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Topic · Sociology and Political Science

Names, Identity, and Discrimination Research

Names, Identity, and Discrimination Research is a research topic within Sociology and Political Science. Science Explorer counts 6k research works in it since 1950. 10.2% of them reached the world's top 10% most cited for their field and year.

This cluster of papers explores the pervasive issue of employment discrimination, particularly in the labor market, through field experiments and audit studies. It investigates various forms of discrimination based on ethnicity, race, gender, and names, shedding light on inequality in employment opportunities.

  • Discrimination
  • Labor Market
  • Field Experiment
  • Ethnic
  • Hiring
  • Racial
  • Names
  • Gender
  • Audit Study
  • Employment
Research works
6k
fractional, since 1950
In the world top 10%
608
per year above
Top-10% rate
10.2%
share of its works in the world top 10%
Growth, 2018-21 → 2022-25
+29%
the tick is no change
Largest producer
United States
45% of the 10 largest, 2022-now
Names, Identity, and Discrimination Research

Which countries lead Names, Identity, and Discrimination Research research?

By volume, the United States and the United Kingdom publish the most (428 and 114 works in 2022-now).

By volume, 2022-now

  1. 1 United States 428 works
  2. 2 United Kingdom 114 works
  3. 3 Germany 89 works
  4. 4 China 61 works
  5. 5 France 61 works
  6. 6 Canada 59 works
  7. 7 Brazil 39 works
  8. 8 Indonesia 34 works
  9. 9 South Africa 33 works
  10. 10 Australia 33 works

How concentrated that is

The same countries as shares of everything the list above accounts for. A node where two countries do two thirds of the work and one spread evenly across twelve read alike as a ranking and not at all alike here.

United States: 45.0%United Kingdom: 12.0%Germany: 9.4%China: 6.4%6 others listed: 27.2%45%largest
United States428 · 45.0%United Kingdom114 · 12.0%Germany89 · 9.4%China61 · 6.4%6 others listed259 · 27.2%

Shares of the rows listed above, not of the whole node.

Which institutions lead Names, Identity, and Discrimination Research research?

By volume in 2022-now, Centre National de la Recherche Scientifique publishes the most Names, Identity, and Discrimination Research research, followed by University of North Carolina at Chapel Hill and University of Chicago.

By volume, 2022-now

  1. 1 Centre National de la Recherche ScientifiqueFrance 19 works
  2. 2 University of North Carolina at Chapel HillUnited States 10 works
  3. 3 University of ChicagoUnited States 9 works
  4. 4 University of TorontoCanada 9 works
  5. 5 Stanford UniversityUnited States 8 works
  6. 6 University College LondonUnited Kingdom 7 works
  7. 7 Eötvös Loránd UniversityHungary 7 works
  8. 8 Cornell UniversityUnited States 7 works
  9. 9 University of CalabarNigeria 7 works
  10. 10 New York UniversityUnited States 6 works

Who are the leading researchers in Names, Identity, and Discrimination Research?

The most-cited researchers publishing on Names, Identity, and Discrimination Research include Nicholas G. Martin, Marko Sarstedt and Shane Douglas Morrison.

  1. 1 Nicholas G. Martin Australia 228k citations
  2. 2 Marko Sarstedt Germany 221k citations
  3. 3 Shane Douglas Morrison United States 148k citations

Ranked by citations received across their whole record, among researchers with at least three works on this topic.

What are the most cited papers in Names, Identity, and Discrimination Research?

The most cited paper in Names, Identity, and Discrimination Research is "Estimating Nonresponse Bias in Mail Surveys" (J. Scott Armstrong, Terry S. Overton, 1977), with 10,293 citations. Next come "Are Emily and Greg More Employable Than Lakisha and Jamal? A Field Experiment on Labor Market Discrimination" (4,548) and "Factoring and weighting approaches to status scores and clique identification" (3,273).

