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Racial Classifications in Latin America
Quote:Racial Classifications in Latin America

In the history of Latin America over the last 500 years or so, the relationships among three races have been a key factor. In the beginning, there were the various indigenous groups.  Then came the European colonizers, who later brought black slaves from Africa. The relationships among these racial groups have at times been tumultuous --- war, slaughter, subjugation, slavery, exploitation, miscegenation, ...
The administration of the vast colonies was placed in the hands of nationals of the European empires. These administrators were rewarded estates for their efforts, and naturally inheritance rights became a significant issue.  As a male may have multiple children with multiple women, the rights of these apparent heirs have to be defined, particularly when some of the mothers were not pure Europeans.  Under Spanish rule, the following detailed caste system was instituted in Mexico at one time.

1. Mestizo: Spanish father and Indian mother
2. Castizo: Spanish father and Mestizo mother
3. Espomolo: Spanish mother and Castizo father
4. Mulatto: Spanish and black African
5. Moor: Spanish and Mulatto
6. Albino: Spanish father and Moor mother
7. Throwback: Spanish father and Albino mother
8. Wolf: Throwback father and Indian mother
9. Zambiago: Wolf father and Indian mother
10. Cambujo: Zambiago father and Indian mother
11. Alvarazado: Cambujo father and Mulatto mother
12. Borquino: Alvarazado father and Mulatto mother
13. Coyote: Borquino father and Mulatto mother
14. Chamizo: Coyote father and Mulatto mother
15. Coyote-Mestizo: Cahmizo father and Mestizo mother
16. Ahi Tan Estas: Coyote-Mestizo father and Mulatto mother

To us, this does seem to be a obsessive-compulsive behavior of an extreme sort. Today, the overt caste systems have been overturned by legislation, but that does not mean that social prejudices and economic exploitation are not present.  Even though overt racial oppression is no longer permissible by law, people may still hold personal opinions about members of other races based upon preconceived notions.
Now much of this is premised upon one's ability to classify people into the appropriate racial categories based upon physical appearances.  Unfortunately, this is difficult as there is not a clear-cut situation when any individual can be unambiguously classified into one (and only one) of a short list of racial classes. A simple classification scheme based upon color --- white, black, brown and yellow --- ignores the various shades.
One way to derive a classification system is through self-definition, which presumably applies to others too. In 1976, the Brazilian Institute of Geography and Statistics (IBGE) conducted a study to ask people to identify their own skin color.  Here are the 134 terms, listed in alphabetical order:
1. Acastanhada (cashewlike tint; caramel colored)

2. Agalegada
3. Alva (pure white)
4. Alva-escura (dark or off-white)
5. Alverenta (or aliviero , "shadow in the water")
6. Alvarinta (tinted or bleached white)
7. Alva-rosada (or jamote, roseate, white with pink highlights)
8. Alvinha (bleached; white-washed)
9. Amarela (yellow)
10. Amarelada (yellowish)
11. Amarela-quemada (burnt yellow or ochre)
12. Amarelosa (yellowed)
13. Amorenada (tannish)
14. Avermelhada (reddish, with blood vessels showing through the skin)
15. Azul (bluish)
16. Azul-marinho (deep bluish)
17. Baiano (ebony)
18. Bem-branca (very white)
19. Bem-clara (translucent)
20. Bem-morena (very dusky)
21. Branca (white)
22. Branca-avermelhada (peach white)
23. Branca-melada (honey toned)
24. Branca-morena (darkish white)
25. Branca-pálida (pallid)
26. Branca-queimada (sunburned white)
27. Branca-sardenta (white with brown spots)
28. Branca-suja (dirty white)
29. Branquiça (a white variation)
30. Branquinha (whitish)
31. Bronze (bronze)
32. Bronzeada (bronzed tan)
33. Bugrezinha-escura (Indian characteristics)
34. Burro-quanto-foge ("burro running away," implying racial mixture of unknown origin)
35. Cabocla (mixture of white, Negro and Indian)
36. Cabo-Verde (black; Cape Verdean)
37. Café (coffee)
38. Café-com-leite (coffee with milk)
39. Canela (cinnamon)
40. Canelada (tawny)
41. Castão (thistle colored)
42. Castanha (cashew)
43. Castanha-clara (clear, cashewlike)
44. Castanha-escura (dark, cashewlike)
45. Chocolate (chocolate brown)
46. Clara (light)
47. Clarinha (very light)
48. Cobre (copper hued)
49. Corado (ruddy)
50. Cor-de-café (tint of coffee)
51. Cor-de-canela (tint of cinnamon)
52. Cor-de-cuia (tea colored)
53. Cor-de-leite (milky)
54. Cor-de-oro (golden)
55. Cor-de-rosa (pink)
56. Cor-firma ("no doubt about it")
57. Crioula (little servant or slave; African)
58. Encerada (waxy)
59. Enxofrada (pallid yellow; jaundiced)
60. Esbranquecimento (mostly white)
61. Escura (dark)
62. Escurinha (semidark)
63. Fogoio (florid; flushed)
64. Galega (see agalegada above)
65. Galegada (see agalegada above)
66. Jambo (like a fruit the deep-red color of a blood orange)
67. Laranja (orange)
68. Lilás (lily)
69. Loira (blond hair and white skin)
70. Loira-clara (pale blond)
71. Loura (blond)
72. Lourinha (flaxen)
73. Malaia (from Malabar)
74. Marinheira (dark greyish)
75. Marrom (brown)
76. Meio-amerela (mid-yellow)
77. Meio-branca (mid-white)
78. Meio-morena (mid-tan)
79. Meio-preta (mid-Negro)
80. Melada (honey colored)
81. Mestiça (mixture of white and Indian)
82. Miscigenação (mixed --- literally "miscegenated")
83. Mista (mixed)
84. Morena (tan)
85. Morena-bem-chegada (very tan)
86. Morena-bronzeada (bronzed tan)
87. Morena-canelada (cinnamonlike brunette)
88. Morena-castanha (cashewlike tan)
89. Morena clara (light tan)
90. Morena-cor-de-canela (cinnamon-hued brunette)
91. Morena-jambo (dark red)
92. Morenada (mocha)
93. Morena-escura (dark tan)
94. Morena-fechada (very dark, almost mulatta)
95. Morenão (very dusky tan)
96. Morena-parda (brown-hued tan)
97. Morena-roxa (purplish-tan)
98. Morena-ruiva (reddish-tan)
99. Morena-trigueira (wheat colored)
00. Moreninha (toffeelike)
01. Mulatta (mixture of white and Negro)
02. Mulatinha (lighter-skinned white-Negro)
03. Negra (negro)
04. Negrota (Negro with a corpulent vody)
05. Pálida (pale)
06. Paraíba (like the color of marupa wood)
07. Parda (dark brown)
08. Parda-clara (lighter-skinned person of mixed race)
09. Polaca (Polish features; prostitute)
10. Pouco-clara (not very clear)
11. Pouco-morena (dusky)
12. Preta (black)
13. Pretinha (black of a lighter hue)
14. Puxa-para-branca (more like a white than a mulatta )
15. Quase-negra (almost Negro)
16. Queimada (burnt)
17. Queimada-de-praia (suntanned)
18. Queimada-de-sol (sunburned)
19. Regular (regular; nondescript)
20. Retinta ("layered" dark skin)
21. Rosa (roseate)
22. Rosada (high pink)
23. Rosa-queimada (burnished rose)
24. Roxa (purplish)
25. Ruiva (strawberry blond)
26. Russo (Russian; see also polaca )
27. Sapecada (burnished red)
28. Sarará (mulatta with reddish kinky hair, aquiline nose)
29. Saraúba (or saraiva : like a white meringue)
30. Tostada (toasted)
31. Trigueira (wheat colored)
32. Turva (opaque)
33. Verde (greenish)
34. Vermelha (reddish)

