Inferring The World's Gender and Ethnic Diversity using Personal Names
The IOM Diaspora Mapping Toolkit analyses pros & cons for the use of big data and onomastics for Diaspora Mapping. It is based on field experience learned from several project conducted by The International Organization for Migration (IOM) using NamSor technology. One particular case study cited in the report is Skills Mapping Through Big Data: A case study of Armenian diaspora in the United States of America and France
As France doesn’t collect ethnic statistics, organizations in the public and private sector need to work around the lack of data to analyze potential discriminations.
DARES, the directorate of the Ministry of Labour, Employment and Integration which produces analyses, studies and statistics on the themes of work, employment, vocational training and social dialogue has used NamSor to prepare a study on competitive exams in the public sector.
Burkina Faso is a multi-cultural and diverse country with a rich history. In this article, we would like to explorer how personal names can be interpreted to reflect regional, ethnic appartenance within the country. Then we would like to illustrate how the use of a personal name can affect a black-box Artificial Intelligence – such as OpenAI’s DALL-E. This is a first article in our series of blog posts with tag #thisnamedpersondoesnotexist.
We’ve used a non-supervised clustering algorithm to identify Russian (Ivanov, Popov), Korean (Kim, Pak) and other names in Kazakhstan and differentiate them from Kakakh names (AZAMAT ABDRAKHMANOV, ERLAN AHMETOV, AIGUL ABDRAKHMANOVA / AYGUL ABDRAKHMANOVA …)
What’s in a name? Artificial intelligence was used to classify the personal names of entrepreneurs and beneficial owners of companies in eight European countries and derive unique insights into the Contribution and Challenges of Ethnic Minority Businesses in Europe.
For International Women’s Day, one blog post and one large study by European Commission illustrate how NamSor can be used to produced an analysis of the gender gap in a particular field, using open databases.
n this fresh study, “Implicit Mentoring The Unacknowledged Developer Efforts in Open Source”, Zixuan Feng, Amreeta Chatterjee, Anita Sarma, and Iftekhar Ahmed characterize implicit mentoring in software development and examine gender behavioural differences.
Romanization of Japanese names is easy, but translating a Japanese name back to its original form in Kanji with the correct probabilities is hard. There are many Kanji variants for a single Japanese name in its romanized form.
In the early 19th century, the Americo-Liberian settlers encountered ethnically, linguistically diverse tribal populations. Even today, names reflect the diversity of populations in Liberia. Some names appear very similar to names of Afrlcan-Americans. Some other names reflect indigenous cultures.
We used NamSor ML to discover three groups of names, among male names and female names in Tatarstan. For each group, we show the most frequent given names and family names.
You can now enrich SalesForce contacts with gender information purely based on their names. The new add-on component was released
Since 2018, NamSor has been used append gender to authors in RePEC (Research Papers in Economics). Overall, 25.8% of economists are female.
If you are unfamiliar with North-Macedonian language and culture, you might think that МАРЈАН is a female name, right? Well it’s not. It’s most likely a male name.
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