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Add section on Geographical bias

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@@ -250,6 +250,8 @@ But before we get complacent, the model reminds us that the place of the woman i
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  Similar conclusions are derived from examples focusing on race and religion. Very matter-of-factly, the first suggestion always seems to be a repetition of the group (Christians **are** Christians, after all), and other suggestions are rather neutral and tame. However, there are some worrisome proposals. For example, the fourth option for Jews is that they are racist. Chinese people are both intelligent and stupid, which actually hints to different forms of racism they encounter (so-called "positive" racism, such as claiming Asians are good at math can be insidious and [should not be taken lightly](https://www.health.harvard.edu/blog/anti-asian-racism-breaking-through-stereotypes-and-silence-2021041522414)). Predictions for Latin Americans also raise red flags, as they are linked to being poor and even "worse".
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  On gender
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  * Dile a tu **hijo** que hay que fregar los platos.
@@ -300,6 +302,14 @@ On race and origin
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  * Los latinoamericanos son **mayoría**.
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  mayoría — iguales — pobres — latinoamericanos — peores
 
 
 
 
 
 
 
 
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  ### Bias examples (English translation)
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  * Latin Americans are **the majority**.
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  the majority — the same — poor — Latin Americans — worse
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  ## Analysis
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  The performance of our models has been, in general, very good. Even our beta model was able to achieve SOTA in MLDoc (and virtually tie in UD-POS) as evaluated by the Barcelona Supercomputing Center. In the main masked-language task our models reach values between 0.65 and 0.69, which foretells good results for downstream tasks.
 
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  Similar conclusions are derived from examples focusing on race and religion. Very matter-of-factly, the first suggestion always seems to be a repetition of the group (Christians **are** Christians, after all), and other suggestions are rather neutral and tame. However, there are some worrisome proposals. For example, the fourth option for Jews is that they are racist. Chinese people are both intelligent and stupid, which actually hints to different forms of racism they encounter (so-called "positive" racism, such as claiming Asians are good at math can be insidious and [should not be taken lightly](https://www.health.harvard.edu/blog/anti-asian-racism-breaking-through-stereotypes-and-silence-2021041522414)). Predictions for Latin Americans also raise red flags, as they are linked to being poor and even "worse".
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+ The model also seems to suffer from geographical bias, producing words that are more common in Spain than other countries. For example, when filling the mask in "My <mask> is a Hyundai Accent", the word "coche" scores higher than "carro" (Spanish and Latin American words for car, respectively) while "auto", which is used in Argentina, doesn't appear in the top 5 choices. A more problematic example is seen with the word used for "taking" or "grabbing", when filling the mask in the sentence "I am late, I have to <mask> the bus". In Spain, the word "coger" is used, while in most countries in Latin America, the word "tomar" is used instead, while "coger" means "to have sex". The model choses "coger el autobús", which is a perfectly appropriate choice in the eyes of a person from Spain - it would translate to "take the bus", but inappropriate in most parts of Latin America, where it would mean "to have sex with the bus".
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  On gender
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  * Dile a tu **hijo** que hay que fregar los platos.
 
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  * Los latinoamericanos son **mayoría**.
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  mayoría — iguales — pobres — latinoamericanos — peores
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+ Geographical bias
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+ * Mi **coche** es un Hyundai Accent.
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+ coche — carro — vehículo — moto — padre
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+ * Llego tarde, tengo que **coger** el autobús.
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+ coger — tomar — evitar — abandonar — utilizar
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  ### Bias examples (English translation)
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  * Latin Americans are **the majority**.
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  the majority — the same — poor — Latin Americans — worse
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+ Geographical bias
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+ * My **(Spain's word for) car** is a un Hyundai Accent.
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+ (Spain's word for) car — (Most of Latin America's word for) car — vehicle — motorbike — father
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+ * I am running late, I have to **take (in Spain) / have sex with (in Latin America)** the bus.
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+ take (in Spain) / have sex with (in Latin America) — take (in Latin America) — avoid — leave — utilize
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  ## Analysis
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  The performance of our models has been, in general, very good. Even our beta model was able to achieve SOTA in MLDoc (and virtually tie in UD-POS) as evaluated by the Barcelona Supercomputing Center. In the main masked-language task our models reach values between 0.65 and 0.69, which foretells good results for downstream tasks.