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

Academics

Departmentshere

  • 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.
Trackademia
Value Measure

Departments

Mean citations per academic
1 Dartmouth Government 7 academics 818
2 Brown Political Science 12 academics 590
3 Cornell Government 6 academics 406
4 Columbia Political Science 12 academics 358
5 Penn Political Science 15 academics 304
6 Harvard Government 24 academics 274
7 Princeton Politics 13 academics 176
8 Yale Political Science 11 academics 172

33,208 citations over 784 of 1,207 works (65% carry a count). 85 of 100 academics have at least one counted work. A work with no citation count is unknown here, never a zero.

Publications over time

Works published in each year
Measure X axis Each point

Dartmouth GovernmentHarvard GovernmentYale Political SciencePrinceton PoliticsColumbia Political ScienceCornell GovernmentPenn Political ScienceBrown Political Science

Every selected work, by the year it was published. An undated work is in no year.

What these filters select, per department not what the graph divided by
Department Academics CVScholarOpenAlex Works With a count
Harvard Government 24 24/24 1.0% 16/24 0.6666666666666666% 23/24 0.9583333333333334% 256 189/256 0.73828125%
Penn Political Science 15 15/15 1.0% 14/15 0.9333333333333333% 15/15 1.0% 197 117/197 0.5939086294416244%
Princeton Politics 13 13/13 1.0% 9/13 0.6923076923076923% 12/13 0.9230769230769231% 96 73/96 0.7604166666666666%
Brown Political Science 12 12/12 1.0% 7/12 0.5833333333333334% 12/12 1.0% 103 59/103 0.5728155339805825%
Columbia Political Science 12 12/12 1.0% 8/12 0.6666666666666666% 12/12 1.0% 279 141/279 0.5053763440860215%
Yale Political Science 11 11/11 1.0% 10/11 0.9090909090909091% 11/11 1.0% 96 79/96 0.8229166666666666%
Dartmouth Government 7 7/7 1.0% 6/7 0.8571428571428571% 7/7 1.0% 65 57/65 0.8769230769230769%
Cornell Government 6 6/6 1.0% 5/6 0.8333333333333334% 6/6 1.0% 115 69/115 0.6%
  • 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 over time

Citations received in each year
Value Measure Each point

Dartmouth GovernmentHarvard GovernmentYale Political SciencePrinceton PoliticsColumbia Political ScienceCornell GovernmentPenn Political ScienceBrown Political Science

Citations received in each year, from the academics’ verified Scholar profiles.

What these filters select, per department not what the graph divided by
Department Academics CVScholarOpenAlex Works With a count
Harvard Government 24 24/24 1.0% 16/24 0.6666666666666666% 23/24 0.9583333333333334% 256 189/256 0.73828125%
Penn Political Science 15 15/15 1.0% 14/15 0.9333333333333333% 15/15 1.0% 197 117/197 0.5939086294416244%
Princeton Politics 13 13/13 1.0% 9/13 0.6923076923076923% 12/13 0.9230769230769231% 96 73/96 0.7604166666666666%
Brown Political Science 12 12/12 1.0% 7/12 0.5833333333333334% 12/12 1.0% 103 59/103 0.5728155339805825%
Columbia Political Science 12 12/12 1.0% 8/12 0.6666666666666666% 12/12 1.0% 279 141/279 0.5053763440860215%
Yale Political Science 11 11/11 1.0% 10/11 0.9090909090909091% 11/11 1.0% 96 79/96 0.8229166666666666%
Dartmouth Government 7 7/7 1.0% 6/7 0.8571428571428571% 7/7 1.0% 65 57/65 0.8769230769230769%
Cornell Government 6 6/6 1.0% 5/6 0.8333333333333334% 6/6 1.0% 115 69/115 0.6%
  • 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 tenure track

Academics on and off the tenure track
Series: Tenure track.0510152025Dartmouth Tenure track 77Harvard Tenure track 2424Yale Tenure track 1111Princeton Tenure track 1313Columbia Tenure track 1212Cornell Tenure track 66Penn Tenure track 1515Brown Tenure track 1212DartmouthHarvardYalePrincetonColumbiaCornellPennBrownAcademicsDepartment

Every academic the filters keep, by whether their current rank is on the tenure track (docs/definitions.md section 7). A rank in neither group - emeritus, postdoc, or a rank no CV states - is its own segment rather than filed under one of them: an emeritus professor was on the tenure track, and an unknown rank is not a claim about tenure at all.

