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 Columbia Political Science 12 academics 33,048
2 Harvard Government 24 academics 17,553
3 Penn Political Science 15 academics 14,354
4 Yale Political Science 11 academics 12,450
5 Dartmouth Government 7 academics 12,447
6 Princeton Politics 13 academics 8,839
7 Cornell Government 6 academics 7,468
8 Brown Political Science 12 academics 4,500

1,446,319 citations over 6,596 of 9,638 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 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% 2458 1828/2458 0.7436940602115542%
Penn Political Science 15 15/15 1.0% 14/15 0.9333333333333333% 15/15 1.0% 1279 870/1279 0.6802189210320563%
Princeton Politics 13 13/13 1.0% 9/13 0.6923076923076923% 12/13 0.9230769230769231% 900 654/900 0.7266666666666667%
Brown Political Science 12 12/12 1.0% 7/12 0.5833333333333334% 12/12 1.0% 753 519/753 0.6892430278884463%
Columbia Political Science 12 12/12 1.0% 8/12 0.6666666666666666% 12/12 1.0% 2378 1341/2378 0.563919259882254%
Yale Political Science 11 11/11 1.0% 10/11 0.9090909090909091% 11/11 1.0% 861 665/861 0.7723577235772358%
Dartmouth Government 7 7/7 1.0% 6/7 0.8571428571428571% 7/7 1.0% 406 325/406 0.8004926108374384%
Cornell Government 6 6/6 1.0% 5/6 0.8333333333333334% 6/6 1.0% 603 394/603 0.6533996683250415%
  • 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% 2458 1828/2458 0.7436940602115542%
Penn Political Science 15 15/15 1.0% 14/15 0.9333333333333333% 15/15 1.0% 1279 870/1279 0.6802189210320563%
Princeton Politics 13 13/13 1.0% 9/13 0.6923076923076923% 12/13 0.9230769230769231% 900 654/900 0.7266666666666667%
Brown Political Science 12 12/12 1.0% 7/12 0.5833333333333334% 12/12 1.0% 753 519/753 0.6892430278884463%
Columbia Political Science 12 12/12 1.0% 8/12 0.6666666666666666% 12/12 1.0% 2378 1341/2378 0.563919259882254%
Yale Political Science 11 11/11 1.0% 10/11 0.9090909090909091% 11/11 1.0% 861 665/861 0.7723577235772358%
Dartmouth Government 7 7/7 1.0% 6/7 0.8571428571428571% 7/7 1.0% 406 325/406 0.8004926108374384%
Cornell Government 6 6/6 1.0% 5/6 0.8333333333333334% 6/6 1.0% 603 394/603 0.6533996683250415%
  • 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% 2458 1828/2458 0.7436940602115542%
Penn Political Science 15 15/15 1.0% 14/15 0.9333333333333333% 15/15 1.0% 1279 870/1279 0.6802189210320563%
Princeton Politics 13 13/13 1.0% 9/13 0.6923076923076923% 12/13 0.9230769230769231% 900 654/900 0.7266666666666667%
Brown Political Science 12 12/12 1.0% 7/12 0.5833333333333334% 12/12 1.0% 753 519/753 0.6892430278884463%
Columbia Political Science 12 12/12 1.0% 8/12 0.6666666666666666% 12/12 1.0% 2378 1341/2378 0.563919259882254%
Yale Political Science 11 11/11 1.0% 10/11 0.9090909090909091% 11/11 1.0% 861 665/861 0.7723577235772358%
Dartmouth Government 7 7/7 1.0% 6/7 0.8571428571428571% 7/7 1.0% 406 325/406 0.8004926108374384%
Cornell Government 6 6/6 1.0% 5/6 0.8333333333333334% 6/6 1.0% 603 394/603 0.6533996683250415%
