Trackademia

Welcome to Trackademia

The idea behind Trackademia is to build on existing academic databases like Google Scholar and OpenAlex so that you can trust the data and use it for whatever you want. That comes down to two things.

More data, and more ways to use it. We aggregate publication data from every major source into a single dataset and add information pulled from faculty CVs. Then we let you slice it however you want: choose which sources to build from, write your own formulas, weight journals, adjust for department size.

More accurate, and honest about where it isn’t. We focus on a smaller set of schools so we can verify everything carefully. Faculty lists come from department websites rather than being inferred from publication records, so we know who should be in the data before we go looking. When we can’t find data on someone, we record the gap instead of dropping them. Every number comes with a coverage rate you can check against ground truth.

Everything in Trackademia is built from seven units. AI merges duplicate records across sources and tags each publication so these categories hold up:

  • Publication — citation counts, authors, journal, peer review status, and more
  • Publication group — versions of the same work combined into one entity, such as a working paper and the article it became
  • Academic
  • Department
  • University
  • Field
  • Journal

There are two modes. In Database mode you browse the underlying records and filter by any of the seven units. In Analytics mode you get graphs and comparisons, and you switch views to compare two departments, compare one department against the average of the others, or see them all at once. Tabs let you focus on a particular level of the data.

Trackademia

Every graph on this site

Publications

  • Ranking Ranked table
    • Value: Citations, Weighted citations, Publications
    • Measure: Total, Mean per work, Median per work
  • Works published per year Lines over years
    • Measure: Total, Mean per academic, Median per academic
    • Calendar year or years since PhD
    • In each year or cumulative
  • Citations received per year Lines over years
    • Value: Citations, Weighted citations
    • Measure: Total, Mean per work, Median per work, Mean per academic, Median per academic
    • In each year or cumulative
  • Citation distribution Bars
    • Value: Citations, Weighted citations
  • Citations by age of work Lines over years
    • Value: Citations, Weighted citations
    • Measure: Total, Mean per work, Median per work
  • Publication type mix Ranked bars
    • Value: Citations, Weighted citations, Publications
  • Top venues Ranked bars
    • Value: Citations, Weighted citations, Publications

Academicshere

Departments

  • Ranking Ranked table
    • Value: Citations, Weighted citations, Publications
    • Measure: Total, Mean per work, Median per work, Mean per academic, Median per academic, Formula
  • Publications over time Lines over years
    • Measure: Total, Mean per academic, Median per academic, Formula
    • Calendar year or years since PhD
    • In each year or cumulative
  • Citations over time Lines over years
    • Value: Citations, Weighted citations
    • Measure: Total, Mean per academic, Median per academic, Formula
    • In each year or cumulative
  • Makeup by tenure track Stacked bars
  • Output by rank Grouped bars
    • Value: Citations, Weighted citations, Publications
    • Measure: Total, Mean per work, Median per work, Mean per academic, Median per academic, Formula
  • Academics ranked against academics Grouped bars
    • Value: Citations, Weighted citations, Publications
    • How many ranks (opens on 5)
  • Years to promotion Grouped bars
  • Journals used Stacked bars
    • Value: Citations, Weighted citations, Publications

Journals

Fields

  • Ranking Ranked table
    • Value: Citations, Weighted citations, Publications
    • Measure: Total, Mean per work, Median per work, Mean per academic, Median per academic
  • Departments by field Bars
    • Measure: Total, Mean per work, Median per work, Mean per academic, Median per academic
  • University rollup Ranked bars
  • Coverage by field Ranked bars

Trackademia

Search the whole site

Search a person, a department, a journal or the title of a work. A person’s name brings up their profile, their publications, their department and the journals they publish in.