What these filters select, per department not what the graph divided by
Department Academics CVScholarOpenAlex Works With a count
Harvard Government 24 24/24 1.0% 16/24 0.6666666666666666% 23/24 0.9583333333333334% 256 189/256 0.73828125%
Penn Political Science 15 15/15 1.0% 14/15 0.9333333333333333% 15/15 1.0% 197 117/197 0.5939086294416244%
Princeton Politics 13 13/13 1.0% 9/13 0.6923076923076923% 12/13 0.9230769230769231% 96 73/96 0.7604166666666666%
Brown Political Science 12 12/12 1.0% 7/12 0.5833333333333334% 12/12 1.0% 103 59/103 0.5728155339805825%
Columbia Political Science 12 12/12 1.0% 8/12 0.6666666666666666% 12/12 1.0% 279 141/279 0.5053763440860215%
Yale Political Science 11 11/11 1.0% 10/11 0.9090909090909091% 11/11 1.0% 96 79/96 0.8229166666666666%
Dartmouth Government 7 7/7 1.0% 6/7 0.8571428571428571% 7/7 1.0% 65 57/65 0.8769230769230769%
Cornell Government 6 6/6 1.0% 5/6 0.8333333333333334% 6/6 1.0% 115 69/115 0.6%
  • 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.

Output by rank

Median citations per academic at each rank
Value Measure
Series: Dartmouth Government, Harvard Government, Yale Political Science, Princeton Politics, Columbia Political Science, Cornell Government, Penn Political Science, Brown Political Science.0.0100.0200.0300.0400.0500.0Distinguished Dartmouth Government over 7 academics 233.0233.0Distinguished Harvard Government over 24 academics 121.5121.5Distinguished Yale Political Science over 11 academics 172.0172.0Distinguished Princeton Politics over 13 academics 71.071.0Distinguished Columbia Political Science over 12 academics 89.589.5Distinguished Cornell Government over 6 academics 428.0428.0Distinguished Penn Political Science over 15 academics 110.0110.0Distinguished Brown Political Science over 12 academics 72.072.0DistinguishedMedian citations per academicRank

Dartmouth GovernmentHarvard GovernmentYale Political SciencePrinceton PoliticsColumbia Political ScienceCornell GovernmentPenn Political ScienceBrown Political Science

Each rank read on its own, so a department of thirty and one of sixty are comparable at the same career stage.

What these filters select, per department not what the graph divided by
Department Academics CVScholarOpenAlex Works With a count
Harvard Government 24 24/24 1.0% 16/24 0.6666666666666666% 23/24 0.9583333333333334% 256 189/256 0.73828125%
Penn Political Science 15 15/15 1.0% 14/15 0.9333333333333333% 15/15 1.0% 197 117/197 0.5939086294416244%
Princeton Politics 13 13/13 1.0% 9/13 0.6923076923076923% 12/13 0.9230769230769231% 96 73/96 0.7604166666666666%
Brown Political Science 12 12/12 1.0% 7/12 0.5833333333333334% 12/12 1.0% 103 59/103 0.5728155339805825%
Columbia Political Science 12 12/12 1.0% 8/12 0.6666666666666666% 12/12 1.0% 279 141/279 0.5053763440860215%
Yale Political Science 11 11/11 1.0% 10/11 0.9090909090909091% 11/11 1.0% 96 79/96 0.8229166666666666%
Dartmouth Government 7 7/7 1.0% 6/7 0.8571428571428571% 7/7 1.0% 65 57/65 0.8769230769230769%
Cornell Government 6 6/6 1.0% 5/6 0.8333333333333334% 6/6 1.0% 115 69/115 0.6%
  • 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.

Academics ranked against academics

Each department's rank-n academic, citations
Value Ranks
Series: Dartmouth Government, Harvard Government, Yale Political Science, Princeton Politics, Columbia Political Science, Cornell Government, Penn Political Science, Brown Political Science.010002000300040001 Dartmouth Government Brendan Nyhan 37871 Harvard Government Joshua David Kertzer 13021 Yale Political Science Gregory Alain Huber 4631 Princeton Politics Arthur Spirling 10151 Columbia Political Science Andrew Gelman 29501 Cornell Government Sarah E. Kreps 8911 Penn Political Science Matthew Levendusky 10541 Brown Political Science Eric M. Patashnik 34702 Dartmouth Government Jennifer Jerit 10302 Harvard Government Dustin Tingley 10842 Yale Political Science Nicholas Sambanis 2872 Princeton Politics Tali Mendelberg 4712 Columbia Political Science Donald P. Green 6892 Cornell Government Thomas B. Pepinsky 6612 Penn Political Science Guy Grossman 9632 Brown Political Science Peter Andreas 25773 Dartmouth Government John Michael Carey 5253 Harvard Government Steven Levitsky 6183 Yale Political Science Ian Shapiro 2373 Princeton Politics Rafaela Dancygier 2543 Columbia Political Science Nadia Urbinati 2603 Cornell Government Douglas L. Kriner 4853 Penn Political Science Michael Horowitz 8923 Brown Political Science Mark McGann Blyth 4144 Dartmouth Government William C. Wohlforth 2334 Harvard Government Gary King 6124 Yale Political Science Jacob S. Hacker 2134 Princeton Politics Amaney A. Jamal 1834 Columbia Political Science Andreas Wimmer 1214 Cornell Government Suzanne Mettler 3714 Penn Political Science Daniel J. Hopkins 7234 Brown Political Science ROSE McDERMOTT 2125 Dartmouth Government Jason Lyall 1345 Harvard Government Daniel Ziblatt 6035 Yale Political Science GERARD PADRÓ i MIQUEL 2005 Princeton Politics Helen V. Milner 1265 Columbia Political Science Andrew J. Nathan 935 Cornell Government Richard F. Bensel 175 Penn Political Science Beth Simmons 2265 Brown Political Science Jeff D. Colgan 20212345CitationsRank

