How well does NamSor perform in predicting the country of origin and ethnicity of individuals based on their first and last names?
Journal
PloS one
ISSN: 1932-6203
Titre abrégé: PLoS One
Pays: United States
ID NLM: 101285081
Informations de publication
Date de publication:
2023
2023
Historique:
received:
03
08
2023
accepted:
02
11
2023
medline:
20
11
2023
pubmed:
17
11
2023
entrez:
16
11
2023
Statut:
epublish
Résumé
We aimed to evaluate NamSor's performance in predicting the country of origin and ethnicity of individuals based on their first/last names. We retrieved the name and country of affiliation of all authors of PubMed publications in 2021, affiliated with universities in the twenty-two countries whose researchers authored ≥1,000 medical publications and whose percentage of migrants was <2.5% (N = 88,699). We estimated with NamSor their most likely "continent of origin" (Asia/Africa/Europe), "country of origin" and "ethnicity". We also examined two other variables that we created: "continent#2" ("Europe" replaced by "Europe/America/Oceania") and "country#2" ("Spain" replaced by "Spain/Hispanic American country" and "Portugal" replaced by "Portugal/Brazil"). Using "country of affiliation" as a proxy for "country of origin", we calculated for these five variables the proportion of misclassifications (= errorCodedWithoutNA) and the proportion of non-classifications (= naCoded). We repeated the analyses with a subsample consisting of all results with inference accuracy ≥50%. For the full sample and the subsample, errorCodedWithoutNA was 16.0% and 12.6% for "continent", 6.3% and 3.3% for "continent#2", 27.3% and 19.5% for "country", 19.7% and 11.4% for "country#2", and 20.2% and 14.8% for "ethnicity"; naCoded was zero and 18.0% for all variables, except for "ethnicity" (zero and 10.7%). NamSor is accurate in determining the continent of origin, especially when using the modified variable (continent#2) and/or restricting the analysis to names with accuracy ≥50%. The risk of misclassification is higher with country of origin or ethnicity, but decreases, as with continent of origin, when using the modified variable (country#2) and/or the subsample.
Sections du résumé
BACKGROUND
BACKGROUND
We aimed to evaluate NamSor's performance in predicting the country of origin and ethnicity of individuals based on their first/last names.
METHODS
METHODS
We retrieved the name and country of affiliation of all authors of PubMed publications in 2021, affiliated with universities in the twenty-two countries whose researchers authored ≥1,000 medical publications and whose percentage of migrants was <2.5% (N = 88,699). We estimated with NamSor their most likely "continent of origin" (Asia/Africa/Europe), "country of origin" and "ethnicity". We also examined two other variables that we created: "continent#2" ("Europe" replaced by "Europe/America/Oceania") and "country#2" ("Spain" replaced by "Spain/Hispanic American country" and "Portugal" replaced by "Portugal/Brazil"). Using "country of affiliation" as a proxy for "country of origin", we calculated for these five variables the proportion of misclassifications (= errorCodedWithoutNA) and the proportion of non-classifications (= naCoded). We repeated the analyses with a subsample consisting of all results with inference accuracy ≥50%.
RESULTS
RESULTS
For the full sample and the subsample, errorCodedWithoutNA was 16.0% and 12.6% for "continent", 6.3% and 3.3% for "continent#2", 27.3% and 19.5% for "country", 19.7% and 11.4% for "country#2", and 20.2% and 14.8% for "ethnicity"; naCoded was zero and 18.0% for all variables, except for "ethnicity" (zero and 10.7%).
CONCLUSION
CONCLUSIONS
NamSor is accurate in determining the continent of origin, especially when using the modified variable (continent#2) and/or restricting the analysis to names with accuracy ≥50%. The risk of misclassification is higher with country of origin or ethnicity, but decreases, as with continent of origin, when using the modified variable (country#2) and/or the subsample.
Identifiants
pubmed: 37972002
doi: 10.1371/journal.pone.0294562
pii: PONE-D-23-24627
pmc: PMC10653483
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
e0294562Informations de copyright
Copyright: © 2023 Paul Sebo. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Déclaration de conflit d'intérêts
The authors have declared that no competing interests exist.
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