge of specific countries regions language families and individual languages This review process resulted in a large number of corrections and revisions Any remaining unreviewed or uncertain estimates were more closely scrutinized by the editors and after soliciting additional commentary from knowledgeable sources decisions made as to how best to evaluate the EGIDS level in each case The EGIDS estimates though based on the best information available to us are preliminary and the review process is ongoing We encourage users of the Ethnologue to provide us with comments and corrections that will lead to a more accurate assessment for inclusion in future editions In a few cases there is real doubt as to whether the language actually exists as a distinct variety Although an ISO 639 3 code has been assigned data on the existence of the language is not convincing In such cases we do not report an EGIDS level but identify the language status as Unattested The existence of an EGIDS estimate for every known language in every country provides a useful new resource for the assessment of language vitality globally regionally and country by country For instance this site includes histograms that use this information to plot summary profiles of the language situation in each of the major geographic areas UN regions and countries of the world The existence of such data opens up the possibility for other kinds of analysis such as the evaluation of the vitality of language families see for example Whalen and Simons 2012 Official recognition If a language has an official function within a country or is specifically recognized in legislation the entry for the language includes a description of the nature of its recognition When that recognition is by statute the specific law is also cited Table 3 lists and defines with examples the fourteen language recognition categories that are used In developing these recognition categories we have adapted the general framework described by Cooper 1989 99 103 Following Stewart s 1968 identification of the official function of languages in a country Cooper further distinguishes between statutory working and symbolic official languages To that we have added a further distinction between those same functions at either the national or the provincial level This descriptive framework identifies the legal foundation if any for the recognition the nature of the official use of the language and the geopolitical scope of that use and recognition The combination of these three parameters legal status nature of use and scope of application results in the first twelve function categories that are listed in table 3 The final two categories represent any other kind of statutory recognition for a language The distinction between statutory and de facto functions is relatively straightforward When a language function is described as statutory it means that there is a legal document such as the constitution of the country language or diversity policy legislation or the like that specifies the functions for which the language will be used Whenever a language is assigned a function that is statutory we provide the name of the relevant statute We are unable at this time to distinguish in all cases between legislation that is in force and legislation which may not be enforced though it is still legally viable As for de facto status in many countries languages are commonly used for governance functions but there is no formal legislative mandate for that use In those cases we identify the function as de facto Table 3 Official recognition categories and definitions Function Definition Example Statutory national language This is the language in which the business of the national government is conducted and this is mandated by law It is also the language of national identity for the citizens of the country Bengali ben in Bangladesh Indonesian ind in Indonesia Spanish spa in Spain Statutory national working language This is a language in which the business of the national government is conducted and this is mandated by law However it

