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

Citations by mean * log(1 + people)
1 Columbia Political Science 12 academics 58,304.3
2 Harvard Government 24 academics 42,215.3
3 Penn Political Science 15 academics 26,934.4
4 Dartmouth Government 7 academics 21,469.9
5 Yale Political Science 11 academics 20,982.6
6 Princeton Politics 13 academics 15,188.7
7 Cornell Government 6 academics 9,774.3
8 Brown Political Science 12 academics 6,771.7

1,005,105 citations over 5,617 of 8,387 works (67% 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

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% 2135 1565/2135 0.7330210772833724%
Penn Political Science 15 15/15 1.0% 14/15 0.9333333333333333% 15/15 1.0% 1089 730/1089 0.6703397612488522%
Princeton Politics 13 13/13 1.0% 9/13 0.6923076923076923% 12/13 0.9230769230769231% 731 531/731 0.7264021887824897%
Brown Political Science 12 12/12 1.0% 7/12 0.5833333333333334% 12/12 1.0% 641 433/641 0.6755070202808112%
Columbia Political Science 12 12/12 1.0% 8/12 0.6666666666666666% 12/12 1.0% 2174 1188/2174 0.546458141674333%
Yale Political Science 11 11/11 1.0% 10/11 0.9090909090909091% 11/11 1.0% 731 546/731 0.746922024623803%
Dartmouth Government 7 7/7 1.0% 6/7 0.8571428571428571% 7/7 1.0% 367 292/367 0.7956403269754768%
Cornell Government 6 6/6 1.0% 5/6 0.8333333333333334% 6/6 1.0% 519 332/519 0.6396917148362236%
  • 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

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% 2135 1565/2135 0.7330210772833724%
Penn Political Science 15 15/15 1.0% 14/15 0.9333333333333333% 15/15 1.0% 1089 730/1089 0.6703397612488522%
Princeton Politics 13 13/13 1.0% 9/13 0.6923076923076923% 12/13 0.9230769230769231% 731 531/731 0.7264021887824897%
Brown Political Science 12 12/12 1.0% 7/12 0.5833333333333334% 12/12 1.0% 641 433/641 0.6755070202808112%
Columbia Political Science 12 12/12 1.0% 8/12 0.6666666666666666% 12/12 1.0% 2174 1188/2174 0.546458141674333%
Yale Political Science 11 11/11 1.0% 10/11 0.9090909090909091% 11/11 1.0% 731 546/731 0.746922024623803%
Dartmouth Government 7 7/7 1.0% 6/7 0.8571428571428571% 7/7 1.0% 367 292/367 0.7956403269754768%
Cornell Government 6 6/6 1.0% 5/6 0.8333333333333334% 6/6 1.0% 519 332/519 0.6396917148362236%
  • 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% 2135 1565/2135 0.7330210772833724%
Penn Political Science 15 15/15 1.0% 14/15 0.9333333333333333% 15/15 1.0% 1089 730/1089 0.6703397612488522%
Princeton Politics 13 13/13 1.0% 9/13 0.6923076923076923% 12/13 0.9230769230769231% 731 531/731 0.7264021887824897%
Brown Political Science 12 12/12 1.0% 7/12 0.5833333333333334% 12/12 1.0% 641 433/641 0.6755070202808112%
Columbia Political Science 12 12/12 1.0% 8/12 0.6666666666666666% 12/12 1.0% 2174 1188/2174 0.546458141674333%
Yale Political Science 11 11/11 1.0% 10/11 0.9090909090909091% 11/11 1.0% 731 546/731 0.746922024623803%
Dartmouth Government 7 7/7 1.0% 6/7 0.8571428571428571% 7/7 1.0% 367 292/367 0.7956403269754768%
Cornell Government 6 6/6 1.0% 5/6 0.8333333333333334% 6/6 1.0% 519 332/519 0.6396917148362236%
  • 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

Citations by mean * log(1 + people) 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.0.010,000.020,000.030,000.040,000.050,000.060,000.0Distinguished Dartmouth Government over 7 academics 21,469.921,469.9Distinguished Harvard Government over 24 academics 42,215.342,215.3Distinguished Yale Political Science over 11 academics 20,982.620,982.6Distinguished Princeton Politics over 13 academics 14,020.314,020.3Distinguished Columbia Political Science over 12 academics 58,304.358,304.3Distinguished Cornell Government over 6 academics 9,774.39,774.3Distinguished Penn Political Science over 15 academics 26,934.426,934.4Distinguished Brown Political Science over 12 academics 6,771.76,771.7DistinguishedCitations by mean * log(1 + people)Rank