Value Measure

Academics

Citations per year in post (from the first professorial appointment, else the PhD year) · the 15 highest of 100 academics
1 Andrew Gelman Columbia Political Science · Distinguished · 36 years in post 6,483.1
2 Gary King Harvard Government · Distinguished · 42 years in post 2,916.8
3 Brendan Nyhan Dartmouth Government · Distinguished · 15 years in post 2,557.9
4 Dustin Tingley Harvard Government · Distinguished · 16 years in post 2,411.8
5 Donald P. Green Columbia Political Science · Distinguished · 37 years in post 1,655.4
6 Steven Levitsky Harvard Government · Distinguished · 26 years in post 1,470.0
7 Peter A. Hall Harvard Government · Distinguished · 44 years in post 1,338.1
8 Andreas Wimmer Columbia Political Science · Distinguished · 27 years in post 1,129.9
9 Matthew Levendusky Penn Political Science · Distinguished · 19 years in post 1,059.9
10 Amy Gutmann Penn Political Science · Distinguished · 50 years in post 1,043.3
11 Daniel J. Hopkins Penn Political Science · Distinguished · 17 years in post 990.5
12 Alan S. Gerber Yale Political Science · Distinguished · 32 years since the PhD 895.0
13 Beth Simmons Penn Political Science · Distinguished · 35 years in post 844.7
14 Nicholas Sambanis Yale Political Science · Distinguished · 25 years in post 821.0
15 Gregory Alain Huber Yale Political Science · Distinguished · 25 years in post 787.0

1,391,112 citations over 6,426 of 9,450 works (68% carry a count). 99 of 100 academics have at least one counted work. A work with no citation count is unknown here, never a zero.

Publications by career year

Publications in each year of a career
Measure

Pooled over the 96 of 100 academics whose CV states a PhD year, across 8 departments; career year 0 is the PhD year. A career year fewer than 5 of them have reached is a gap. A total counts only the academics who had reached that career year, so the tail is low because fewer of them are in it; the mean and the median divide by exactly those academics.

What these filters select, over everything selected not what the graph divided by
Selected Academics CVScholarOpenAlex Works With a count
Everything selected 100 100/100 1.0% 75/100 0.75% 98/100 0.98% 9450 6426/9450 0.68%
  • Over the academics these filters select, so a filtered page describes the academics it selected and not the whole department.
  • A row with nothing held draws no mark above: the graph is quiet there because the evidence is missing, not because the work is.
  • What there was to draw from, not what the graph divided by - the graph states its own denominator above.
  • A Scholar profile is attached when at least 3 of the CV titles are found on it, or 30% of them are; one at another institution or under a different name needs 10 titles, and a profile far larger than the CV that holds only a small part of it is refused. Its articles are then checked one by one: what is not a work, or not by this person, is not counted.

Citations by career year

Citations of the works published in each career year
Value Measure

Pooled over the 96 of 100 academics whose CV states a PhD year, across 8 departments; career year 0 is the PhD year. A career year fewer than 5 of them have reached is a gap. The citations of the works published in that career year, not the citations received in it. A total counts only the academics who had reached that career year, so the tail is low because fewer of them are in it; the mean and the median divide by exactly those academics.

What these filters select, over everything selected not what the graph divided by
Selected Academics CVScholarOpenAlex Works With a count
Everything selected 100 100/100 1.0% 75/100 0.75% 98/100 0.98% 9450 6426/9450 0.68%
  • Over the academics these filters select, so a filtered page describes the academics it selected and not the whole department.
  • A row with nothing held draws no mark above: the graph is quiet there because the evidence is missing, not because the work is.
  • What there was to draw from, not what the graph divided by - the graph states its own denominator above.
  • A Scholar profile is attached when at least 3 of the CV titles are found on it, or 30% of them are; one at another institution or under a different name needs 10 titles, and a profile far larger than the CV that holds only a small part of it is refused. Its articles are then checked one by one: what is not a work, or not by this person, is not counted.

Publications per year

Works published in each year
Each point

One line over the 100 academics the filters select, by the year each work was published; an undated work is in no year. A work two colleagues share counts once for their department.