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  • Summary by language size | Ethnologue
    are not counted in the ranking but are listed as indented entries below the macrolanguage Note that the indented listing of individual languages does not include all member languages it includes only those that have at least one million speakers Table 2 Distribution of world languages by number of first language speakers Population range Living languages Number of speakers Count Percent Cumulative Total Percent Cumulative 100 000 000 to 999 999 999 8 0 1 0 1 2 529 403 578 40 20547 40 20547 10 000 000 to 99 999 999 82 1 2 1 3 2 480 078 977 39 42144 79 62691 1 000 000 to 9 999 999 304 4 3 5 5 915 659 448 14 55462 94 18154 100 000 to 999 999 943 13 3 18 8 296 136 843 4 70717 98 88870 10 000 to 99 999 1 822 25 7 44 5 61 802 734 0 98237 99 87107 1 000 to 9 999 1 982 27 9 72 4 7 633 408 0 12133 99 99241 100 to 999 1 065 15 0 87 4 464 299 0 00738 99 99979 10 to 99 338 4 8 92 1 12 777 0 00020 99 99999 1 to 9 140 2 0 94 1 560 0 00001 100 00000 0 206 2 9 97 0 0 0 00000 100 00000 Unknown 212 3 0 100 0 Totals 7 102 100 0 6 291 192 624 100 00000 Table 3 Languages with at least 50 million first language speakers Rank Language Primary Country Total Countries Speakers millions 1 Chinese zho China 33 1 197 Chinese Gan gan China 1 20 6 Chinese Hakka hak China 13 30 1 Chinese Huizhou czh China 1 4 60 Chinese Jinyu cjy China 1 45 0 Chinese Mandarin cmn China 12 848 Chinese Min Bei mnp China 2 10 3 Chinese Min Dong cdo China 6 9 12 Chinese Min Nan nan China 10 46 6 Chinese Min Zhong czo China 1 3 10 Chinese Pu Xian cpx China 3 2 56 Chinese Wu wuu China 1 77 2 Chinese Xiang hsn China 1 36 0 Chinese Yue yue China 10 62 2 2 Spanish spa Spain 31 399 3 English eng United Kingdom 101 335 4 Hindi hin India 4 260 5 Arabic ara Saudi Arabia 60 242 Arabic Algerian Spoken arq Algeria 1 26 7 Arabic Chadian Spoken shu Chad 4 1 14 Arabic Eastern Egyptian Bedawi Spoken avl Egypt 4 1 69 Arabic Egyptian Spoken arz Egypt 1 55 0 Arabic Gulf Spoken afb Kuwait 9 5 34 Arabic Hijazi Spoken acw Saudi Arabia 2 6 02 Arabic Libyan Spoken ayl Libya 3 4 32 Arabic Mesopotamian Spoken acm Iraq 4 15 1 Arabic Moroccan Spoken ary Morocco 2 21 0 Arabic Najdi Spoken ars Saudi Arabia 4 9 87 Arabic North Levantine Spoken apc Syria 2 14 8 Arabic North Mesopotamian Spoken ayp Iraq 3 6 30 Arabic Omani Spoken acx

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  • Summary by language status | Ethnologue
    are as in Table 2 In addition the Mean column gives the average population of all the languages with the given EGIDS level and the Median column gives the median population for the languages at that level that is half of the languages at that level have a higher population and half have a lower population If there are any languages with an unknown population these are ignored in the calculation of the mean and the median Table 4 Distribution of world languages by vitality status EGIDS Living languages Number of speakers Count Percent Cumulative Total Percent Cumulative Mean Median 0 6 0 1 0 1 1 824 315 868 28 9979 28 9979 304 052 645 335 491 748 1 95 1 3 1 4 1 939 820 827 30 8339 59 8318 20 419 167 7 005 905 2 68 1 0 2 4 620 349 192 9 8606 69 6925 9 122 782 1 236 470 3 172 2 4 4 8 559 519 360 8 8937 78 5862 3 253 020 712 300 4 237 3 3 8 2 251 847 819 4 0032 82 5893 1 062 649 117 500 5 1 598 22 5 30 7 625 895 108 9 9488 92 5381 391 674 25 500 6a 2 479 34 9 65 6 402 097 895 6 3914 98 9295 162 202 10 000 6b 1 075 15 1 80 7 53 266 254 0 8467 99 7762 49 550 3 000 7 456 6 4 87 1 13 314 023 0 2116 99 9879 29 197 1 000 8a 280 3 9 91 0 692 377 0 0110 99 9988 2 473 250 8b 431 6 1 97 1 73 901 0 0012 100 0000 171 15 9 205 2 9 100