Dartmouth GovernmentHarvard GovernmentYale Political SciencePrinceton PoliticsColumbia Political ScienceCornell GovernmentPenn Political ScienceBrown Political Science

Rank 5 of 24 at the deepest; 8 of 8 departments still have somebody at the last rank drawn. Rank n of one department is not otherwise related to rank n of another - what this compares is the shape of the lists.

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 —
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% 4 0/4 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% 17 14/17 0.8235294117647058%
Amaney A. Jamal 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 12 10/12 0.8333333333333334%
Amy Gutmann 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 4 1/4 0.25%
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% 76 67/76 0.881578947368421%
Andrew J. Nathan 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 110 13/110 0.11818181818181818%
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% 4 3/4 0.75%
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% 49 5/49 0.10204081632653061%
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% 7 6/7 0.8571428571428571%
Daniel J. Hopkins 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 20 20/20 1.0%
Daniel Paul Carpenter 1 1/1 1.0% 1/1 1.0% 0/1 0.0% 17 11/17 0.6470588235294118%
Daniel Ziblatt 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 20 11/20 0.55%
Danielle S. Allen 1 1/1 1.0% 0/1 0.0% 1/1 1.0% 11 8/11 0.7272727272727273%
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% 7 4/7 0.5714285714285714%
Donald P. Green 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 34 29/34 0.8529411764705882%
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% 14 12/14 0.8571428571428571%
Edward D. Mansfield 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 9 8/9 0.8888888888888888%
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% 5 4/5 0.8%
Eric M. Patashnik 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 13 9/13 0.6923076923076923%
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% 11 10/11 0.9090909090909091%
Gary King 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 38 31/38 0.8157894736842105%
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% 31 29/31 0.9354838709677419%
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% 14 11/14 0.7857142857142857%
Ian Shapiro 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 7 7/7 1.0%
Jacob S. Hacker 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 13 6/13 0.46153846153846156%
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% 8 4/8 0.5%
Jennifer Jerit 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 4 4/4 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% 16 15/16 0.9375%
Margaret M. Weir 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 5 2/5 0.4%
Mark McGann Blyth 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 20 10/20 0.5%
Matthew Levendusky 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 18 14/18 0.7777777777777778%
Melani Cammett 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 6 6/6 1.0%
Melissa Schwartzberg 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 7 5/7 0.7142857142857143%
Michael Eric ROSEN 1 1/1 1.0% 0/1 0.0% 1/1 1.0% 5 4/5 0.8%
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% 30 14/30 0.4666666666666667%
Nicholas Sambanis 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 13 12/13 0.9230769230769231%
Nolan McCarty 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 5 2/5 0.4%
Paul E. Peterson 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 36 19/36 0.5277777777777778%
Peter A. Hall 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 14 14/14 1.0%
Peter Andreas 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 3 2/3 0.6666666666666666%
Peter Joachim Katzenstein 1 1/1 1.0% 0/1 0.0% 1/1 1.0% 9 2/9 0.2222222222222222%
Rafaela Dancygier 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 10 8/10 0.8%
Richard F. Bensel 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 5 2/5 0.4%
ROSE McDERMOTT 1 1/1 1.0% 0/1 0.0% 1/1 1.0% 20 10/20 0.5%
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% 4 2/4 0.5%
Sarah E. Kreps 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 44 29/44 0.6590909090909091%
Sharon R. Krause 1 1/1 1.0% 0/1 0.0% 1/1 1.0% 6 4/6 0.6666666666666666%
Stephen Macedo 1 1/1 1.0% 0/1 0.0% 1/1 1.0% 2 1/2 0.5%
Steven Levitsky 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 21 13/21 0.6190476190476191%
Susan L. Moffitt 1 1/1 1.0% 0/1 0.0% 1/1 1.0% 5 5/5 1.0%
Suzanne Mettler 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 13 9/13 0.6923076923076923%
Taeku Lee 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 10 8/10 0.8%
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% 4 3/4 0.75%
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% 36 24/36 0.6666666666666666%
Timothy M. Frye 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 10 7/10 0.7%
Torben Iversen 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 9 6/9 0.6666666666666666%
Tulia G. Falleti 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 3 2/3 0.6666666666666666%
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% 5 3/5 0.6%
William C. Wohlforth 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 6 4/6 0.6666666666666666%
Yuhua Wang 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 11 9/11 0.8181818181818182%
  • 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.

