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 Brendan Nyhan Dartmouth Government · Distinguished · 15 years in post 252.5
2 Joshua David Kertzer Harvard Government · Distinguished · 12 years in post 103.2
3 Guy Grossman Penn Political Science · Distinguished · 14 years in post 68.8
4 Andrew Gelman Columbia Political Science · Distinguished · 36 years in post 60.8
5 Dustin Tingley Harvard Government · Distinguished · 16 years in post 58.6
6 Arthur Spirling Princeton Politics · Distinguished · 18 years in post 56.4
7 Sarah E. Kreps Cornell Government · Distinguished · 18 years in post 49.4
8 Michael Horowitz Penn Political Science · Distinguished · 19 years in post 46.9
9 Matthew Levendusky Penn Political Science · Distinguished · 19 years in post 42.2
10 Daniel J. Hopkins Penn Political Science · Distinguished · 17 years in post 40.8
11 Thomas B. Pepinsky Cornell Government · Distinguished · 19 years in post 24.7
12 Douglas L. Kriner Cornell Government · Distinguished · 20 years in post 24.2
13 Yuhua Wang Harvard Government · Distinguished · 15 years in post 21.2
14 Gregory Alain Huber Yale Political Science · Distinguished · 25 years in post 18.3
15 Donald P. Green Columbia Political Science · Distinguished · 37 years in post 18.1

22,409 citations over 688 of 1,077 works (64% carry a count). 83 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% 1077 688/1077 0.6388115134633241%
  • 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% 1077 688/1077 0.6388115134633241%
  • 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
Claudine Gay 1 1/1 1.0% 0/1 0.0% 1/1 1.0% 0
Daniel Gillion 1 1/1 1.0% 0/1 0.0% 1/1 1.0% 0
G. John Ikenberry 1 1/1 1.0% 0/1 0.0% 1/1 1.0% 0
Ira I. Katznelson 1 1/1 1.0% 0/1 0.0% 1/1 1.0% 0
Jean Louise Cohen 1 1/1 1.0% 0/1 0.0% 1/1 1.0% 0
Michael J. Hiscox 1 1/1 1.0% 0/1 0.0% 1/1 1.0% 0
Robert Y. Shapiro 1 1/1 1.0% 0/1 0.0% 1/1 1.0% 0
Sonu Bedi 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 0
Stephen Daniel Ansolabehere 1 1/1 1.0% 0/1 0.0% 1/1 1.0% 0
Stephen Skowronek 1 1/1 1.0% 0/1 0.0% 1/1 1.0% 0
Amy Gutmann 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 1 0/1 0.0%
Edward S. Steinfeld 1 1/1 1.0% 0/1 0.0% 1/1 1.0% 1 0/1 0.0%
Jack L. Snyder 1 1/1 1.0% 0/1 0.0% 1/1 1.0% 1 0/1 0.0%
Melissa Sharon Lane 1 1/1 1.0% 0/1 0.0% 0/1 0.0% 3 0/3 0.0%
Peter Andreas 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 1 0/1 0.0%
Sharyn O’Halloran 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 1 0/1 0.0%
Steven I. Wilkinson 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 2 0/2 0.0%
Adam Meirowitz 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 4 4/4 1.0%
Alan S. Gerber 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 16 13/16 0.8125%
Amaney A. Jamal 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 9 8/9 0.8888888888888888%
Andreas Wimmer 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 14 8/14 0.5714285714285714%
Andrew Gelman 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 72 63/72 0.875%
Andrew J. Nathan 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 108 11/108 0.10185185185185185%
Arthur Spirling 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 11 10/11 0.9090909090909091%
Ashutosh Varshney 1 1/1 1.0% 0/1 0.0% 1/1 1.0% 2 2/2 1.0%
Atul Kohli 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 3 2/3 0.6666666666666666%
Beth Simmons 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 14 11/14 0.7857142857142857%
Brendan Nyhan 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 40 38/40 0.95%
Brendan O'Leary 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 48 4/48 0.08333333333333333%
Carles Boix 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 8 8/8 1.0%
Christina L. Davis 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 6 5/6 0.8333333333333334%
Daniel J. Hopkins 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 19 19/19 1.0%
Daniel Paul Carpenter 1 1/1 1.0% 1/1 1.0% 0/1 0.0% 16 11/16 0.6875%
Daniel Ziblatt 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 18 9/18 0.5%
Danielle S. Allen 1 1/1 1.0% 0/1 0.0% 1/1 1.0% 9 7/9 0.7777777777777778%
David Skarbek 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 4 4/4 1.0%
Deborah J. Yashar 1 1/1 1.0% 0/1 0.0% 1/1 1.0% 3 1/3 0.3333333333333333%
Diana C. Mutz 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 6 4/6 0.6666666666666666%
Donald P. Green 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 32 27/32 0.84375%
Douglas L. Kriner 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 19 14/19 0.7368421052631579%
Dustin Tingley 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 13 11/13 0.8461538461538461%
Edward D. Mansfield 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 7 7/7 1.0%
Elisabeth Jean Wood 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 8 6/8 0.75%