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  • Summary by language family | Ethnologue
    Germany Ghana Greece Guatemala Guinea Honduras Hungary Iceland India Indonesia Iran Ireland Israel Italy Jamaica Japan Jordan Kenya Laos Latvia Libya Lithuania Madagascar Malaysia Mali Malta Mauritius Mexico Moldova Mongolia Morocco Mozambique Namibia Nepal Netherlands New Zealand Nicaragua Nigeria Norway Pakistan Panama Paraguay Peru Philippines Poland Portugal Puerto Rico Romania Russian Federation Saudi Arabia Serbia Sierra Leone Singapore Slovakia South Africa South Korea Spain Sri Lanka Sweden Switzerland Tanzania Thailand Trinidad and Tobago Tunisia Turkey Uganda Ukraine United Kingdom United States Uruguay Venezuela Viet Nam Zambia Zimbabwe Dravidian 84 1 18 229 346 860 3 65 2 730 320 26 000 India Nepal Pakistan East Bird s Head Sentani 8 0 11 71 730 8 966 5 875 Indonesia East Geelvink Bay 12 0 17 8 005 667 300 Indonesia East New Britain 6 0 08 13 800 2 300 1 950 Papua New Guinea Eastern Trans Fly 4 0 06 6 760 1 690 1 525 Australia Papua New Guinea Eskimo Aleut 10 0 14 108 705 10 870 1 200 Canada Greenland Russian Federation United States Eyak Athabaskan 40 0 56 207 001 5 175 125 Canada United States Fas 2 0 03 2 840 1 420 1 420 Papua New Guinea Guajiboan 5 0 07 38 700 7 740 1 000 Colombia Guaykuruan 4 0 06 49 350 12 338 3 500 Argentina Brazil Haida 2 0 03 24 12 12 Canada Harákmbut 2 0 03 810 405 405 Peru Hmong Mien 38 0 54 9 334 840 0 15 245 654 65 500 China Laos Viet Nam Huavean 4 0 06 14 670 3 668 1 585 Mexico Iroquoian 9 0 13 14 543 1 616 100 Canada United States Jabutian 2 0 03 3 2 1 Brazil Japonic 12 0 17 129 067 790 2 05 10 755 649 5 000 Japan Jean 13 0 18 44 335 3 410 1 535 Brazil Jicaquean 1 0 01 350 350 350 Honduras Jivaroan 4 0 06 89 630 22 408 22 165 Ecuador Peru Karajá 1 0 01 2 670 2 670 2 670 Brazil Kartvelian 5 0 07 4 853 810 0 08 970 762 79 800 Georgia Israel Turkey Katukinan 2 0 03 10 5 5 Brazil Kaure 3 0 04 900 300 250 Indonesia Kaweskaran 1 0 01 12 12 12 Chile Keresan 2 0 03 10 670 5 335 5 335 United States Khoe Kwadi 12 0 17 337 337 28 111 4 250 Botswana Namibia South Africa Kiowa Tanoan 5 0 07 6 360 1 272 1 500 United States Koreanic 2 0 03 77 160 030 1 23 38 580 015 38 580 015 South Korea Kwomtari 3 0 04 1 510 503 600 Papua New Guinea Kx a 4 0 06 103 760 25 940 21 130 Botswana Namibia Lakes Plain 19 0 27 8 455 445 300 Indonesia Language isolate 75 1 06 827 049 0 01 11 027 42 Bolivia Brazil Canada Chile Colombia Ecuador India Indonesia

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  • Summary by country | Ethnologue
    0 20 7 7 1 356 840 123 349 64 000 0 586 79 Mayotte 4 0 06 3 1 185 800 61 933 54 000 0 622 75 Mexico 289 4 07 283 6 109 118 551 384 220 4 720 0 109 98 Micronesia 19 0 27 18 1 116 260 6 459 2 500 0 768 95 Moldova 15 0 21 10 5 3 413 060 379 229 129 000 0 410 60 Monaco 4 0 06 4 0 31 700 7 925 5 600 0 652 100 Mongolia 14 0 20 12 2 2 613 100 326 638 35 000 0 187 57 Montenegro 7 0 10 4 3 588 140 84 020 36 700 0 244 100 Montserrat 2 0 03 2 0 7 670 3 835 7 570 0 026 100 Morocco 14 0 20 14 0 26 713 920 2 428 538 80 000 0 474 79 Mozambique 49 0 69 43 6 20 620 300 429 590 200 000 0 936 98 Myanmar 117 1 65 117 0 46 528 905 404 599 15 000 0 519 98 Namibia 36 0 51 28 8 2 152 090 61 488 18 400 0 816 97 Nauru 9 0 13 3 6 10 010 1 668 6 000 0 596 67 Nepal 125 1 76 120 5 26 593 200 223 472 8 770 0 755 95 Netherlands 41 0 58 15 26 18 847 620 753 905 220 000 0 302 61 New Caledonia 40 0 56 38 2 143 800 3 994 990 0 753 90 New Zealand 25 0 35 4 21 4 508 030 196 001 148 000 0 280 92 Nicaragua 11 0 15 11 0 5 505 374 550 537 3 000 0 069 91 Niger 21 0 30 21 0 10 