  • 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.0.02,000.04,000.06,000.08,000.010,000.012,000.0Distinguished Dartmouth Government over 7 academics 9,585.09,585.0Distinguished Harvard Government over 24 academics 6,659.56,659.5Distinguished Yale Political Science over 11 academics 11,476.011,476.0Distinguished Princeton Politics over 13 academics 7,545.07,545.0Distinguished Columbia Political Science over 12 academics 9,700.59,700.5Distinguished Cornell Government over 6 academics 8,687.08,687.0Distinguished Penn Political Science over 15 academics 9,047.09,047.0Distinguished Brown Political Science over 12 academics 2,984.02,984.0DistinguishedMedian 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% 2458 1828/2458 0.7436940602115542%
Penn Political Science 15 15/15 1.0% 14/15 0.9333333333333333% 15/15 1.0% 1279 870/1279 0.6802189210320563%
Princeton Politics 13 13/13 1.0% 9/13 0.6923076923076923% 12/13 0.9230769230769231% 900 654/900 0.7266666666666667%
Brown Political Science 12 12/12 1.0% 7/12 0.5833333333333334% 12/12 1.0% 753 519/753 0.6892430278884463%
Columbia Political Science 12 12/12 1.0% 8/12 0.6666666666666666% 12/12 1.0% 2378 1341/2378 0.563919259882254%
Yale Political Science 11 11/11 1.0% 10/11 0.9090909090909091% 11/11 1.0% 861 665/861 0.7723577235772358%
Dartmouth Government 7 7/7 1.0% 6/7 0.8571428571428571% 7/7 1.0% 406 325/406 0.8004926108374384%
Cornell Government 6 6/6 1.0% 5/6 0.8333333333333334% 6/6 1.0% 603 394/603 0.6533996683250415%
  • 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.0500001000001500002000002500001 Dartmouth Government Brendan Nyhan 383681 Harvard Government Gary King 1225071 Yale Political Science Alan S. Gerber 286411 Princeton Politics Helen V. Milner 269531 Columbia Political Science Andrew Gelman 2333901 Cornell Government Peter Joachim Katzenstein 100831 Penn Political Science Amy Gutmann 521671 Brown Political Science Mark McGann Blyth 133942 Dartmouth Government John Michael Carey 186322 Harvard Government Peter A. Hall 588752 Yale Political Science Nicholas Sambanis 205242 Princeton Politics Carles Boix 203022 Columbia Political Science Donald P. Green 612502 Cornell Government Sarah E. Kreps 94562 Penn Political Science Beth Simmons 295662 Brown Political Science Peter Andreas 103683 Dartmouth Government William C. Wohlforth 150153 Harvard Government Dustin Tingley 385893 Yale Political Science Gregory Alain Huber 196763 Princeton Politics Nolan McCarty 141303 Columbia Political Science Andreas Wimmer 305063 Cornell Government Suzanne Mettler 87253 Penn Political Science Diana C. Mutz 263203 Brown Political Science ROSE McDERMOTT 80564 Dartmouth Government Jennifer Jerit 95854 Harvard Government Steven Levitsky 382194 Yale Political Science Jacob S. Hacker 175254 Princeton Politics G. John Ikenberry 117414 Columbia Political Science Nadia Urbinati 129494 Cornell Government Thomas B. Pepinsky 86494 Penn Political Science Edward D. Mansfield 221744 Brown Political Science Eric M. Patashnik 57185 Dartmouth Government Jason Lyall 41565 Harvard Government James M. Snyder, Jr. 277345 Yale Political Science Ian Shapiro 154055 Princeton Politics Atul Kohli 114845 Columbia Political Science Jack L. Snyder 118335 Cornell Government Douglas L. Kriner 51675 Penn Political Science Matthew Levendusky 201385 Brown Political Science Jeff D. Colgan 469612345CitationsRank

