NamSor's performance in predicting the country of origin and ethnicity of 90,000 researchers based on their first and last names

Sebo, Paul

doi:10.21203/rs.3.rs-1565759/v3

Cited by 2 publications

(1 citation statement)

References 7 publications

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“…27,28 While race characterization and accuracy using Namsor has not been extensively studied, this tool has been validated and allows for an objective method to characterize race in this retrospective study. 25,29…”

Section: Race and Gender Data Collectionmentioning

confidence: 99%

Gender and Racial Diversity in Relation to Publication Rates at the Canadian Association of Radiology Annual Scientific Meetings 2016 to 2019

Joarder,

Ahmadi,

Khosa

2023

Can Assoc Radiol J

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Purpose: To determine the overall rate of publication of abstracts presented at the 2016 to 2019 Canadian Association of Radiology Annual Scientific Meeting (CAR ASM), with an emphasis on gender and racial diversity. Methods: Abstracts from publicly available past programs were analyzed using PubMed, EMBASE, and Google Scholar for publication status, time to publication (TTP), author affiliation, and journal of publication. Past programs were used to determine the abstract format, abstract category, and the subspecialty and imaging modalities explored. First author demographics were identified using the Namsor software. Results: Four hundred and sixty-two abstract presentations were included in the analysis with an overall conversion rate of 34.63%. Two hundred and ninety-two (63.2%) of the first-authors were male-identified, of which 104 (35.62%) were published. In contrast, 170 (36.8%) were female-identified, of which 56 (32.94%) were published. Additionally, 50.87% first-authors were identified as white, 38.31% asian, 6.06% black, 4.76% latino, and 0.00% indigenous. While diversity was seen in demographics, 60% of publications had a white first-author. The following conversion rates were found: 40.85% white, 30.51% asian, 25% black, and 13.64% latino. In terms of abstract category, radiologist-in-training had the highest conversion rate at 60.71%. The median TTP was 14 months, with an average impact factor of 5.26. Conclusion: Less than half of abstracts at the 2016 to 2019 CAR ASM were published and both gender and racial disparities in relation to conversion rates were identified. Measures to improve publication rates and overall diversity in Radiology are warranted.

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Section: Race and Gender Data Collectionmentioning

confidence: 99%

Gender and Racial Diversity in Relation to Publication Rates at the Canadian Association of Radiology Annual Scientific Meetings 2016 to 2019

Joarder,

Ahmadi,

Khosa

2023

Can Assoc Radiol J

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How well does NamSor perform in predicting the country of origin and ethnicity of individuals based on their first and last names?

Sebo

2023

PLoS ONE

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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 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 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 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.

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NamSor's performance in predicting the country of origin and ethnicity of 90,000 researchers based on their first and last names

Cited by 2 publications

References 7 publications

Gender and Racial Diversity in Relation to Publication Rates at the Canadian Association of Radiology Annual Scientific Meetings 2016 to 2019

Gender and Racial Diversity in Relation to Publication Rates at the Canadian Association of Radiology Annual Scientific Meetings 2016 to 2019

How well does NamSor perform in predicting the country of origin and ethnicity of individuals based on their first and last names?

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