010 900 476 710 30 000 0 640 100 Nigeria 526 7 41 520 6 104 853 605 217 991 13 000 0 892 91 Niue 3 0 04 2 1 2 108 1 054 2 030 0 071 67 Norfolk Island 2 0 03 2 0 2 110 1 055 1 680 0 325 100 North Korea 1 0 01 1 0 23 300 000 23 300 000 23 300 000 0 000 100 Northern Mariana Islands 6 0 08 4 2 26 680 4 447 6 820 0 635 100 Norway 16 0 23 9 7 4 805 660 400 472 1 500 0 067 75 Oman 19 0 27 16 3 1 578 400 98 650 25 000 0 702 84 Pakistan 77 1 08 72 5 158 471 460 2 296 688 80 000 0 802 90 Palau 5 0 07 5 0 15 682 3 920 500 0 108 80 Palestine 8 0 11 6 2 1 812 000 302 000 2 000 0 208 75 Panama 19 0 27 14 5 3 102 843 238 680 18 000 0 314 68 Papua New Guinea 839 11 81 839 0 4 122 278 4 943 1 210 0 988 99 Paraguay 29 0 41 23 6 5 971 308 213 261 2 530 0 378 97 Peru 94 1 32 93 1 29 669 086 322 490 5 500 0 341 98 Philippines 193 2 72 182 11 72 208 122 392 435 21 300 0 843 95 Pitcairn 2 0 03 2 0 36 36 36 50 Poland 22 0 31 17 5 37 852 910 2 365 807 38 000 0 065 73 Portugal 11 0 15 10 1 10 309 140 937 195 15 000 0 059 100 Puerto Rico 13 0 18 4 9 3 643 650 455 456 100 000 0 055 62 Qatar 13 0 18 3 10 1 583 200 131 933 471 000 0 825 92 Romania 25 0 35 23 2 21 863 000 1 150 684 22 000 0 167 76 Russian Federation 140 1 97 105 35 158 381 420 1 164 569 4 800 0 251 97 Rwanda 5 0 07 3 2 6 503 000 2 167 667 6 490 000 0 004 60 Réunion 8 0 11 3 5 1 191 000 170 143 619 000 0 513 88 Saint Barthélemy 3 0 04 3 0 7 850 2 617 1 000 0 244 100 Saint Kitts and Nevis 3 0 04 3 0 39 200 19 600 39 000 0 010 67 Saint Lucia 3 0 04 2 1 159 600 79 800 158 000 0 020 67 Saint Martin 3 0 04 3 0 22 000 7 333 5 000 0 525 100 Saint Pierre and Miquelon 3 0 04 2 1 6 790 2 263 6 400 0 110 100 Saint Vincent and the Grenadines 4 0 06 3 1 138 700 34 675 400 0 010 100 Samoa 2 0 03 2 0 199 200 99 600 199 000 0 002 100 San Marino 2 0 03 2 0 25 000 12 500 25 000 0 000 100 Saudi Arabia 20 0 28 5 15 16 440 720 913 373 6 000 000 0 626 90 Senegal 48 0 68 38 10 10 795 620 239 903 18 400 0 784 94 Serbia 20 0 28 15 5 9 644 660 507 614 114 000 0 498 95 Seychelles 3 0 04 3 0 79 700 26 567 4 000 0 164 100 Sierra Leone 27 0 38 25 2 5 379 515 215 181 108 000 0 844 93 Singapore 31 0 44 24 7 3 502 170 129 710 10 000 0 756 87 Sint Maarten 5 0 07 4 1 32 400 6 480 7 000 0 750 100 Slovakia 13 0 18 10 3 5 466 080 455 507 15 000 0 235 92 Slovenia 10 0 14 8 2 2 091 720 232 413 4 020 0 161 90 Solomon Islands 71 1 00 71 0 379 923 5 351 2 940 0 968 100 Somalia 14 0 20 13 1 8 710 659 725 888 23 000 0 404 86 South Africa 44 0 62 28 16 52 302 399 1 376 379 235 000 0 877 86 South Korea 4 0 06 3 1 48 586 000 16 195 333 48 400 000 0 008 75 South Sudan 68 0 96 68 0 4 444 650 79 369 27 000 0 929 82 Spain 22 0 31 15 7 45 419 410 2 523 301 45 000 0 276 82 Sri Lanka 7 0 10 7 0 19 326 030 3 865 206 46 000 0 319 71 Sudan 76 1 07 76 0 18 861 600 281 516 10 000 0 363 88 Suriname 22 0 31 19 3 629 485 34 971 1 400 0 788 82 Swaziland 7 0 10 5 2 1 105 900 157 986 19 000 0 209 100 Sweden 24 0 34 14 10 9 621 890 418 343 4 000 0 155 96 Switzerland 23 0 32 12 11 8 473 230 470 735 40 000 0 658 78 Syria 22 0 31 16 6 13 170 000 731 667 70 000 0 527 82 São Tomé e Príncipe 6 0 08 4 2 91 480 18 296 5 000 0 390 83 Tajikistan 32 0 45 13 19 7 554 240 302 170 40 000 0 272 78 Tanzania 126 1 77 125 1 43 282 690 360 689 86 000 0 857 95 Thailand 86 1 21 74 12 51 695 583 738 508 12 600 0 740 81 Togo 46 0 65 43 3 4 889 380 113 707 35 500 0 905 93 Tokelau 2 0 03 2 0 1 450 725 1 410 0 054 100 Tonga 5 0 07 3 2 97 037 24 259 96 300 0 015 80 Trinidad and Tobago 9 0 13 8 1 2 628 100 328 512 15 600 0 597 89 Tunisia 10 0 14 6 4 10 897 700 1 210 856 21 200 0 018 90 Turkey 47 0 66 35 12 87 613 270 2 305 612 25 000 0 394 81 Turkmenistan 27 0 38 4 23 4 417 220 169 893 317 000 0 385 96 Turks and Caicos Islands 3 0 04 2 1 11 620 5 810 10 700 0 146 67 Tuvalu 3 0 04 3 0 10 870 5 435 10 000 0 147 67 U