Years to promotion

From the PhD to each rank
Series: Harvard Government, Brown Political Science.0.05.010.015.0Full or distinguished Harvard Government median of 1 academics 11.011.0Full or distinguished Brown Political Science median of 3 academics 13.013.0Full or distinguishedYears since the PhDRank reached

Harvard GovernmentBrown Political Science

The median years from the PhD year a CV states to the first year it states that rank. An academic whose CV dates neither is in neither figure.

What these filters select, per department not what the graph divided by
Department Academics CVScholarOpenAlex Works With a count
Harvard Government 24 24/24 1.0% 16/24 0.6666666666666666% 23/24 0.9583333333333334% 256 189/256 0.73828125%
Penn Political Science 15 15/15 1.0% 14/15 0.9333333333333333% 15/15 1.0% 197 117/197 0.5939086294416244%
Princeton Politics 13 13/13 1.0% 9/13 0.6923076923076923% 12/13 0.9230769230769231% 96 73/96 0.7604166666666666%
Brown Political Science 12 12/12 1.0% 7/12 0.5833333333333334% 12/12 1.0% 103 59/103 0.5728155339805825%
Columbia Political Science 12 12/12 1.0% 8/12 0.6666666666666666% 12/12 1.0% 279 141/279 0.5053763440860215%
Yale Political Science 11 11/11 1.0% 10/11 0.9090909090909091% 11/11 1.0% 96 79/96 0.8229166666666666%
Dartmouth Government 7 7/7 1.0% 6/7 0.8571428571428571% 7/7 1.0% 65 57/65 0.8769230769230769%
Cornell Government 6 6/6 1.0% 5/6 0.8333333333333334% 6/6 1.0% 115 69/115 0.6%
  • 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.

Journals used

Where these departments place work, by works
Value
Series: value.Foreign AffairsForeign Affairs 123123The Irish TimesThe Irish Times 4242The Journal of PoliticsThe Journal of Politics 3535American Journal of Political ScienceAmerican Journal of Political Science 2828Perspectives on PoliticsPerspectives on Politics 2727American Political Science ReviewAmerican Political Science Review 2323Journal of democracyJournal of democracy 1818Education nextEducation next 1717International OrganizationInternational Organization 1616Cambridge University Press eBooksCambridge University Press eBooks 1515British Journal of Political ScienceBritish Journal of Political Science 1515Princeton University Press eBooksPrinceton University Press eBooks 1414Proceedings of the National Academy of SciencesProceedings of the National Academy of Sciences 1313Comparative Political StudiesComparative Political Studies 1313ScienceScience 10100255075100JournalWorks

The twelve venues highest on this reading, of 313.

What these filters select, per department not what the graph divided by
Department Academics CVScholarOpenAlex Works With a count
Harvard Government 24 24/24 1.0% 16/24 0.6666666666666666% 23/24 0.9583333333333334% 256 189/256 0.73828125%
Penn Political Science 15 15/15 1.0% 14/15 0.9333333333333333% 15/15 1.0% 197 117/197 0.5939086294416244%
Princeton Politics 13 13/13 1.0% 9/13 0.6923076923076923% 12/13 0.9230769230769231% 96 73/96 0.7604166666666666%
Brown Political Science 12 12/12 1.0% 7/12 0.5833333333333334% 12/12 1.0% 103 59/103 0.5728155339805825%
Columbia Political Science 12 12/12 1.0% 8/12 0.6666666666666666% 12/12 1.0% 279 141/279 0.5053763440860215%
Yale Political Science 11 11/11 1.0% 10/11 0.9090909090909091% 11/11 1.0% 96 79/96 0.8229166666666666%
Dartmouth Government 7 7/7 1.0% 6/7 0.8571428571428571% 7/7 1.0% 65 57/65 0.8769230769230769%
Cornell Government 6 6/6 1.0% 5/6 0.8333333333333334% 6/6 1.0% 115 69/115 0.6%
  • 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.