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.

Value Measure

Departments

Mean citations per academic
1 Harvard Government 34 academics 11,226
2 Columbia Political Science 35 academics 9,221
3 Penn Political Science 33 academics 5,105
4 Dartmouth Government 28 academics 4,219
5 Princeton Politics 47 academics 4,074
6 Yale Political Science 34 academics 3,839
7 Cornell Government 31 academics 2,012
8 Brown Political Science 27 academics 1,914

1,349,170 citations over 8,919 of 12,603 works (71% carry a count). 268 of 269 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
Princeton Politics 47 47/47 1.0% 38/47 0.8085106382978723% 45/47 0.9574468085106383% 1629 1266/1629 0.7771639042357275%
Columbia Political Science 35 35/35 1.0% 24/35 0.6857142857142857% 35/35 1.0% 2756 1665/2756 0.6041364296081277%
Harvard Government 34 34/34 1.0% 26/34 0.7647058823529411% 33/34 0.9705882352941176% 2415 1800/2415 0.7453416149068323%
Yale Political Science 34 34/34 1.0% 32/34 0.9411764705882353% 33/34 0.9705882352941176% 1130 885/1130 0.7831858407079646%
Penn Political Science 33 33/33 1.0% 28/33 0.8484848484848485% 33/33 1.0% 1468 1033/1468 0.7036784741144414%
Cornell Government 31 31/31 1.0% 26/31 0.8387096774193549% 30/31 0.967741935483871% 1296 873/1296 0.6736111111111112%
Dartmouth Government 28 28/28 1.0% 24/28 0.8571428571428571% 26/28 0.9285714285714286% 895 695/895 0.776536312849162%
Brown Political Science 27 27/27 1.0% 21/27 0.7777777777777778% 27/27 1.0% 1014 702/1014 0.6923076923076923%
  • 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
Princeton Politics 47 47/47 1.0% 38/47 0.8085106382978723% 45/47 0.9574468085106383% 1629 1266/1629 0.7771639042357275%
Columbia Political Science 35 35/35 1.0% 24/35 0.6857142857142857% 35/35 1.0% 2756 1665/2756 0.6041364296081277%
Harvard Government 34 34/34 1.0% 26/34 0.7647058823529411% 33/34 0.9705882352941176% 2415 1800/2415 0.7453416149068323%
Yale Political Science 34 34/34 1.0% 32/34 0.9411764705882353% 33/34 0.9705882352941176% 1130 885/1130 0.7831858407079646%
Penn Political Science 33 33/33 1.0% 28/33 0.8484848484848485% 33/33 1.0% 1468 1033/1468 0.7036784741144414%
Cornell Government 31 31/31 1.0% 26/31 0.8387096774193549% 30/31 0.967741935483871% 1296 873/1296 0.6736111111111112%
Dartmouth Government 28 28/28 1.0% 24/28 0.8571428571428571% 26/28 0.9285714285714286% 895 695/895 0.776536312849162%
Brown Political Science 27 27/27 1.0% 21/27 0.7777777777777778% 27/27 1.0% 1014 702/1014 0.6923076923076923%
  • 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.01020304050Dartmouth Tenure track 2828Harvard Tenure track 3434Yale Tenure track 3434Princeton Tenure track 4747Columbia Tenure track 3535Cornell Tenure track 3131Penn Tenure track 3333Brown Tenure track 2727DartmouthHarvardYalePrincetonColumbiaCornellPennBrownAcademicsDepartment