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
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.

Years to promotion

From the PhD to each rank
Series: Dartmouth Government, Harvard Government, Yale Political Science, Princeton Politics, Columbia Political Science, Cornell Government, Penn Political Science, Brown Political Science.0.05.010.015.0Associate Dartmouth Government median of 5 academics 7.07.0Associate Harvard Government median of 20 academics 5.05.0Associate Yale Political Science median of 8 academics 5.05.0Associate Princeton Politics median of 11 academics 6.06.0Associate Columbia Political Science median of 8 academics 5.05.0Associate Cornell Government median of 5 academics 6.06.0Associate Penn Political Science median of 14 academics 6.06.0Associate Brown Political Science median of 10 academics 6.06.0Full or distinguished Dartmouth Government median of 7 academics 13.013.0Full or distinguished Harvard Government median of 21 academics 8.08.0Full or distinguished Yale Political Science median of 9 academics 7.07.0Full or distinguished Princeton Politics median of 12 academics 10.510.5Full or distinguished Columbia Political Science median of 10 academics 9.59.5Full or distinguished Cornell Government median of 5 academics 12.012.0Full or distinguished Penn Political Science median of 15 academics 11.011.0Full or distinguished Brown Political Science median of 10 academics 13.013.0AssociateFull or distinguishedYears since the PhDRank reached

Dartmouth GovernmentHarvard GovernmentYale Political SciencePrinceton PoliticsColumbia Political ScienceCornell GovernmentPenn Political ScienceBrown 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% 2458 1828/2458 0.7436940602115542%
Penn Political Science 15 15/15 1.0% 14/15 0.9333333333333333% 15/15 1.0% 1279 870/1279 0.6802189210320563%
Princeton Politics 13 13/13 1.0% 9/13 0.6923076923076923% 12/13 0.9230769230769231% 900 654/900 0.7266666666666667%
Brown Political Science 12 12/12 1.0% 7/12 0.5833333333333334% 12/12 1.0% 753 519/753 0.6892430278884463%
Columbia Political Science 12 12/12 1.0% 8/12 0.6666666666666666% 12/12 1.0% 2378 1341/2378 0.563919259882254%
Yale Political Science 11 11/11 1.0% 10/11 0.9090909090909091% 11/11 1.0% 861 665/861 0.7723577235772358%
Dartmouth Government 7 7/7 1.0% 6/7 0.8571428571428571% 7/7 1.0% 406 325/406 0.8004926108374384%
Cornell Government 6 6/6 1.0% 5/6 0.8333333333333334% 6/6 1.0% 603 394/603 0.6533996683250415%
  • 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 616616American Political Science ReviewAmerican Political Science Review 199199American Journal of Political ScienceAmerican Journal of Political Science 191191Perspectives on PoliticsPerspectives on Politics 189189The Journal of PoliticsThe Journal of Politics 160160Education nextEducation next 141141International OrganizationInternational Organization 133133PS Political Science & PoliticsPS Political Science & Politics 110110Cambridge University Press eBooksCambridge University Press eBooks 108108Public Opinion QuarterlyPublic Opinion Quarterly 8989World PoliticsWorld Politics 8686Comparative Political StudiesComparative Political Studies 8181Political AnalysisPolitical Analysis 7979Political Science QuarterlyPolitical Science Quarterly 7878Princeton University Press eBooksPrinceton University Press eBooks 74740250500JournalWorks

The twelve venues highest on this reading, of 1,187.

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% 2458 1828/2458 0.7436940602115542%
Penn Political Science 15 15/15 1.0% 14/15 0.9333333333333333% 15/15 1.0% 1279 870/1279 0.6802189210320563%
Princeton Politics 13 13/13 1.0% 9/13 0.6923076923076923% 12/13 0.9230769230769231% 900 654/900 0.7266666666666667%
Brown Political Science 12 12/12 1.0% 7/12 0.5833333333333334% 12/12 1.0% 753 519/753 0.6892430278884463%
Columbia Political Science 12 12/12 1.0% 8/12 0.6666666666666666% 12/12 1.0% 2378 1341/2378 0.563919259882254%
Yale Political Science 11 11/11 1.0% 10/11 0.9090909090909091% 11/11 1.0% 861 665/861 0.7723577235772358%
Dartmouth Government 7 7/7 1.0% 6/7 0.8571428571428571% 7/7 1.0% 406 325/406 0.8004926108374384%
Cornell Government 6 6/6 1.0% 5/6 0.8333333333333334% 6/6 1.0% 603 394/603 0.6533996683250415%
  • 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.