Posted by Here are the top 20 papers in The Social Science Research Network (SSRN) using or citing NamSor name classification software. SSRN is a high impact journal : the 2021 impact factor of SSRN Electronic Journal is 1, making it among the top 14% journals.
Some papers used NamSor to infer the gender of a personal name, some other papers to supplement subject data with race / ethnicity, or cultural heritage and ethnic origin. We’ve ranked the articles by their total number of downloads, without any adjustment based on the publication date. Some of the most downloaded papers are very recent (2020-2022), showing how impactful AI technology ca be, when applied to large databases to produce new data and scientific knowledge.
1. Diverse Hedge Funds
Number of pages: 70 Posted: 18 Feb 2021 Last Revised: 06 Jun 2022
Yan Lu, Narayan Y. Naik and Melvyn Teo
University of Central Florida – College of Business Administration, London Business School – Institute of Finance and Accounting and Singapore Management University – Lee Kong Chian School of Business
Keywords: Diversity, Homophily, Nationality, Experience, Education, Gender, Race, Ethnicity, Behavioral …
io), and NamSor (https://www.namsor.com) application programming interfaces (APIs) for predicting na- tionality, gender, and race from name. In results that are available upon request, we show that our baseline findings are robust to using forebears.io (https://forebears.io/onograph/) to estimate manager nationality and to using the NamePrism algorithm of Ye et al. (2017) 10 Hedge fund teams are not large. Of the funds managed by teams, 40.61% are managed by two people, 30.29% are …
Downloads : 1,009
2. Audit Partner Ethnicity and Salient Audit Phenomena
Number of pages: 73 Posted: 22 Jul 2020 Last Revised: 07 Jun 2022
Gopal V. Krishnan, Zvi Singer and Jing Zhang
Bentley University, HEC Montreal and university of Colorado Denver
Keywords: ethnicity; audit partner assignment; homophily; audit quality; work-related repercussion; minority
To identify the ethnicity of the above parties, we use NamSor, a popular machine learning-based software that identifies an individual’s most probable ethnicity and gender, based on the individual’s first and last names. 44F The software classifies individuals into the following four ethnic categories according to the U.S. Census taxonomy: Asian, Black non-Latino, Hispanic Latino, and White non-Latino. 55F We define a person belonging to the first three categories as an ethnic …
Downloads : 392
3. Name Similarity Encourages Generosity: A Field Experiment in Email Personalization
Munz, Kurt P., Minah H. Jung, and Adam L. Alter (2020) , “Name Similarity Encourages Generosity: A Field Experiment in Email Personalization,” Marketing Science, forthcoming.
Number of pages: 62 Posted: 14 Sep 2018 Last Revised: 05 May 2020
Kurt Munz, Minah Jung and Adam Alter
Bocconi University – Department of Marketing, New York University (NYU) – Department of Marketing and New York University (NYU) – Department of Marketing
Keywords: field experiment, charitable giving, individual targeting, personalization, one-to-one marketing
1 Machine Learning Approach We partnered with Namsor, a company that classifies names by gender, ethnicity, and national origin based on a proprietary machine-learning algorithm. Namsor trained their algorithm using data sets from across the world, and claims accuracy of about 75% for ethnicity in the US and greater than 95% for gender. We provided Namsor with both the given name and surname for each donor and teacher in our sample. Providing both names aids …
Downloads : 334
4. Does Gender and Ethnic Diversity among Audit Partners Influence Office-Level Audit Personnel Retention and Audit Quality?
Number of pages: 71 Posted: 11 May 2020 Last Revised: 10 Nov 2022
Eric Condie, Ling Lei Lisic, Timothy A. Seidel, J. Mike Truelson and Ally Zimmerman
Georgia Institute of Technology, Virginia Tech – Pamplin College of Business, Brigham Young University, Mississippi State University and Florida State University – Department of Accounting
Keywords: diversity, leadership, audit quality, audit offices, audit partners, audit fees
We then paid for an academic license to the program namsor.app to determine the ethnicity of the audit professionals based on both first and last names. According to the app, the program has been used in over 200 prior academic research studies. We manually reviewed a random sample of 100 names and ethnicity to verify that they were reasonably assigned. the gender diversity of non-partner office audit professionals (intern through managing director) for office j in year t, …
Downloads : 266
5. Race, Discrimination, and Hedge Funds
Number of pages: 55 Posted: 08 Apr 2022 Last Revised: 25 Jul 2022
Yan Lu, Narayan Y. Naik and Melvyn Teo
University of Central Florida – College of Business Administration, London Business School – Institute of Finance and Accounting and Singapore Management University – Lee Kong Chian School of Business
Keywords: Race, Racial bias, Discrimination, Barriers to entry, Minorities, Homophily, Education, Hedge …
Measuring race To determine manager and race, we rely on the NamSor application programming interface 7 for predicting race from name. We obtain manager race information for 13,578 managers running 18,696 funds, respectively. For robustness, we employ two alternative racial clas- sifications, one based on the NamePrism algorithm of Ye et al. (2017) and another based on the methodology of Imai and Khanna (2016). In addition, for 2,845 managers operating 4,454 funds, we hand collect …
Downloads : 252
6. The Gender Panopticon: Artificial Intelligence, Gender, and Design Justice
UCLA Law Review (2021)
Number of pages: 94 Posted: 06 Feb 2021 Last Revised: 04 Dec 2021
University of California, Berkeley – School of Law and affiliation not provided to SSRN
Keywords: Gender, Transgender, Artificial Intelligence, Design Justice
122 NamSor classifies personal names from a dataset of 1.3 million names plus sociolinguistic information, with three choices—male, female, or 116. Id. at 14. 117. Id. 118. Id. at 13. 119. Id. at 14–15. 120. Id. at 13 (describing gender-API.com). It currently supports almost 180 countries. Lucía Santamaría & Helena Mihaljević, Comparison and Benchmark of Name-to-Gender Inference Services, PEERJ COMPUT. SCI., July 16, 2018, at 1, 5. 121. Id. at 6. 122. Id.