What these filters select, per academic not what the graph divided by
Academic Academics CVScholarOpenAlex Works With a count
Melissa Sharon Lane 1 1/1 1.0% 0/1 0.0% 0/1 0.0% 54 0/54 0.0%
Adam Meirowitz 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 50 46/50 0.92%
Alan S. Gerber 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 144 130/144 0.9027777777777778%
Amaney A. Jamal 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 108 79/108 0.7314814814814815%
Amy Gutmann 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 111 78/111 0.7027027027027027%
Andreas Wimmer 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 114 87/114 0.7631578947368421%
Andrew Gelman 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 533 438/533 0.8217636022514071%
Andrew J. Nathan 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 745 140/745 0.18791946308724833%
Arthur Spirling 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 47 44/47 0.9361702127659575%
Ashutosh Varshney 1 1/1 1.0% 0/1 0.0% 1/1 1.0% 54 37/54 0.6851851851851852%
Atul Kohli 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 69 57/69 0.8260869565217391%
Beth Simmons 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 97 80/97 0.8247422680412371%
Brendan Nyhan 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 100 98/100 0.98%
Brendan O'Leary 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 309 122/309 0.3948220064724919%
Carles Boix 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 60 53/60 0.8833333333333333%
Christina L. Davis 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 39 29/39 0.7435897435897436%
Claudine Gay 1 1/1 1.0% 0/1 0.0% 1/1 1.0% 12 11/12 0.9166666666666666%
Daniel Gillion 1 1/1 1.0% 0/1 0.0% 1/1 1.0% 11 11/11 1.0%
Daniel J. Hopkins 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 71 70/71 0.9859154929577465%
Daniel Paul Carpenter 1 1/1 1.0% 1/1 1.0% 0/1 0.0% 142 96/142 0.676056338028169%
Daniel Ziblatt 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 72 49/72 0.6805555555555556%
Danielle S. Allen 1 1/1 1.0% 0/1 0.0% 1/1 1.0% 52 29/52 0.5576923076923077%
David Skarbek 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 43 38/43 0.8837209302325582%
Deborah J. Yashar 1 1/1 1.0% 0/1 0.0% 1/1 1.0% 22 10/22 0.45454545454545453%
Diana C. Mutz 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 86 70/86 0.813953488372093%
Donald P. Green 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 240 215/240 0.8958333333333334%
Douglas L. Kriner 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 85 67/85 0.788235294117647%
Dustin Tingley 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 101 94/101 0.9306930693069307%
Edward D. Mansfield 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 123 100/123 0.8130081300813008%
Edward S. Steinfeld 1 1/1 1.0% 0/1 0.0% 1/1 1.0% 27 10/27 0.37037037037037035%
Elisabeth Jean Wood 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 43 36/43 0.8372093023255814%
Elizabeth J. Perry 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 139 76/139 0.5467625899280576%
Eric M. Patashnik 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 81 40/81 0.49382716049382713%
Eric Nelson 1 1/1 1.0% 0/1 0.0% 1/1 1.0% 23 19/23 0.8260869565217391%
Erik Wibbels 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 60 55/60 0.9166666666666666%
G. John Ikenberry 1 1/1 1.0% 0/1 0.0% 1/1 1.0% 125 89/125 0.712%
Gary King 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 356 296/356 0.8314606741573034%
GERARD PADRÓ i MIQUEL 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 27 24/27 0.8888888888888888%
Gregory Alain Huber 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 120 114/120 0.95%
Grzegorz Ekiert 1 1/1 1.0% 0/1 0.0% 1/1 1.0% 45 25/45 0.5555555555555556%
Guy Grossman 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 48 47/48 0.9791666666666666%
Helen V. Milner 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 133 114/133 0.8571428571428571%
Ian Shapiro 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 168 141/168 0.8392857142857143%
Ira I. Katznelson 1 1/1 1.0% 0/1 0.0% 1/1 1.0% 105 65/105 0.6190476190476191%
Jack L. Snyder 1 1/1 1.0% 0/1 0.0% 1/1 1.0% 79 64/79 0.810126582278481%
Jacob S. Hacker 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 201 98/201 0.48756218905472637%
James M. Snyder, Jr. 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 142 133/142 0.9366197183098591%
Jason Lyall 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 20 20/20 1.0%
Jean Louise Cohen 1 1/1 1.0% 0/1 0.0% 1/1 1.0% 68 28/68 0.4117647058823529%
Jeff D. Colgan 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 66 46/66 0.696969696969697%
Jennifer Hochschild 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 160 102/160 0.6375%
Jennifer Jerit 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 47 39/47 0.8297872340425532%
John Michael Carey 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 102 63/102 0.6176470588235294%