Elizabeth J. Perry 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 3 2/3 0.6666666666666666%
Eric M. Patashnik 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 9 7/9 0.7777777777777778%
Eric Nelson 1 1/1 1.0% 0/1 0.0% 1/1 1.0% 3 1/3 0.3333333333333333%
Erik Wibbels 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 10 10/10 1.0%
Gary King 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 27 22/27 0.8148148148148148%
GERARD PADRÓ i MIQUEL 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 9 8/9 0.8888888888888888%
Gregory Alain Huber 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 30 28/30 0.9333333333333333%
Grzegorz Ekiert 1 1/1 1.0% 0/1 0.0% 1/1 1.0% 2 2/2 1.0%
Guy Grossman 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 15 15/15 1.0%
Helen V. Milner 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 13 10/13 0.7692307692307693%
Ian Shapiro 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 4 4/4 1.0%
Jacob S. Hacker 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 12 5/12 0.4166666666666667%
James M. Snyder, Jr. 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 8 8/8 1.0%
Jason Lyall 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 5 5/5 1.0%
Jeff D. Colgan 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 19 8/19 0.42105263157894735%
Jennifer Hochschild 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 7 3/7 0.42857142857142855%
Jennifer Jerit 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 3 3/3 1.0%
John Michael Carey 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 12 10/12 0.8333333333333334%
Joshua David Kertzer 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 15 14/15 0.9333333333333333%
Margaret M. Weir 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 3 1/3 0.3333333333333333%
Mark McGann Blyth 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 18 8/18 0.4444444444444444%
Matthew Levendusky 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 15 11/15 0.7333333333333333%
Melani Cammett 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 5 5/5 1.0%
Melissa Schwartzberg 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 5 3/5 0.6%
Michael Eric ROSEN 1 1/1 1.0% 0/1 0.0% 1/1 1.0% 4 3/4 0.75%
Michael Horowitz 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 40 22/40 0.55%
Michael Jones-Correa 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 4 3/4 0.75%
Milan Svolik 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 2 2/2 1.0%
Nadia Urbinati 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 25 10/25 0.4%
Nicholas Sambanis 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 12 11/12 0.9166666666666666%
Nolan McCarty 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 4 2/4 0.5%
Paul E. Peterson 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 33 17/33 0.5151515151515151%
Peter A. Hall 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 8 8/8 1.0%
Peter Joachim Katzenstein 1 1/1 1.0% 0/1 0.0% 1/1 1.0% 6 2/6 0.3333333333333333%
Rafaela Dancygier 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 9 7/9 0.7777777777777778%
Richard F. Bensel 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 4 1/4 0.25%
ROSE McDERMOTT 1 1/1 1.0% 0/1 0.0% 1/1 1.0% 19 10/19 0.5263157894736842%
Roxanne L. Euben 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 1 1/1 1.0%
Russell Muirhead 1 1/1 1.0% 0/1 0.0% 1/1 1.0% 3 2/3 0.6666666666666666%
Sarah E. Kreps 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 40 27/40 0.675%
Sharon R. Krause 1 1/1 1.0% 0/1 0.0% 1/1 1.0% 3 2/3 0.6666666666666666%
Stephen Macedo 1 1/1 1.0% 0/1 0.0% 1/1 1.0% 1 1/1 1.0%
Steven Levitsky 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 18 10/18 0.5555555555555556%
Susan L. Moffitt 1 1/1 1.0% 0/1 0.0% 1/1 1.0% 4 4/4 1.0%
Suzanne Mettler 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 12 8/12 0.6666666666666666%
Taeku Lee 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 8 6/8 0.75%
Tali Mendelberg 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 18 16/18 0.8888888888888888%
TARIQ THACHIL 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 2 2/2 1.0%
Theda Skocpol 1 1/1 1.0% 0/1 0.0% 1/1 1.0% 2 2/2 1.0%
Thomas B. Pepinsky 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 32 22/32 0.6875%
Timothy M. Frye 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 9 6/9 0.6666666666666666%
Torben Iversen 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 5 5/5 1.0%
Tulia G. Falleti 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 2 1/2 0.5%
Virginia Page Fortna 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 3 3/3 1.0%
Wendy J. Schiller 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 3 2/3 0.6666666666666666%
William C. Wohlforth 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 4 2/4 0.5%
Yuhua Wang 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 9 7/9 0.7777777777777778%