Downloads : 239
7. The Demographics of Innovation in the United States
Number of pages: 87 Posted: 07 Nov 2017
Adams Nager, David M. Hart, Stephen J. Ezell and Robert D. Atkinson
Information Technology and Innovation Foundation, Schar School of Policy and Government, Information Technology and Innovation Foundation and Information Technology and Innovation Foundation
Keywords: innovation, demographics, patents, STEM, immigration, education, workforce, survey
66 Appendix E:
NamSor Tests and Interpretations …………………………………………………………………68
Gender Predictions…………………………………………………………………………………………… 68
Country of Origin and Language Families ……………………………………………………………….. 70
Downloads : 208
8. In Living Color: Does In-Person Screening Affect Who Gets Hired?
University of Chicago, Becker Friedman Institute for Economics Working Paper No. 2020-38
Number of pages: 79 Posted: 09 Apr 2020
John Manuel Barrios, Laura M. Giuliano and Andrew J. Leone
Washington University in St. Louis – John M. Olin Business School, University of Miami – School of Business Administration – Department of Economics and Northwestern University
Keywords: Job Matching, Screening, Signaling, Hiring, Networks, Imperfect Information, In-Person Interview, …
For gender, we use the NamSor Gender API, which infers gender from the combination of characters in individuals’ rst and last names.13 For cases where gender is identi ed with less than 99% certainty, we assign gender based on assessments made by research assistants using photographs from the professional websites of the candidates. We assign race and national origin to individuals in our sample by combining predictions using both NamSor and \NamePrism”, a …
Downloads : 202
9. Analysing Elsevier Journal Metadata with a New Specialized Workbench inside ICSR Lab
Number of pages: 9 Posted: 06 Sep 2022 Last Revised: 10 Nov 2022
Ramadurai Petchiappan, Kristy James, Andrew Plume, Efthymios Tsakonas, Ana Marušić, Mario Malicki, Francisco Grimaldo and Bahar Mehmani
Data Science Research Content (DSRC), Elsevier, Elsevier, International Center for the Study of Research, Elsevier, Elsevier, Stanford University, Stanford University – Meta-Research Innovation Center at Stanford (METRICS), Departament d’Informàtica – Universitat de València and affiliation not provided to SSRN
Keywords: Peer Review Workbench
Gender inference using Namsor API is not satisfactory for names and those are classified as “unknown”. 7. Inter-rater review agreement percentage is calculated only for articles with more than one reviewer part of the first round. 8. Namsor Gender Probability ranges from 0.5 to 1.0. A score of 0.5 indicates high uncertainty that the inferred gender is correct and a score of 1.0 indicates the highest level of certainty that the inferred gender is correct. At Elsevier, we use a cutoff …
Downloads : 195
10. Board Co-Option and Default Risk
Journal of Corporate Finance, Forthcoming
Number of pages: 47 Posted: 25 Jun 2019 Last Revised: 28 Jul 2020
Ghasan Baghdadi, Lily Nguyen and Edward Podolski
La Trobe University – La Trobe Business School – Department of Finance, The University of Queensland – UQ Business School and Deakin University
Keywords: expected default risk, board independence, agency conflicts, corporate governance
Moreover, the coefficients on the interactions between co-option and all measures 17 The UAI algorithm used to identify the likely country of heritage of the CEO is performed by an external service provider – NamSor. 18 Holder67 is a dummy variable equal to one if the CEO holds vested options with average moneyness of 67 percent or more at least twice during the sample period, starting in the first year the CEO displays this behavior. 21 …
Downloads : 192
11. Determinants and Career Consequences of Early Audit Partner Rotations
Number of pages: 55 Posted: 05 Oct 2021 Last Revised: 31 Oct 2022
Brandon Gipper, Luzi Hail and Christian Leuz
Stanford University Graduate School of Business, University of Pennsylvania – The Wharton School and University of Chicago – Booth School of Business
There are 2 versions of this paper
Keywords: auditor rotation, audit quality, audit partners, career development, audit industry, PCAOB
In sensitivity analyses (not tabulated), we use alternative algorithms such as https://namsor.app to classify partner gender based on first names and find similar results. 22 For Restated Financials, the unexplained rotation coefficient for female partners is not significant at conventional levels (i.e., two-sided p-value of 0.109). If in column (7) of Table 4 we replace the client fixed effects with industry fixed effects, the coefficient for female partners becomes significant with …
Downloads : 162