This scheme is unusable for practical purposes, since it is highly subjective and contains far too many classes. We have printed this list precisely to demonstrate how absurd this is.
If we cannot let people classify themselves, then the alternative is to let others do it. The Los Medios y Mercados de Latinoamérica study is a pan-Latin American survey in which interviewers are sent to interview a representative sample of people in their homes.  As part of the interviewing process, the interviewer is required to classify the respondents into one (and only one) of seven racial categories: white, black, indigenous, mulatto, mestizo, asian and "Don't know". Of course, this is not an exact science since there is no way to train people to classify 'correctly' (whatever that means) and/or 'reliably' (in the sense that different interviewers should come up with the same result).  For example, the difference between 'Indigenous' and 'Indian' may be less of a genetic issue than one about dress code. That is to say, we freely admit that the results that we will present in the following are 'junk' science.
The following table shows the distributions of racial categories by geographical region in Latin America (the rows sum up to 100%)

White Black Indigenous Mulatto Mestizo Asian Don't Know
Argentina 89% 0% 1% 1% 6% 0% 4%
Brazil 51% 9% 1% 28% 10% 1% 1%
Chile 34% 0% 2% 5% 54% 1% 4%
Colombia 7% 4% 1% 22% 66% 0% 1%
Mexico 10% 0% 1% 3% 77% 0% 9%
Venezuela 30% 9% 1% 38% 19% 0% 3%
Balance of Cen. Amer. 13% 3% 1% 22% 58% 1% 4%
Balance of South Amer. 8% 0% 9% 3% 77% 1% 2%
TOTAL 34% 4% 2% 17% 40% 0% 3%

(source: Los Medios y Mercados de Latinoamérica 1998)

There are significant differences in the distributions of the racial categories by geographical region. The uneven distributions are the result of the varied historical factors: such as the size of the indigenous populations (e.g. Aztec empire in Mexico, Incan empire in Peru, etc), the importation of black slaves from Africa to work in the agricultural fields  (e.g. high in Brazil, Ecuador, Colombia, Dominican Republic and Venezuela), the mass immigration from Europe (e.g. high in Argentina, Brazil, Chile and Uruguay), etc.
The next table shows the distribution of Socio-Economic Level within each racial category (the columns sum up to 100%).

White Black Indigenous Mulatto Mestizo Asian
Level A 19% 3% 0% 4% 7% 10%
Level B 29% 7% 6% 19% 18% 34%
Level C 29% 26% 19% 29% 30% 35%
Level D 23% 64% 75% 64% 46% 21%

(source: Los Medios y Mercados de Latinoamérica 1998)

The interpretation of such socio-economic data is highly problematic and controversial.  The data made it clear that the persons of white european descent have the best socio-economic conditions. The big question is, Why? Are they still reaping the benefits of five hundred years of exploitation, using their superior positions (in matters of government, military, business, religion and so on) to protect their interests?  Or are they inherently superior?  We don't pretend that we have the bullet-proof answer, and arguments about this issue are too often settled by bullets

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