Most cited papers
#PaperReleasedCitations
1 Estimating Nonresponse Bias in Mail Surveys J. Scott Armstrong, Terry S. Overton · Journal of Marketing Research Aug 1977 10,293
2 Are Emily and Greg More Employable Than Lakisha and Jamal? A Field Experiment on Labor Market Discrimination Marianne Bertrand, Sendhil Mullainathan · American Economic Review Sep 2004 4,548
3 Factoring and weighting approaches to status scores and clique identification Phillip Bonacich · Journal of Mathematical Sociology 1972 3,273
4 The Swedish personal identity number: possibilities and pitfalls in healthcare and medical research Jonas Filip Ludvigsson, P Otterblad-Olausson, Birgitta U. Pettersson et al. · European Journal of Epidemiology Open access 5 Jun 2009 2,439
5 Thirty years of investigating the own-race bias in memory for faces: A meta-analytic review. Christian A. Meissner, John C. Brigham · Psychology Public Policy and Law Mar 2001 1,596
All 99 most cited papers, with filters and sorting

Where is Names, Identity, and Discrimination Research research done?

The largest centres of Names, Identity, and Discrimination Research research in 2022-now are London (United Kingdom), Paris (France), New York (United States) and Washington D.C. (United States).

Largest cities, 2022-now

  1. 1 LondonUnited Kingdom 27 works
  2. 2 ParisFrance 25 works
  3. 3 New YorkUnited States 24 works
  4. 4 Washington D.C.United States 19 works
  5. 5 BeijingChina 18 works
  6. 6 TokyoJapan 16 works
  7. 7 ChicagoUnited States 16 works
  8. 8 TorontoCanada 14 works
  9. 9 BudapestHungary 11 works
  10. 10 Los AngelesUnited States 11 works
See Names, Identity, and Discrimination Research on the map

Where is the best place to study Names, Identity, and Discrimination Research?

Among universities, judged by research, University of Chicago, University of North Carolina at Chapel Hill and University of Toronto score highest, combining excellence, specialisation, size, growth and international reach. Research strength is one signal when choosing where to study; it does not measure teaching.

Excellenceshare of its work in the world top 10%, 2022-now and all time averaged
40%
Specialisationhow much of its work is in this field, counted up to 10× the world share
10%
Sizeits output in this field, on a log scale
30%
Growthoutput growth, counted from -20% to +20%
10%
Internationalshare of its work with a co-author abroad
10%
Each slider sets a weight; the share it gets of the score is beside it.
#UniversityScoreTop 10%SpecialisationWorksGrowth
1University of ChicagoUnited States 73.122.5%8.3×9 +52.0%
2University of North Carolina at Chapel HillUnited States 43.03.6%4.3×10 +59.4%
3University of TorontoCanada 38.414.9%3.3×9 +182.4%

Universities only. The score blends excellence (40%), size (30%), specialisation (10%), growth (10%), international reach (10%), 2022-now; growth compares 2018-21 with 2022-25 and counts up to +20%, since a jump from a small base is mostly noise.

Every institution in Names, Identity, and Discrimination Research, country by country

Is Names, Identity, and Discrimination Research research growing?

Output in 2022-2025 was 29% higher than in 2018-2021, peaking in 2025. The fastest-growing topics are Names, Identity, and Discrimination Research.

still counting19801990200020102020
grewheldshrank

The same series as a ribbon: one cell per year, darker for more. The line above answers how much; this answers when.

Its share of all research

Growing output can still be a shrinking share: all of science grows. This is Names, Identity, and Discrimination Research as a percentage of every work published that year, 0.0070% in 2024.

still counting0.0050%0.010%Names, Identity, and Discrimination Research0.0069% in 202519801990200020102020

Fractional works of Names, Identity, and Discrimination Research over all fractional works that year. How the balance of science has shifted.

How much of it reaches the world top 10%

Year by year.

still counting5%10%15%Names, Identity, and Discrimination Research10.7% in 2025200020102020

Of each year's works in it, the share that reached the world's 10% most cited for their field and year. A field is the world for its own topics, so there is no other line to hold it against.

Which topics inside it are moving

Growth and decline on one axis around a shared zero. Two lists side by side hide the thing that matters: whether the growth dwarfs the decline, or the other way round.

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