Joshua David Kertzer 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 55 46/55 0.8363636363636363%
Margaret M. Weir 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 65 50/65 0.7692307692307693%
Mark McGann Blyth 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 121 80/121 0.6611570247933884%
Matthew Levendusky 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 52 46/52 0.8846153846153846%
Melani Cammett 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 51 41/51 0.803921568627451%
Melissa Schwartzberg 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 48 37/48 0.7708333333333334%
Michael Eric ROSEN 1 1/1 1.0% 0/1 0.0% 1/1 1.0% 29 23/29 0.7931034482758621%
Michael Horowitz 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 150 80/150 0.5333333333333333%
Michael J. Hiscox 1 1/1 1.0% 0/1 0.0% 1/1 1.0% 16 16/16 1.0%
Michael Jones-Correa 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 71 46/71 0.647887323943662%
Milan Svolik 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 22 21/22 0.9545454545454546%
Nadia Urbinati 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 245 144/245 0.5877551020408164%
Nicholas Sambanis 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 71 60/71 0.8450704225352113%
Nolan McCarty 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 73 50/73 0.684931506849315%
Paul E. Peterson 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 419 287/419 0.684964200477327%
Peter A. Hall 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 154 114/154 0.7402597402597403%
Peter Andreas 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 64 51/64 0.796875%
Peter Joachim Katzenstein 1 1/1 1.0% 0/1 0.0% 1/1 1.0% 114 73/114 0.6403508771929824%
Rafaela Dancygier 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 32 26/32 0.8125%
Richard F. Bensel 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 37 21/37 0.5675675675675675%
Robert Y. Shapiro 1 1/1 1.0% 0/1 0.0% 1/1 1.0% 125 69/125 0.552%
ROSE McDERMOTT 1 1/1 1.0% 0/1 0.0% 1/1 1.0% 145 102/145 0.7034482758620689%
Roxanne L. Euben 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 33 20/33 0.6060606060606061%
Russell Muirhead 1 1/1 1.0% 0/1 0.0% 1/1 1.0% 25 20/25 0.8%
Sarah E. Kreps 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 156 104/156 0.6666666666666666%
Sharon R. Krause 1 1/1 1.0% 0/1 0.0% 1/1 1.0% 33 28/33 0.8484848484848485%
Sharyn O’Halloran 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 42 27/42 0.6428571428571429%
Sonu Bedi 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 19 18/19 0.9473684210526315%
Stephen Daniel Ansolabehere 1 1/1 1.0% 0/1 0.0% 1/1 1.0% 84 78/84 0.9285714285714286%
Stephen Macedo 1 1/1 1.0% 0/1 0.0% 1/1 1.0% 69 49/69 0.7101449275362319%
Stephen Skowronek 1 1/1 1.0% 0/1 0.0% 1/1 1.0% 35 24/35 0.6857142857142857%
Steven I. Wilkinson 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 31 21/31 0.6774193548387096%
Steven Levitsky 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 107 90/107 0.8411214953271028%
Susan L. Moffitt 1 1/1 1.0% 0/1 0.0% 1/1 1.0% 18 18/18 1.0%
Suzanne Mettler 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 79 56/79 0.7088607594936709%
Taeku Lee 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 56 39/56 0.6964285714285714%
Tali Mendelberg 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 65 51/65 0.7846153846153846%
TARIQ THACHIL 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 20 17/20 0.85%
Theda Skocpol 1 1/1 1.0% 0/1 0.0% 1/1 1.0% 151 88/151 0.5827814569536424%
Thomas B. Pepinsky 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 152 92/152 0.6052631578947368%
Timothy M. Frye 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 64 50/64 0.78125%
Torben Iversen 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 67 61/67 0.9104477611940298%
Tulia G. Falleti 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 47 38/47 0.8085106382978723%
Virginia Page Fortna 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 20 16/20 0.8%
Wendy J. Schiller 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 37 20/37 0.5405405405405406%
William C. Wohlforth 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 102 76/102 0.7450980392156863%
Yuhua Wang 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 30 26/30 0.8666666666666667%
  • Over the academics these filters select, so a filtered page describes the academics it selected and not the whole department.
  • A row with nothing held draws no mark above: the graph is quiet there because the evidence is missing, not because the work is.
  • What there was to draw from, not what the graph divided by - the graph states its own denominator above.
  • A Scholar profile is attached when at least 3 of the CV titles are found on it, or 30% of them are; one at another institution or under a different name needs 10 titles, and a profile far larger than the CV that holds only a small part of it is refused. Its articles are then checked one by one: what is not a work, or not by this person, is not counted.