12. Represented But Unequal: The Contingent Effect of Legal Representation in Removal Proceedings
Law & Society Review, Forthcoming, USC CLASS Research Paper No. CLASS21-29 , USC Law Legal Studies Paper No. 21-29
Number of pages: 63 Posted: 15 Jul 2021
Emily Ryo and Ian Peacock
University of Southern California Gould School of Law and University of California, Los Angeles (UCLA)
Keywords: access to justice, immigration courts, removal proceedings, judicial decisionmaking
For a handful of IJs without formal biographies containing such pronouns, we used the NamSor classification tool developed by Carsenat (2013). NameSor uses proprietary machine learning algorithms trained on birth records and statistics from countries around the world that take into account cultural and sociolinguistic features of first and last names, to provide the likelihood of a given name being male, female, or unknown. White, another binary variable, indicates whether a given …
Downloads :152
13. Conflicts of Interest and Agent Heterogeneity in Buyer Brokerage
Number of pages: 88 Posted: 18 Mar 2021 Last Revised: 07 Sep 2022
Lawrence Kryzanowski, Yanting Wu and Tingyu Zhou
Concordia University, Quebec – John Molson School of Business, John Molson School of Business, Concordia University and Florida State University
Keywords: Real estate, Housing, Conflict of interests, Buyer brokerage, Non-binding principal-agent …
We use the classifier Namsor to classify their gender, race, and ethnicity.18 Namsor has developed a name-checking technology that uses big data and machine-learning tools to classify names by gender, race (White, Black, Hispanic, and Asian), and ethnicity (e.g., French, British, Italian, Jewish, Chinese, etc.). We also construct a set of proxies for demographic attributes, including education, age, marital status, and immigration status, based on census data. Because only 20,137 …
Downloads : 136
14. Who’s the Boss? Evidence of Job Seeker Bias from a Field Experiment
INSEAD Working Paper No. 2021/08/OBH
Number of pages: 48 Posted: 01 Mar 2021 Last Revised: 22 Mar 2021
Kaisa Snellman and Peter Younkin
INSEAD – Organisational Behavior and University of Oregon
Keywords: entrepreneurship, discrimination, field experiment, inequality, race
The NamSor classifier calculates weighted gender probabilities using the combination of first and last name taking into account the cultural origin. For example, the algorithm recognizes that Karen Gallagher is a female, Irish name, whereas Karen Grigoryan is a male, Armenian name. For each name, the classifier returns the value male, female, or unknown, as well as a parameter scale ranging from -1 to +1 to reflect the certainty that a name is male or female. For all names that …
Downloads : 134
15. The Immigrant Next Door: Long-Term Contact, Generosity, and Prejudice
University of Chicago, Becker Friedman Institute for Economics Working Paper No. 2021-16
Number of pages: 85 Posted: 09 Feb 2021 Last Revised: 01 Apr 2022
Leonardo Bursztyn, Thomas Chaney, Tarek A. Hassan and Aakash Rao
University of Chicago – Department of Economics, SciencesPo – Sciences Po – Department of Economics, Boston University and affiliation not provided to SSRN
There are 2 versions of this paper
Keywords: contact, attitudes, immigration, prejudice
14 To identify the likely ancestral country of origin of donors, we contract with NamSor, an organization which uses machine learning techniques on historical Census data to classify names by ethnicity, gender, and religion.15 In our main specification, we restrict the sample to donors matched to European countries to approximate a population of white “natives”.16 Given that no recipient country in our dataset is in Europe, this restriction also ensures that our results are not driven by …
Downloads : 115
16. Corresponding Authors: Past and Present How Has the Role of Corresponding Author Changed Since the Early 2000s? [ICSR Perspectives]
International Center for the Study of Research Paper No. 10
Number of pages: 2 Posted: 08 Mar 2022 Last Revised: 26 Aug 2022
Alvin Shijie Ding and Rachel Herbert
Elsevier – International Center for the Study of Research and International Center for the Study of Research
Keywords: Corresponding author, Research trends, Research careers, Bibliometrics, Scopus
Gender inference is powered by NamSor®. Find the code for the analyses in ICSR Lab supports your scholarly research by this infographic in ICSR Lab. giving access, at no cost, to powerful research metadata and metrics. ICSR Lab is a cloud- About ICSR based computational platform which enables The mission of the International Center for the Study of Research (ICSR) is researchers to analyze large structured datasets, to further the study of research and thus to contribute to the …