S Virgin Islands 4 0 06 3 1 150 500 50 167 98 000 0 455 75 Uganda 43 0 61 41 2 23 171 270 551 697 300 000 0 925 98 Ukraine 42 0 59 24 18 43 668 216 1 180 222 144 000 0 426 88 United Arab Emirates 34 0 48 7 27 5 648 810 235 367 468 000 0 707 71 United Kingdom 56 0 79 13 43 60 251 900 1 309 824 77 000 0 148 82 United States 422 5 94 216 206 278 895 278 772 563 25 0 334 86 Uruguay 12 0 17 2 10 3 314 050 473 436 3 170 000 0 084 58 Uzbekistan 39 0 55 9 30 29 045 893 880 179 808 000 0 440 85 Vanuatu 116 1 63 110 6 191 691 1 682 700 0 973 98 Vatican State 2 0 03 2 0 1 000 1 000 1 000 50 Venezuela 50 0 70 44 6 26 879 865 584 345 760 0 043 92 Viet Nam 111 1 56 108 3 76 935 370 769 354 13 800 0 267 90 Wallis and Futuna 3 0 04 3 0 13 340 4 447 3 600 0 407 100 Yemen 14 0 20 10 4 15 700 000 1 570 000 57 000 0 578 71 Zambia 55 0 77 46 9 11 433 570 248 556 36 200 0 830 84 Zimbabwe 23 0 32 21 2 15 992 470 888 471 145 000 0 535 78 Table 8 Linguistic diversity of countries in the world highest to lowest Country Diversity Living languages Number of speakers Index Cover age Total Per cent Indige nous Immi grant Count Mean Median Papua New Guinea 0 988 99 839 11 81 839 0 4 122 278 4 943 1 210 Cameroon 0 974 97 281 3 96 280 1 10 171 376 37 395 9 500 Vanuatu 0 973 98 116 1 63 110 6 191 691 1 682 700 Solomon Islands 0 968 100 71 1 00 71 0 379 923 5 351 2 940 Central African Republic 0 959 94 82 1 15 71 11 3 488 143 45 301 17 700 Democratic Republic of the Congo 0 947 94 212 2 99 210 2 39 872 030 200 362 26 000 Chad 0 945 92 131 1 84 131 0 6 655 659 55 464 14 000 Mozambique 0 936 98 49 0 69 43 6 20 620 300 429 590 200 000 Benin 0 929 98 56 0 79 55 1 7 234 700 131 540 63 000 South Sudan 0 929 82 68 0 96 68 0 4 444 650 79 369 27 000 Kenya 0 927 96 72 1 01 67 5 37 135 208 538 191 176 000 Uganda 0 925 98 43 0 61 41 2 23 171 270 551 697 300 000 Côte d Ivoire 0 919 84 98 1 38 81 17 11 421 290 139 284 28 300 India 0 914 95 454 6 39 447 7 1 078 151 321 2 501 511 34 300 Togo 0 905 93 46 0 65 43 3 4 889 380 113 707 35 500 Liberia 0 899 94 32 0 45 31 1 3 281 680 109 389 61 600 Nigeria 0 892 91 526 7 41 520 6 104 853 605 217 991 13 000 South Africa 0 877 86 44 0 62 28 16 52 302 399 1 376 379 235 000 Guinea Bissau 0 867 81 27 0 38 22 5 1 698 740 77 215 29 900 Mali 0 864 94 71 1 00 66 5 12 376 590 184 725 25 000 Tanzania 0 857 95 126 1 77 125 1 43 282 690 360 689 86 000 Ethiopia 0 852 97 89 1 25 86 3 65 683 980 763 767 55 700 Bhutan 0 851 85 33 0 46 23 10 712 100 25 432 5 000 Gabon 0 846 98 42 0 59 42 0 1 074 360 26 204 4 000 Sierra Leone 0 844 93 27 0 38 25 2 5 379 515 215 181 108 000 Philippines 0 843 95 193 2 72 182 11 72 208 122 392 435 21 300 Ghana 0 835 91 85 1 20 81 4 25 132 506 326 396 30 000 Zambia 0 830 84 55 0 77 46 9 11 433 570 248 556 36 200 Qatar 0 825 92 13 0 18 3 10 1 583 200 131 933 471 000 East Timor 0 817 100 19 0 27 19 0 1 033 506 54 395 18 400 Indonesia 0 816 99 707 9 95 706 1 221 398 286 315 382 3 500 Namibia 0 816 97 36 0 51 28 8 2 152 090 61 488 18 400 Congo 0 810 94 65 0 92 62 3 2 759 310 45 235 14 400 Pakistan 0 802 90 77 1 08 72 5 158 471 460 2 296 688 80 000 Afghanistan 0 790 98 41 0 58 40 1 22 964 800 574 120 8 000 Suriname 0 788 82 22 0 31 19 3 629 485 34 971 1 400 Senegal 0 784 94 48 0 68 38 10 10 795 620 239 903 18 400 Madagascar 0 781 90 20 0 28 14 6 17 747 000 985 944 1 000 000 Angola 0 778 97 37 0 52 37 0 16 070 260 446 396 50 000 Gambia 0 772 79 24 0 34 11 13 1 351 890 71 152 67 000 Micronesia 0 768 95 19 0 27 18 1 116 260 6 459 2 500 Burkina Faso 0 762 94 70 0 99 70 0 10 755 830 162 967 21 000 Malaysia 0 761 64 146 2 06 138 8 24 355 505 261 887 3 500 Singapore 0 756 87 31 0 44 24 7 3 502 170 129 710 10 000 Nepal 0 755 95 125 1 76 120 5 26 593 200 223 472 8 770 Guinea 0 753 82 39 0 55 37 2 8 227 600 257 112 24 000 New Caledonia 0 753 90 40 0 56 38 2 143 800 3 