Citations per year

Citations received in each year
Each point

One line over the 100 academics the filters select. Citations received in each year, from the academics’ verified Scholar profiles, which count every citation to everything they wrote: no publication filter reaches this line, and no journal weight either, which is why it offers no Value.

What these filters select, per academic not what the graph divided by
Academic Academics CVScholarOpenAlex Works With a count
Melissa Sharon Lane 1 1/1 1.0% 0/1 0.0% 0/1 0.0% 54 0/54 0.0%
Adam Meirowitz 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 50 46/50 0.92%
Alan S. Gerber 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 144 130/144 0.9027777777777778%
Amaney A. Jamal 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 108 79/108 0.7314814814814815%
Amy Gutmann 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 111 78/111 0.7027027027027027%
Andreas Wimmer 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 114 87/114 0.7631578947368421%
Andrew Gelman 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 533 438/533 0.8217636022514071%
Andrew J. Nathan 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 745 140/745 0.18791946308724833%
Arthur Spirling 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 47 44/47 0.9361702127659575%
Ashutosh Varshney 1 1/1 1.0% 0/1 0.0% 1/1 1.0% 54 37/54 0.6851851851851852%
Atul Kohli 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 69 57/69 0.8260869565217391%
Beth Simmons 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 97 80/97 0.8247422680412371%
Brendan Nyhan 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 100 98/100 0.98%
Brendan O'Leary 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 309 122/309 0.3948220064724919%
Carles Boix 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 60 53/60 0.8833333333333333%
Christina L. Davis 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 39 29/39 0.7435897435897436%
Claudine Gay 1 1/1 1.0% 0/1 0.0% 1/1 1.0% 12 11/12 0.9166666666666666%
Daniel Gillion 1 1/1 1.0% 0/1 0.0% 1/1 1.0% 11 11/11 1.0%
Daniel J. Hopkins 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 71 70/71 0.9859154929577465%
Daniel Paul Carpenter 1 1/1 1.0% 1/1 1.0% 0/1 0.0% 142 96/142 0.676056338028169%
Daniel Ziblatt 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 72 49/72 0.6805555555555556%
Danielle S. Allen 1 1/1 1.0% 0/1 0.0% 1/1 1.0% 52 29/52 0.5576923076923077%
David Skarbek 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 43 38/43 0.8837209302325582%
Deborah J. Yashar 1 1/1 1.0% 0/1 0.0% 1/1 1.0% 22 10/22 0.45454545454545453%
Diana C. Mutz 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 86 70/86 0.813953488372093%
Donald P. Green 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 240 215/240 0.8958333333333334%
Douglas L. Kriner 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 85 67/85 0.788235294117647%
Dustin Tingley 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 101 94/101 0.9306930693069307%
Edward D. Mansfield 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 123 100/123 0.8130081300813008%
Edward S. Steinfeld 1 1/1 1.0% 0/1 0.0% 1/1 1.0% 27 10/27 0.37037037037037035%
Elisabeth Jean Wood 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 43 36/43 0.8372093023255814%
Elizabeth J. Perry 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 139 76/139 0.5467625899280576%