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% 2135 1565/2135 0.7330210772833724%
Penn Political Science 15 15/15 1.0% 14/15 0.9333333333333333% 15/15 1.0% 1089 730/1089 0.6703397612488522%
Princeton Politics 13 13/13 1.0% 9/13 0.6923076923076923% 12/13 0.9230769230769231% 731 531/731 0.7264021887824897%
Brown Political Science 12 12/12 1.0% 7/12 0.5833333333333334% 12/12 1.0% 641 433/641 0.6755070202808112%
Columbia Political Science 12 12/12 1.0% 8/12 0.6666666666666666% 12/12 1.0% 2174 1188/2174 0.546458141674333%
Yale Political Science 11 11/11 1.0% 10/11 0.9090909090909091% 11/11 1.0% 731 546/731 0.746922024623803%
Dartmouth Government 7 7/7 1.0% 6/7 0.8571428571428571% 7/7 1.0% 367 292/367 0.7956403269754768%
Cornell Government 6 6/6 1.0% 5/6 0.8333333333333334% 6/6 1.0% 519 332/519 0.6396917148362236%
  • 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.0500001000001500002000001 Dartmouth Government Brendan Nyhan 382251 Harvard Government Gary King 1031531 Yale Political Science Alan S. Gerber 243031 Princeton Politics Helen V. Milner 176321 Columbia Political Science Andrew Gelman 1531891 Cornell Government Sarah E. Kreps 86131 Penn Political Science Beth Simmons 233601 Brown Political Science Mark McGann Blyth 71422 Dartmouth Government William C. Wohlforth 108722 Harvard Government Peter A. Hall 420352 Yale Political Science Gregory Alain Huber 196472 Princeton Politics Carles Boix 124662 Columbia Political Science Donald P. Green 485622 Cornell Government Thomas B. Pepinsky 76572 Penn Political Science Amy Gutmann 200092 Brown Political Science ROSE McDERMOTT 68913 Dartmouth Government John Michael Carey 96923 Harvard Government Dustin Tingley 379223 Yale Political Science Nicholas Sambanis 147623 Princeton Politics G. John Ikenberry 83443 Columbia Political Science Andreas Wimmer 251783 Cornell Government Peter Joachim Katzenstein 49393 Penn Political Science Diana C. Mutz 193363 Brown Political Science Peter Andreas 44444 Dartmouth Government Jennifer Jerit 86664 Harvard Government James M. Snyder, Jr. 273814 Yale Political Science Jacob S. Hacker 79874 Princeton Politics Nolan McCarty 76204 Columbia Political Science Jack L. Snyder 75894 Cornell Government Suzanne Mettler 44174 Penn Political Science Edward D. Mansfield 173334 Brown Political Science Jeff D. Colgan 42185 Dartmouth Government Jason Lyall 39575 Harvard Government Steven Levitsky 236245 Yale Political Science Milan Svolik 77745 Princeton Politics Amaney A. Jamal 49815 Columbia Political Science Nadia Urbinati 70345 Cornell Government Douglas L. Kriner 43635 Penn Political Science Matthew Levendusky 160025 Brown Political Science Ashutosh Varshney 235812345CitationsRank