994 990 Sint Maarten 0 750 100 5 0 07 4 1 32 400 6 480 7 000 Thailand 0 740 81 86 1 21 74 12 51 695 583 738 508 12 600 Iraq 0 732 85 27 0 38 23 4 26 117 820 1 135 557 60 000 Iran 0 710 78 80 1 13 76 4 89 585 020 1 444 920 60 000 United Arab Emirates 0 707 71 34 0 48 7 27 5 648 810 235 367 468 000 Oman 0 702 84 19 0 27 16 3 1 578 400 98 650 25 000 Belgium 0 697 73 30 0 42 10 20 12 754 700 579 759 600 000 Laos 0 691 93 91 1 28 85 6 5 690 594 66 948 5 280 Belize 0 688 100 13 0 18 8 5 355 190 27 322 16 100 Bolivia 0 671 93 45 0 63 43 2 9 436 655 224 682 500 Malawi 0 668 74 23 0 32 16 7 13 404 500 788 500 200 000 Israel 0 667 86 51 0 72 35 16 8 702 175 197 777 45 000 Andorra 0 664 100 4 0 06 4 0 73 500 18 375 27 600 Bahrain 0 663 75 12 0 17 4 8 557 600 61 956 300 000 Switzerland 0 658 78 23 0 32 12 11 8 473 230 470 735 40 000 Guam 0 655 56 9 0 13 2 7 151 000 30 200 62 500 Monaco 0 652 100 4 0 06 4 0 31 700 7 925 5 600 Niger 0 640 100 21 0 30 21 0 10 010 900 476 710 30 000 Northern Mariana Islands 0 635 100 6 0 08 4 2 26 680 4 447 6 820 Latvia 0 629 100 14 0 20 7 7 2 826 701 201 907 8 000 Eritrea 0 628 65 20 0 28 15 5 4 542 800 349 446 100 000 Saudi Arabia 0 626 90 20 0 28 5 15 16 440 720 913 373 6 000 000 Bosnia and Herzegovina 0 624 75 8 0 11 4 4 2 358 000 393 000 850 000 Mayotte 0 622 75 4 0 06 3 1 185 800 61 933 54 000 Fiji 0 608 62 21 0 30 10 11 810 100 62 315 9 000 Kuwait 0 605 71 7 0 10 3 4 1 749 400 349 880 1 000 000 Canada 0 603 89 174 2 45 89 85 32 949 601 212 578 350 Trinidad and Tobago 0 597 89 9 0 13 8 1 2 628 100 328 512 15 600 Nauru 0 596 67 9 0 13 3 6 10 010 1 668 6 000 Brunei 0 590 82 17 0 24 15 2 345 195 24 657 10 000 Guatemala 0 590 96 26 0 37 26 0 12 039 012 481 560 41 600 Luxembourg 0 589 100 6 0 08 3 3 447 600 74 600 82 000 Mauritius 0 586 79 14 0 20 7 7 1 356 840 123 349 64 000 Georgia 0

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  • History of the Ethnologue | Ethnologue
    world first created in 1971 by then consulting editor Joseph Grimes from the typesetting tapes for the seventh edition 1969 The work was done at the University of Oklahoma under a grant from the National Science Foundation In 1974 the database was moved to a computer at Cornell University where Dr Grimes was professor of linguistics and it was then moved to a personal computer in 1979 Since 2000 it has been maintained at the headquarters of SIL International in Dallas Texas The structure of the database continues to develop to meet the ongoing research needs of the Ethnologue user community The fact that language entries are partially constructed by computer accounts for a certain stiffness or redundancy in the phrasing The seventeenth edition marked a major milestone in the history of the Ethnologue Previously the primary product had been a printed book Beginning in 1997 with the thirteenth edition the complete contents of the book were also shared on the web However with the seventeenth edition Ethnologue shifted to a web centric paradigm in which the website is the primary means by which the Ethnologue database contents are made known The web edition stands at the center of a whole family of more focused derivative digital and print products that are updated annually The seventeenth edition was initially released to the web in 2013 with a revision of that same edition appearing both on the web and in other formats including print in 2014 Another significant milestone accompanying the seventeenth edition release was the development of the Ethnologue Global Dataset which makes a subset of the Ethnologue database available in tabular form The eighteenth edition updates and expands the data coverage One feature of the database since its inception has been a system of three letter language identifiers The codes were first published with the following explanation