Eric M. Patashnik 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 81 40/81 0.49382716049382713%
Eric Nelson 1 1/1 1.0% 0/1 0.0% 1/1 1.0% 23 19/23 0.8260869565217391%
Erik Wibbels 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 60 55/60 0.9166666666666666%
G. John Ikenberry 1 1/1 1.0% 0/1 0.0% 1/1 1.0% 125 89/125 0.712%
Gary King 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 356 296/356 0.8314606741573034%
GERARD PADRÓ i MIQUEL 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 27 24/27 0.8888888888888888%
Gregory Alain Huber 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 120 114/120 0.95%
Grzegorz Ekiert 1 1/1 1.0% 0/1 0.0% 1/1 1.0% 45 25/45 0.5555555555555556%
Guy Grossman 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 48 47/48 0.9791666666666666%
Helen V. Milner 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 133 114/133 0.8571428571428571%
Ian Shapiro 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 168 141/168 0.8392857142857143%
Ira I. Katznelson 1 1/1 1.0% 0/1 0.0% 1/1 1.0% 105 65/105 0.6190476190476191%
Jack L. Snyder 1 1/1 1.0% 0/1 0.0% 1/1 1.0% 79 64/79 0.810126582278481%
Jacob S. Hacker 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 201 98/201 0.48756218905472637%
James M. Snyder, Jr. 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 142 133/142 0.9366197183098591%
Jason Lyall 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 20 20/20 1.0%
Jean Louise Cohen 1 1/1 1.0% 0/1 0.0% 1/1 1.0% 68 28/68 0.4117647058823529%
Jeff D. Colgan 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 66 46/66 0.696969696969697%
Jennifer Hochschild 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 160 102/160 0.6375%
Jennifer Jerit 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 47 39/47 0.8297872340425532%
John Michael Carey 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 102 63/102 0.6176470588235294%
Joshua David Kertzer 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 55 46/55 0.8363636363636363%
Margaret M. Weir 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 65 50/65 0.7692307692307693%
Mark McGann Blyth 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 121 80/121 0.6611570247933884%
Matthew Levendusky 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 52 46/52 0.8846153846153846%
Melani Cammett 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 51 41/51 0.803921568627451%
Melissa Schwartzberg 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 48 37/48 0.7708333333333334%
Michael Eric ROSEN 1 1/1 1.0% 0/1 0.0% 1/1 1.0% 29 23/29 0.7931034482758621%
Michael Horowitz 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 150 80/150 0.5333333333333333%
Michael J. Hiscox 1 1/1 1.0% 0/1 0.0% 1/1 1.0% 16 16/16 1.0%
Michael Jones-Correa 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 71 46/71 0.647887323943662%
Milan Svolik 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 22 21/22 0.9545454545454546%
Nadia Urbinati 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 245 144/245 0.5877551020408164%
Nicholas Sambanis 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 71 60/71 0.8450704225352113%
Nolan McCarty 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 73 50/73 0.684931506849315%
Paul E. Peterson 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 419 287/419 0.684964200477327%
Peter A. Hall 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 154 114/154 0.7402597402597403%