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% 46 0/46 0.0%
Adam Meirowitz 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 49 45/49 0.9183673469387755%
Alan S. Gerber 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 136 122/136 0.8970588235294118%
Amaney A. Jamal 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 91 68/91 0.7472527472527473%
Amy Gutmann 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 76 50/76 0.6578947368421053%
Andreas Wimmer 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 100 76/100 0.76%
Andrew Gelman 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 511 419/511 0.8199608610567515%
Andrew J. Nathan 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 713 116/713 0.16269284712482468%
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% 44 32/44 0.7272727272727273%
Atul Kohli 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 45 35/45 0.7777777777777778%
Beth Simmons 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 86 72/86 0.8372093023255814%
Brendan Nyhan 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 99 97/99 0.9797979797979798%
Brendan O'Leary 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 252 92/252 0.36507936507936506%
Carles Boix 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 50 44/50 0.88%
Christina L. Davis 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 33 24/33 0.7272727272727273%
Claudine Gay 1 1/1 1.0% 0/1 0.0% 1/1 1.0% 11 10/11 0.9090909090909091%
Daniel Gillion 1 1/1 1.0% 0/1 0.0% 1/1 1.0% 8 8/8 1.0%
Daniel J. Hopkins 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 68 67/68 0.9852941176470589%
Daniel Paul Carpenter 1 1/1 1.0% 1/1 1.0% 0/1 0.0% 137 92/137 0.6715328467153284%
Daniel Ziblatt 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 64 42/64 0.65625%
Danielle S. Allen 1 1/1 1.0% 0/1 0.0% 1/1 1.0% 37 20/37 0.5405405405405406%
David Skarbek 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 40 35/40 0.875%
Deborah J. Yashar 1 1/1 1.0% 0/1 0.0% 1/1 1.0% 15 7/15 0.4666666666666667%
Diana C. Mutz 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 76 62/76 0.8157894736842105%
Donald P. Green 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 226 203/226 0.8982300884955752%
Douglas L. Kriner 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 78 61/78 0.782051282051282%
Dustin Tingley 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 98 92/98 0.9387755102040817%
Edward D. Mansfield 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 97 78/97 0.8041237113402062%
Edward S. Steinfeld 1 1/1 1.0% 0/1 0.0% 1/1 1.0% 24 8/24 0.3333333333333333%
Elisabeth Jean Wood 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 39 32/39 0.8205128205128205%
Elizabeth J. Perry 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 101 50/101 0.49504950495049505%
Eric M. Patashnik 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 66 31/66 0.4696969696969697%
Eric Nelson 1 1/1 1.0% 0/1 0.0% 1/1 1.0% 18 15/18 0.8333333333333334%
Erik Wibbels 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 54 51/54 0.9444444444444444%
G. John Ikenberry 1 1/1 1.0% 0/1 0.0% 1/1 1.0% 98 70/98 0.7142857142857143%
Gary King 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 327 271/327 0.8287461773700305%
GERARD PADRÓ i MIQUEL 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 26 23/26 0.8846153846153846%
Gregory Alain Huber 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 118 112/118 0.9491525423728814%
Grzegorz Ekiert 1 1/1 1.0% 0/1 0.0% 1/1 1.0% 41 21/41 0.5121951219512195%
Guy Grossman 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 47 46/47 0.9787234042553191%
Helen V. Milner 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 112 96/112 0.8571428571428571%
Ian Shapiro 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 92 72/92 0.782608695652174%
Ira I. Katznelson 1 1/1 1.0% 0/1 0.0% 1/1 1.0% 84 47/84 0.5595238095238095%
Jack L. Snyder 1 1/1 1.0% 0/1 0.0% 1/1 1.0% 65 55/65 0.8461538461538461%
Jacob S. Hacker 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 188 85/188 0.4521276595744681%
James M. Snyder, Jr. 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 139 130/139 0.935251798561151%
Jason Lyall 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 19 19/19 1.0%
Jean Louise Cohen 1 1/1 1.0% 0/1 0.0% 1/1 1.0% 62 25/62 0.4032258064516129%
Jeff D. Colgan 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 63 43/63 0.6825396825396826%
Jennifer Hochschild 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 142 86/142 0.6056338028169014%
Jennifer Jerit 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 46 38/46 0.8260869565217391%
John Michael Carey 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 95 56/95 0.5894736842105263%
Joshua David Kertzer 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 52 44/52 0.8461538461538461%
Margaret M. Weir 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 44 32/44 0.7272727272727273%
Mark McGann Blyth 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 108 67/108 0.6203703703703703%
Matthew Levendusky 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 43 39/43 0.9069767441860465%
Melani Cammett 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 43 34/43 0.7906976744186046%
Melissa Schwartzberg 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 36 25/36 0.6944444444444444%
Michael Eric ROSEN 1 1/1 1.0% 0/1 0.0% 1/1 1.0% 21 17/21 0.8095238095238095%
Michael Horowitz 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 147 78/147 0.5306122448979592%
Michael J. Hiscox 1 1/1 1.0% 0/1 0.0% 1/1 1.0% 15 15/15 1.0%
Michael Jones-Correa 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 62 38/62 0.6129032258064516%