in a monograph reporting the results of the grant to create the database Each language is given a three letter code on the order of international airport codes This aids in equating languages across national boundaries where the same language may be called by different names and in distinguishing different languages called by the same name Grimes 1974 i While the codes were used behind the scenes in the database that generated the eighth and ninth editions it was not until the tenth edition 1984 that they appeared in the publication itself In 1998 the International Organization for Standardization ISO adopted ISO 639 2 a standard for three letter language identifiers It is based on a convergence of ISO 639 1 an earlier standard for two letter language identifiers originally adopted in 1967 and of ANSI Z39 53 also known as the MARC language codes a set of three letter identifiers developed within the library community and adopted as an American National Standard in 1987 The ISO 639 2 standard was insufficient for many purposes since it has identifiers for fewer than 400 individual languages Thus in 2002 ISO TC37 SC2 formally

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  • The Problem of Language Identification | Ethnologue
    go over time Varieties which share similar features diverge from one another to different degrees Divergent varieties are often referred to as dialects In some cases they may be distinct enough that some would consider them to be separate languages In other cases the varieties may be sufficiently similar to be considered merely characteristic of a particular geographic region social grouping or historical era Sometimes speakers may be very aware of dialect variation and be able to label a particular dialect with a name In other cases the variation may go largely unnoticed or overlooked For many the term dialect is a pejorative term that identifies a variety as being in some way deficient or inadequate Not all scholars share the same set of criteria for distinguishing what level of divergence distinguishes a language from a dialect and therefore the terms are not always consistently applied Since the fifteenth edition 2005 Ethnologue has followed the ISO 639 3 inventory of identified languages http www sil org iso639 3 as the basis for our listing of languages ISO 639 3 criteria for language identification The ISO 639 3 standard applies the following basic criteria for defining a language in relation to varieties which may be considered dialects Two related varieties are normally considered varieties of the same language if speakers of each variety have inherent understanding of the other variety at a functional level that is can understand based on knowledge of their own variety without needing to learn the other variety Where spoken intelligibility between varieties is marginal the existence of a common literature or of a common ethnolinguistic identity with a central variety that both understand can be a strong indicator that they should nevertheless be considered varieties of the same language Where there is enough intelligibility between varieties to enable communication the existence of well established distinct ethnolinguistic identities can be a strong indicator that they should nevertheless be considered to be different languages These criteria make it clear that the identification of a language is not based on linguistic criteria alone The language entries in Ethnologue include a listing of dialect names In most cases those listings are not based on rigorous dialectology Rather these lists include all names reported to us which may at one time or another have been used in reference to a local variety of a language Names listed may be alternate names for the same linguistic variety Macrolanguages In addition to defining three letter codes for individual languages the ISO 639 3 standard also defines codes for macrolanguages The latter are defined in the standard as multiple closely related individual languages that are deemed in some usage contexts to be a single language Macrolanguages were introduced into the standard in order to handle cases in which varieties would be considered distinct languages by the criterion of non intellgibility as described above but had already been given a code as a single language by the previously existing ISO 639 2 standard For instance