  • 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
Claudine Gay 1 1/1 1.0% 0/1 0.0% 1/1 1.0% 0
Daniel Gillion 1 1/1 1.0% 0/1 0.0% 1/1 1.0% 0
G. John Ikenberry 1 1/1 1.0% 0/1 0.0% 1/1 1.0% 0
Ira I. Katznelson 1 1/1 1.0% 0/1 0.0% 1/1 1.0% 0
Jean Louise Cohen 1 1/1 1.0% 0/1 0.0% 1/1 1.0% 0
Michael J. Hiscox 1 1/1 1.0% 0/1 0.0% 1/1 1.0% 0
Robert Y. Shapiro 1 1/1 1.0% 0/1 0.0% 1/1 1.0% 0
Sonu Bedi 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 0
Stephen Daniel Ansolabehere 1 1/1 1.0% 0/1 0.0% 1/1 1.0% 0
Stephen Skowronek 1 1/1 1.0% 0/1 0.0% 1/1 1.0% 0
Amy Gutmann 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 1 0/1 0.0%
Edward S. Steinfeld 1 1/1 1.0% 0/1 0.0% 1/1 1.0% 1 0/1 0.0%
Jack L. Snyder 1 1/1 1.0% 0/1 0.0% 1/1 1.0% 1 0/1 0.0%
Melissa Sharon Lane 1 1/1 1.0% 0/1 0.0% 0/1 0.0% 3 0/3 0.0%
Peter Andreas 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 1 0/1 0.0%
Sharyn O’Halloran 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 1 0/1 0.0%
Steven I. Wilkinson 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 2 0/2 0.0%
Adam Meirowitz 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 4 4/4 1.0%
Alan S. Gerber 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 16 13/16 0.8125%
Amaney A. Jamal 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 9 8/9 0.8888888888888888%
Andreas Wimmer 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 14 8/14 0.5714285714285714%
Andrew Gelman 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 72 63/72 0.875%
Andrew J. Nathan 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 108 11/108 0.10185185185185185%
Arthur Spirling 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 11 10/11 0.9090909090909091%
Ashutosh Varshney 1 1/1 1.0% 0/1 0.0% 1/1 1.0% 2 2/2 1.0%
Atul Kohli 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 3 2/3 0.6666666666666666%
Beth Simmons 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 14 11/14 0.7857142857142857%
Brendan Nyhan 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 40 38/40 0.95%
Brendan O'Leary 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 48 4/48 0.08333333333333333%
Carles Boix 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 8 8/8 1.0%
Christina L. Davis 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 6 5/6 0.8333333333333334%
Daniel J. Hopkins 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 19 19/19 1.0%
Daniel Paul Carpenter 1 1/1 1.0% 1/1 1.0% 0/1 0.0% 16 11/16 0.6875%
Daniel Ziblatt 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 18 9/18 0.5%
Danielle S. Allen 1 1/1 1.0% 0/1 0.0% 1/1 1.0% 9 7/9 0.7777777777777778%
David Skarbek 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 4 4/4 1.0%
Deborah J. Yashar 1 1/1 1.0% 0/1 0.0% 1/1 1.0% 3 1/3 0.3333333333333333%
Diana C. Mutz 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 6 4/6 0.6666666666666666%
Donald P. Green 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 32 27/32 0.84375%
Douglas L. Kriner 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 19 14/19 0.7368421052631579%
Dustin Tingley 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 13 11/13 0.8461538461538461%
Edward D. Mansfield 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 7 7/7 1.0%
Elisabeth Jean Wood 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 8 6/8 0.75%
Elizabeth J. Perry 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 3 2/3 0.6666666666666666%
Eric M. Patashnik 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 9 7/9 0.7777777777777778%
Eric Nelson 1 1/1 1.0% 0/1 0.0% 1/1 1.0% 3 1/3 0.3333333333333333%
Erik Wibbels 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 10 10/10 1.0%
Gary King 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 27 22/27 0.8148148148148148%
GERARD PADRÓ i MIQUEL 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 9 8/9 0.8888888888888888%
Gregory Alain Huber 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 30 28/30 0.9333333333333333%
Grzegorz Ekiert 1 1/1 1.0% 0/1 0.0% 1/1 1.0% 2 2/2 1.0%
Guy Grossman 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 15 15/15 1.0%
Helen V. Milner 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 13 10/13 0.7692307692307693%
Ian Shapiro 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 4 4/4 1.0%
Jacob S. Hacker 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 12 5/12 0.4166666666666667%
James M. Snyder, Jr. 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 8 8/8 1.0%
Jason Lyall 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 5 5/5 1.0%
Jeff D. Colgan 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 19 8/19 0.42105263157894735%
Jennifer Hochschild 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 7 3/7 0.42857142857142855%
Jennifer Jerit 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 3 3/3 1.0%