Peter Andreas 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 64 51/64 0.796875%
Peter Joachim Katzenstein 1 1/1 1.0% 0/1 0.0% 1/1 1.0% 114 73/114 0.6403508771929824%
Rafaela Dancygier 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 32 26/32 0.8125%
Richard F. Bensel 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 37 21/37 0.5675675675675675%
Robert Y. Shapiro 1 1/1 1.0% 0/1 0.0% 1/1 1.0% 125 69/125 0.552%
ROSE McDERMOTT 1 1/1 1.0% 0/1 0.0% 1/1 1.0% 145 102/145 0.7034482758620689%
Roxanne L. Euben 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 33 20/33 0.6060606060606061%
Russell Muirhead 1 1/1 1.0% 0/1 0.0% 1/1 1.0% 25 20/25 0.8%
Sarah E. Kreps 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 156 104/156 0.6666666666666666%
Sharon R. Krause 1 1/1 1.0% 0/1 0.0% 1/1 1.0% 33 28/33 0.8484848484848485%
Sharyn O’Halloran 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 42 27/42 0.6428571428571429%
Sonu Bedi 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 19 18/19 0.9473684210526315%
Stephen Daniel Ansolabehere 1 1/1 1.0% 0/1 0.0% 1/1 1.0% 84 78/84 0.9285714285714286%
Stephen Macedo 1 1/1 1.0% 0/1 0.0% 1/1 1.0% 69 49/69 0.7101449275362319%
Stephen Skowronek 1 1/1 1.0% 0/1 0.0% 1/1 1.0% 35 24/35 0.6857142857142857%
Steven I. Wilkinson 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 31 21/31 0.6774193548387096%
Steven Levitsky 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 107 90/107 0.8411214953271028%
Susan L. Moffitt 1 1/1 1.0% 0/1 0.0% 1/1 1.0% 18 18/18 1.0%
Suzanne Mettler 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 79 56/79 0.7088607594936709%
Taeku Lee 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 56 39/56 0.6964285714285714%
Tali Mendelberg 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 65 51/65 0.7846153846153846%
TARIQ THACHIL 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 20 17/20 0.85%
Theda Skocpol 1 1/1 1.0% 0/1 0.0% 1/1 1.0% 151 88/151 0.5827814569536424%
Thomas B. Pepinsky 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 152 92/152 0.6052631578947368%
Timothy M. Frye 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 64 50/64 0.78125%
Torben Iversen 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 67 61/67 0.9104477611940298%
Tulia G. Falleti 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 47 38/47 0.8085106382978723%
Virginia Page Fortna 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 20 16/20 0.8%
Wendy J. Schiller 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 37 20/37 0.5405405405405406%
William C. Wohlforth 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 102 76/102 0.7450980392156863%
Yuhua Wang 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 30 26/30 0.8666666666666667%
  • Over the academics these filters select, so a filtered page describes the academics it selected and not the whole department.
  • A row with nothing held draws no mark above: the graph is quiet there because the evidence is missing, not because the work is.
  • What there was to draw from, not what the graph divided by - the graph states its own denominator above.
  • A Scholar profile is attached when at least 3 of the CV titles are found on it, or 30% of them are; one at another institution or under a different name needs 10 titles, and a profile far larger than the CV that holds only a small part of it is refused. Its articles are then checked one by one: what is not a work, or not by this person, is not counted.