Downloads : 74
17. Discrimination Against Foreigners in the U.S. Patent System
Number of pages: 58 Posted: 27 Oct 2020
Gaétan de Rassenfosse and Reza Hosseini
Ecole Polytechnique Fédérale de Lausanne and Ecole Polytechnique Fédérale de Lausanne
Keywords: foreign bias, discrimination, disparate impact, national treatment principle, patent system
However, we have relied primarily on five sources: the PATSTAT database, the USPTO PAIR database, the Google Public Patent database, NamSor application programming interface (API), and NamePrism API. This section provides a brief overview of the data assembly process. Appendix A provides a detailed description of the construction of the dataset, and a GitHub repository contains relevant pieces of software.6 The EPO Worldwide Patent Statistical Database (known as PATSTAT) contains …
Downloads : 39
18. COVID-19 and Caregiving IS Researchers: In the Same Storm, but not in the Same Boat
Communications of the AIS, Forthcoming, 2021
Number of pages: 17 Posted: 29 Jun 2021
Wietske Van Osch and Cynthia Beath
affiliation not provided to SSRN and University of Texas at Austin – Department of Information, Risk and Operations Management
Keywords: COVID-19, Research productivity, Caregivers, Diversity, Inclusion, Gender, Women in IS
namsor.com to analyze author names to predict gender (it allows up to 5000 free classifications per month). There are multiple “genderizers” available, but this is the one Elsevier uses for their authorship gender reporting, hence we considered it the optimal choice for gender classification. Each prediction is associated with a confidence level. Although .85 is suggested as a cut-off, we used .95 as a cut-off, to be more conservative. Any name classification with a confidence level …
Downloads : 36
19. Conference Presentations and Academic Publishing
NBER Working Paper No. w26240
Number of pages: 51 Posted: 09 Sep 2019 Last Revised: 12 Sep 2022
Yuriy Gorodnichenko, Tho Pham and Oleksandr Talavera
University of California, Berkeley – Department of Economics, University of Reading and University of Birmingham
There are 2 versions of this paper
io and namsor.com to classify authors’ gender based on their first names (the former service) and their full names (the latter service). Out of 5,170 authors in our sample, the gender classifications obtained from these tools return the similarity of 95%. For the remaining authors whose names are either unisex or the gender classifications provided by two services are different, we manually establish gender of authors by going through their photos or biographies in the institutional …
Downloads : 9
20. The Immigrant Next Door: Long-Term Contact, Generosity, and Prejudice
NBER Working Paper No. w28448
Number of pages: 85 Posted: 08 Feb 2021 Last Revised: 25 Sep 2022
Leonardo Bursztyn, Thomas Chaney, Tarek A. Hassan and Aakaash Rao
University of Chicago – Department of Economics, SciencesPo – Sciences Po – Department of Economics, Boston University and Harvard University, Department of Economics
14 To identify the likely ancestral country of origin of donors, we contract with NamSor, an organization which uses machine learning techniques on historical Census data to classify names by ethnicity, gender, and religion.15 In our main specification, we restrict the sample to donors matched to European countries to approximate a population of white “natives”.16 Given that no recipient country in our dataset is in Europe, this restriction also ensures that our results are not driven by …
What about Race & Social Inequity research papers ?
Several of the papers mentionned above are related to race and ethnicity. As of 2022, none of those 20 papers are part of the SSRN’s Race & Social Inequity hub which highlights early-stage research related to systemic racism, racial violence, law enforcement reform, and social justice movements. Fields of study such as criminal justice, anthropology, political science and philosophy will help eradicate racism and bring about lasting change.
We have room for improvement, as a company, to promote NamSor as an essential tool for the modern anthropologist, sociologist, political scientist or even philosopher. As robots and algorithms take more and more decisions, on behalf of humans, we would like to position NamSor as a leading tool to fight discrimination and assess fairness of algorithms with respect to gender and race.
Image credits : DALL-E text-to-image AI, prompted with text “The Social Science Research Network”.
About NamSor
NamSor™ Applied Onomastics is a European vendor of sociolinguistics software (NamSor sorts names). NamSor mission is to help understand international flows of money, ideas and people. We proudly support Gender Gap Grader.