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  • Plan of the Site | Ethnologue
    language names or any other text that may appear on pages in this site Clicking on the logo in the upper left always returns to the home page The following may be accessed from the page footer Browse by provides five indexes which allow you to browse content alphabetically by country language names language codes language families map titles and products Abbreviations is an alphabetical list of abbreviations and acronyms used in the language descriptions it may be consulted to find their meaning Bibliography is an alphabetical listing of all the published sources that are cited on this site Credits identifies all the staff who have been involved in the production of this edition Downloads gives access to the tables of language codes that are made available for free download Ethnoblog is a place where the Ethnologue Editor and others talk about language in general news items regarding language and languages and developments products and projects being worked on by the Ethnologue staff and others FAQ provides answers to Frequently Asked Questions Language of the Day highlights a different language of the world every day it may be subscribed to via RSS feed Archives of the 13th 14th 15th 16th and 17th editions are still accessible online How references are cited Because the Ethnologue is produced by extracting data from a database there is a great deal of uniformity and some stiffness and repetition in the wording and phrases used Frequently the data is maintained using a set of predetermined categories and labels These are explained in Country information and Language information Because of this the Ethnologue rarely quotes any source verbatim Sources are acknowledged wherever specific statements or facts can be directly attributed to them Three kinds of source citations are used Published works are identified using standard in text citations enclosed in parentheses These consist of the author s or editor s surname followed by the year of publication Up to three authors are listed in the citation Published works authored or edited by more than three persons are cited using the first author s surname followed by et al and the year of publication Citations do not distinguish between multiple works by the same person published in the same year Neither are persons with the same surname distinguished in the citations Generally the corresponding references identified by such ambiguous citations can be identified clearly based on the language entry in which the citation is made and the title of the work in the Bibliography where full bibliographic details of all cited published works are included Unpublished sources are also acknowledged when specific statements or facts are attributed to them Unpublished works may include personal communications manuscripts unpublished reports many websites and other materials submitted to us They are identified using in text citations enclosed in parentheses in which the year of the communication is given first followed by the source s first initial and surname Unpublished sources with multiple authors are handled in the same way as

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