h-index

Academics at each h-index
Series: Academics.010203040505–9 Academics 5510–19 Academics 151520–39 Academics 373740+ Academics 42425–910–1920–3940+Academicsh-index

The verified Scholar profile’s h-index where there is one, else computed from the OpenAlex citations of the academic’s CV works (definitions section 6): Scholar for 75 academics, OpenAlex citations of CV works for 24, 1 with no h-index. Never OpenAlex’s author-level figure, and no filter here moves it.

What these filters select, over everything selected not what the graph divided by
Selected Academics CVScholarOpenAlex Works With a count
Everything selected 100 100/100 1.0% 75/100 0.75% 98/100 0.98% 9450 6426/9450 0.68%
  • Over the academics these filters select, so a filtered page describes the academics it selected and not the whole department.
  • A row with nothing held draws no mark above: the graph is quiet there because the evidence is missing, not because the work is.
  • What there was to draw from, not what the graph divided by - the graph states its own denominator above.
  • A Scholar profile is attached when at least 3 of the CV titles are found on it, or 30% of them are; one at another institution or under a different name needs 10 titles, and a profile far larger than the CV that holds only a small part of it is refused. Its articles are then checked one by one: what is not a work, or not by this person, is not counted.

Makeup by rank

Academics at each current rank
Series: value.DistinguishedDistinguished 100100020406080100RankAcademics

The current rank of every academic the filters keep (definitions section 7). A rank is current as of the CV, so no year window or publication type moves it.

What these filters select, over everything selected not what the graph divided by
Selected Academics CVScholarOpenAlex Works With a count
Everything selected 100 100/100 1.0% 75/100 0.75% 98/100 0.98% 9450 6426/9450 0.68%
  • Over the academics these filters select, so a filtered page describes the academics it selected and not the whole department.
  • A row with nothing held draws no mark above: the graph is quiet there because the evidence is missing, not because the work is.
  • What there was to draw from, not what the graph divided by - the graph states its own denominator above.
  • A Scholar profile is attached when at least 3 of the CV titles are found on it, or 30% of them are; one at another institution or under a different name needs 10 titles, and a profile far larger than the CV that holds only a small part of it is refused. Its articles are then checked one by one: what is not a work, or not by this person, is not counted.

Top collaborators

Works two of the selected academics both hold
Series: value.Alan S. Gerber · Gregory Alain HuberAlan S. Gerber · Gregory Alain Huber 5050Alan S. Gerber · Donald P. GreenAlan S. Gerber · Donald P. Green 4949James M. Snyder, Jr. · Stephen Daniel Ansolabehe…James M. Snyder, Jr. · Stephen Daniel Ansolabehe… 2525Douglas L. Kriner · Sarah E. KrepsDouglas L. Kriner · Sarah E. Kreps 1818Edward D. Mansfield · Helen V. MilnerEdward D. Mansfield · Helen V. Milner 1515Alan S. Gerber · Eric M. PatashnikAlan S. Gerber · Eric M. Patashnik 1414Dustin Tingley · Helen V. MilnerDustin Tingley · Helen V. Milner 1313Andrew Gelman · Gary KingAndrew Gelman · Gary King 1212Donald P. Green · Ian ShapiroDonald P. Green · Ian Shapiro 1111Edward D. Mansfield · Jack L. SnyderEdward D. Mansfield · Jack L. Snyder 1111Daniel Ziblatt · Steven LevitskyDaniel Ziblatt · Steven Levitsky 1010Brendan Nyhan · John Michael CareyBrendan Nyhan · John Michael Carey 99Diana C. Mutz · Edward D. MansfieldDiana C. Mutz · Edward D. Mansfield 55G. John Ikenberry · William C. WohlforthG. John Ikenberry · William C. Wohlforth 55Michael Horowitz · Sarah E. KrepsMichael Horowitz · Sarah E. Kreps 4401020304050PairShared works

The pairs of the 100 selected academics who share the most of these works. 324 of the 9,450 selected works are held by two of them, making 79 pairs - a work three of them share is three pairs, so the two figures are different quantities and neither is a sum of the other. Only collaborations inside this selection are here: a work written with somebody outside it is counted everywhere else on this page and cannot be paired.

What these filters select, over everything selected not what the graph divided by
Selected Academics CVScholarOpenAlex Works With a count
Everything selected 100 100/100 1.0% 75/100 0.75% 98/100 0.98% 9450 6426/9450 0.68%
  • Over the academics these filters select, so a filtered page describes the academics it selected and not the whole department.
  • A row with nothing held draws no mark above: the graph is quiet there because the evidence is missing, not because the work is.
  • What there was to draw from, not what the graph divided by - the graph states its own denominator above.
  • A Scholar profile is attached when at least 3 of the CV titles are found on it, or 30% of them are; one at another institution or under a different name needs 10 titles, and a profile far larger than the CV that holds only a small part of it is refused. Its articles are then checked one by one: what is not a work, or not by this person, is not counted.
First Second

Pick two academics to see how many of the selected works they share.