Milan Svolik 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 20 19/20 0.95%
Nadia Urbinati 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 194 106/194 0.5463917525773195%
Nicholas Sambanis 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 62 52/62 0.8387096774193549%
Nolan McCarty 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 64 43/64 0.671875%
Paul E. Peterson 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 351 231/351 0.6581196581196581%
Peter A. Hall 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 124 87/124 0.7016129032258065%
Peter Andreas 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 51 39/51 0.7647058823529411%
Peter Joachim Katzenstein 1 1/1 1.0% 0/1 0.0% 1/1 1.0% 79 49/79 0.620253164556962%
Rafaela Dancygier 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 28 22/28 0.7857142857142857%
Richard F. Bensel 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 30 15/30 0.5%
Robert Y. Shapiro 1 1/1 1.0% 0/1 0.0% 1/1 1.0% 110 62/110 0.5636363636363636%
ROSE McDERMOTT 1 1/1 1.0% 0/1 0.0% 1/1 1.0% 132 95/132 0.7196969696969697%
Roxanne L. Euben 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 29 16/29 0.5517241379310345%
Russell Muirhead 1 1/1 1.0% 0/1 0.0% 1/1 1.0% 21 18/21 0.8571428571428571%
Sarah E. Kreps 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 146 96/146 0.6575342465753424%
Sharon R. Krause 1 1/1 1.0% 0/1 0.0% 1/1 1.0% 26 23/26 0.8846153846153846%
Sharyn O’Halloran 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 38 23/38 0.6052631578947368%
Sonu Bedi 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 15 14/15 0.9333333333333333%
Stephen Daniel Ansolabehere 1 1/1 1.0% 0/1 0.0% 1/1 1.0% 79 74/79 0.9367088607594937%
Stephen Macedo 1 1/1 1.0% 0/1 0.0% 1/1 1.0% 44 35/44 0.7954545454545454%
Stephen Skowronek 1 1/1 1.0% 0/1 0.0% 1/1 1.0% 25 17/25 0.68%
Steven I. Wilkinson 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 27 17/27 0.6296296296296297%
Steven Levitsky 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 85 68/85 0.8%
Susan L. Moffitt 1 1/1 1.0% 0/1 0.0% 1/1 1.0% 15 15/15 1.0%
Suzanne Mettler 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 67 45/67 0.6716417910447762%
Taeku Lee 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 47 32/47 0.6808510638297872%
Tali Mendelberg 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 60 47/60 0.7833333333333333%
TARIQ THACHIL 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 16 14/16 0.875%
Theda Skocpol 1 1/1 1.0% 0/1 0.0% 1/1 1.0% 127 69/127 0.5433070866141733%
Thomas B. Pepinsky 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 139 85/139 0.6115107913669064%
Timothy M. Frye 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 57 44/57 0.7719298245614035%
Torben Iversen 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 56 53/56 0.9464285714285714%
Tulia G. Falleti 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 38 29/38 0.7631578947368421%
Virginia Page Fortna 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 16 14/16 0.875%
Wendy J. Schiller 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 28 13/28 0.4642857142857143%
William C. Wohlforth 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 81 59/81 0.7283950617283951%
Yuhua Wang 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 26 23/26 0.8846153846153846%
  • 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% 2135 1565/2135 0.7330210772833724%
Penn Political Science 15 15/15 1.0% 14/15 0.9333333333333333% 15/15 1.0% 1089 730/1089 0.6703397612488522%
Princeton Politics 13 13/13 1.0% 9/13 0.6923076923076923% 12/13 0.9230769230769231% 731 531/731 0.7264021887824897%
Brown Political Science 12 12/12 1.0% 7/12 0.5833333333333334% 12/12 1.0% 641 433/641 0.6755070202808112%
Columbia Political Science 12 12/12 1.0% 8/12 0.6666666666666666% 12/12 1.0% 2174 1188/2174 0.546458141674333%
Yale Political Science 11 11/11 1.0% 10/11 0.9090909090909091% 11/11 1.0% 731 546/731 0.746922024623803%
Dartmouth Government 7 7/7 1.0% 6/7 0.8571428571428571% 7/7 1.0% 367 292/367 0.7956403269754768%
Cornell Government 6 6/6 1.0% 5/6 0.8333333333333334% 6/6 1.0% 519 332/519 0.6396917148362236%
  • 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 599599American 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 132132PS Political Science & PoliticsPS Political Science & Politics 110110Public Opinion QuarterlyPublic Opinion Quarterly 8888World PoliticsWorld Politics 8686Political AnalysisPolitical Analysis 7979Comparative Political StudiesComparative Political Studies 7777Political Science QuarterlyPolitical Science Quarterly 7777Journal of democracyJournal of democracy 7272British Journal of Political ScienceBritish Journal of Political Science 70700100200300400500JournalWorks

The twelve venues highest on this reading, of 1,121.

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% 2135 1565/2135 0.7330210772833724%
Penn Political Science 15 15/15 1.0% 14/15 0.9333333333333333% 15/15 1.0% 1089 730/1089 0.6703397612488522%
Princeton Politics 13 13/13 1.0% 9/13 0.6923076923076923% 12/13 0.9230769230769231% 731 531/731 0.7264021887824897%
Brown Political Science 12 12/12 1.0% 7/12 0.5833333333333334% 12/12 1.0% 641 433/641 0.6755070202808112%
Columbia Political Science 12 12/12 1.0% 8/12 0.6666666666666666% 12/12 1.0% 2174 1188/2174 0.546458141674333%
Yale Political Science 11 11/11 1.0% 10/11 0.9090909090909091% 11/11 1.0% 731 546/731 0.746922024623803%
Dartmouth Government 7 7/7 1.0% 6/7 0.8571428571428571% 7/7 1.0% 367 292/367 0.7956403269754768%
Cornell Government 6 6/6 1.0% 5/6 0.8333333333333334% 6/6 1.0% 519 332/519 0.6396917148362236%
  • 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.