John Michael Carey 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 12 10/12 0.8333333333333334%
Joshua David Kertzer 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 15 14/15 0.9333333333333333%
Margaret M. Weir 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 3 1/3 0.3333333333333333%
Mark McGann Blyth 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 18 8/18 0.4444444444444444%
Matthew Levendusky 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 15 11/15 0.7333333333333333%
Melani Cammett 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 5 5/5 1.0%
Melissa Schwartzberg 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 5 3/5 0.6%
Michael Eric ROSEN 1 1/1 1.0% 0/1 0.0% 1/1 1.0% 4 3/4 0.75%
Michael Horowitz 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 40 22/40 0.55%
Michael Jones-Correa 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 4 3/4 0.75%
Milan Svolik 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 2 2/2 1.0%
Nadia Urbinati 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 25 10/25 0.4%
Nicholas Sambanis 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 12 11/12 0.9166666666666666%
Nolan McCarty 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 4 2/4 0.5%
Paul E. Peterson 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 33 17/33 0.5151515151515151%
Peter A. Hall 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 8 8/8 1.0%
Peter Joachim Katzenstein 1 1/1 1.0% 0/1 0.0% 1/1 1.0% 6 2/6 0.3333333333333333%
Rafaela Dancygier 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 9 7/9 0.7777777777777778%
Richard F. Bensel 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 4 1/4 0.25%
ROSE McDERMOTT 1 1/1 1.0% 0/1 0.0% 1/1 1.0% 19 10/19 0.5263157894736842%
Roxanne L. Euben 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 1 1/1 1.0%
Russell Muirhead 1 1/1 1.0% 0/1 0.0% 1/1 1.0% 3 2/3 0.6666666666666666%
Sarah E. Kreps 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 40 27/40 0.675%
Sharon R. Krause 1 1/1 1.0% 0/1 0.0% 1/1 1.0% 3 2/3 0.6666666666666666%
Stephen Macedo 1 1/1 1.0% 0/1 0.0% 1/1 1.0% 1 1/1 1.0%
Steven Levitsky 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 18 10/18 0.5555555555555556%
Susan L. Moffitt 1 1/1 1.0% 0/1 0.0% 1/1 1.0% 4 4/4 1.0%
Suzanne Mettler 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 12 8/12 0.6666666666666666%
Taeku Lee 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 8 6/8 0.75%
Tali Mendelberg 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 18 16/18 0.8888888888888888%
TARIQ THACHIL 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 2 2/2 1.0%
Theda Skocpol 1 1/1 1.0% 0/1 0.0% 1/1 1.0% 2 2/2 1.0%
Thomas B. Pepinsky 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 32 22/32 0.6875%
Timothy M. Frye 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 9 6/9 0.6666666666666666%
Torben Iversen 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 5 5/5 1.0%
Tulia G. Falleti 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 2 1/2 0.5%
Virginia Page Fortna 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 3 3/3 1.0%
Wendy J. Schiller 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 3 2/3 0.6666666666666666%
William C. Wohlforth 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 4 2/4 0.5%
Yuhua Wang 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 9 7/9 0.7777777777777778%
  • 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% 1077 688/1077 0.6388115134633241%
  • 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% 1077 688/1077 0.6388115134633241%
  • 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 1010Douglas L. Kriner · Sarah E. KrepsDouglas L. Kriner · Sarah E. Kreps 1010Brendan Nyhan · John Michael CareyBrendan Nyhan · John Michael Carey 66Daniel Ziblatt · Steven LevitskyDaniel Ziblatt · Steven Levitsky 55Alan S. Gerber · Eric M. PatashnikAlan S. Gerber · Eric M. Patashnik 33Amaney A. Jamal · Rafaela DancygierAmaney A. Jamal · Rafaela Dancygier 11Arthur Spirling · Melissa SchwartzbergArthur Spirling · Melissa Schwartzberg 11Beth Simmons · Diana C. MutzBeth Simmons · Diana C. Mutz 11Brendan Nyhan · Matthew LevenduskyBrendan Nyhan · Matthew Levendusky 11Brendan Nyhan · Thomas B. PepinskyBrendan Nyhan · Thomas B. Pepinsky 11Dustin Tingley · Joshua David KertzerDustin Tingley · Joshua David Kertzer 11Guy Grossman · Matthew LevenduskyGuy Grossman · Matthew Levendusky 11Michael Horowitz · Sarah E. KrepsMichael Horowitz · Sarah E. Kreps 11Suzanne Mettler · Thomas B. PepinskySuzanne Mettler · Thomas B. Pepinsky 110246810PairShared works

The pairs of the 100 selected academics who share the most of these works. 43 of the 1,077 selected works are held by two of them, making 14 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% 1077 688/1077 0.6388115134633241%
  • 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.