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
Princeton Politics 47 47/47 1.0% 38/47 0.8085106382978723% 45/47 0.9574468085106383% 1629 1266/1629 0.7771639042357275%
Columbia Political Science 35 35/35 1.0% 24/35 0.6857142857142857% 35/35 1.0% 2756 1665/2756 0.6041364296081277%
Harvard Government 34 34/34 1.0% 26/34 0.7647058823529411% 33/34 0.9705882352941176% 2415 1800/2415 0.7453416149068323%
Yale Political Science 34 34/34 1.0% 32/34 0.9411764705882353% 33/34 0.9705882352941176% 1130 885/1130 0.7831858407079646%
Penn Political Science 33 33/33 1.0% 28/33 0.8484848484848485% 33/33 1.0% 1468 1033/1468 0.7036784741144414%
Cornell Government 31 31/31 1.0% 26/31 0.8387096774193549% 30/31 0.967741935483871% 1296 873/1296 0.6736111111111112%
Dartmouth Government 28 28/28 1.0% 24/28 0.8571428571428571% 26/28 0.9285714285714286% 895 695/895 0.776536312849162%
Brown Political Science 27 27/27 1.0% 21/27 0.7777777777777778% 27/27 1.0% 1014 702/1014 0.6923076923076923%
  • 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.0.02,000.04,000.06,000.08,000.010,000.0Distinguished Dartmouth Government over 7 academics 8,666.0Distinguished Harvard Government over 24 academics 4,089.0Distinguished Yale Political Science over 11 academics 6,814.0Distinguished Princeton Politics over 13 academics 4,007.0Distinguished Columbia Political Science over 12 academics 6,353.0Distinguished Cornell Government over 6 academics 4,678.0Distinguished Penn Political Science over 15 academics 5,758.0Distinguished Brown Political Science over 12 academics 1,649.5Full Dartmouth Government over 9 academics 1,635.0Full Harvard Government over 3 academics 3,151.0Full Yale Political Science over 5 academics 5,153.0Full Princeton Politics over 15 academics 4,155.0Full Columbia Political Science over 10 academics 2,704.5Full Cornell Government over 7 academics 2,052.0Full Penn Political Science over 5 academics 2,053.0Full Brown Political Science over 3 academics 1,748.0Associate Dartmouth Government over 9 academics 1,096.0Associate Harvard Government over 1 academics 1,473.0Associate Yale Political Science over 7 academics 1,371.0Associate Princeton Politics over 6 academics 1,793.5Associate Columbia Political Science over 5 academics 1,882.0Associate Cornell Government over 10 academics 925.0Associate Penn Political Science over 6 academics 1,312.5Associate Brown Political Science over 7 academics 1,035.0Assistant Dartmouth Government over 3 academics 95.0Assistant Harvard Government over 6 academics 248.0Assistant Yale Political Science over 11 academics 221.0Assistant Princeton Politics over 13 academics 243.0Assistant Columbia Political Science over 8 academics 759.5Assistant Cornell Government over 8 academics 194.5Assistant Penn Political Science over 7 academics 291.0Assistant Brown Political Science over 5 academics 135.0DistinguishedFullAssociateAssistantMedian 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
Princeton Politics 47 47/47 1.0% 38/47 0.8085106382978723% 45/47 0.9574468085106383% 1629 1266/1629 0.7771639042357275%
Columbia Political Science 35 35/35 1.0% 24/35 0.6857142857142857% 35/35 1.0% 2756 1665/2756 0.6041364296081277%
Harvard Government 34 34/34 1.0% 26/34 0.7647058823529411% 33/34 0.9705882352941176% 2415 1800/2415 0.7453416149068323%
Yale Political Science 34 34/34 1.0% 32/34 0.9411764705882353% 33/34 0.9705882352941176% 1130 885/1130 0.7831858407079646%
Penn Political Science 33 33/33 1.0% 28/33 0.8484848484848485% 33/33 1.0% 1468 1033/1468 0.7036784741144414%
Cornell Government 31 31/31 1.0% 26/31 0.8387096774193549% 30/31 0.967741935483871% 1296 873/1296 0.6736111111111112%
Dartmouth Government 28 28/28 1.0% 24/28 0.8571428571428571% 26/28 0.9285714285714286% 895 695/895 0.776536312849162%
Brown Political Science 27 27/27 1.0% 21/27 0.7777777777777778% 27/27 1.0% 1014 702/1014 0.6923076923076923%
  • 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 Sean J. Westwood 140422 Harvard Government Kosuke Imai 585642 Yale Political Science Gregory Alain Huber 196472 Princeton Politics Rocío Titiunik 159172 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 William C. Wohlforth 108723 Harvard Government Peter A. Hall 420353 Yale Political Science Nicholas Sambanis 147623 Princeton Politics Andrew Moravcsik 150603 Columbia Political Science Andreas Wimmer 251783 Cornell Government Kenneth Roberts 69653 Penn Political Science Diana C. Mutz 193363 Brown Political Science Richard Owen Snyder 63614 Dartmouth Government John Michael Carey 96924 Harvard Government Dustin Tingley 379224 Yale Political Science Jennifer Gandhi 100294 Princeton Politics Andrew M. Guess 133464 Columbia Political Science John D. Huber 87584 Cornell Government Peter John Loewen 57494 Penn Political Science Edward D. Mansfield 173334 Brown Political Science Peter Andreas 44445 Dartmouth Government Jennifer Jerit 86665 Harvard Government James M. Snyder, Jr. 273815 Yale Political Science Jacob S. Hacker 79875 Princeton Politics Carles Boix 124665 Columbia Political Science Jack L. Snyder 75895 Cornell Government Peter Joachim Katzenstein 49395 Penn Political Science Matthew Levendusky 160025 Brown Political Science Jeff D. Colgan 421812345CitationsRank

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

Rank 5 of 47 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%
Adam Michael Auerbach 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 17 14/17 0.8235294117647058%
Aditi Sahasrabuddhe 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 11 6/11 0.5454545454545454%
Ainsley Lesure 1 1/1 1.0% 0/1 0.0% 1/1 1.0% 2 2/2 1.0%
Akshay Govind Dixit 1 1/1 1.0% 1/1 1.0% 0/1 0.0% 4 3/4 0.75%
Alan S. Gerber 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 136 122/136 0.8970588235294118%
Alessandra M. Casella 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 54 45/54 0.8333333333333334%
Alex Weisiger 1 1/1 1.0% 0/1 0.0% 1/1 1.0% 7 7/7 1.0%
Alexander Hirschman Gourevitch 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 41 28/41 0.6829268292682927%
Alexander Livingston 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 38 14/38 0.3684210526315789%
Alexandre Debs 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 20 17/20 0.85%
Alisha C. Holland 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 22 15/22 0.6818181818181818%
Allen R. Carlson 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 29 14/29 0.4827586206896552%
Allison Carnegie 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 40 27/40 0.675%
Allison P. Harris 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 8 8/8 1.0%
Amanda Weiss 1 1/1 1.0% 0/1 0.0% 1/1 1.0% 4 3/4 0.75%
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%
Ana De La O Torres 1 1/1 1.0% 1/1 1.0% 0/1 0.0% 14 14/14 1.0%
Andreas Wiedemann 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 10 10/10 1.0%
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. McCall 1 1/1 1.0% 0/1 0.0% 1/1 1.0% 2 2/2 1.0%
Andrew J. Nathan 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 713 116/713 0.16269284712482468%
Andrew M. Guess 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 44 42/44 0.9545454545454546%
Andrew Moravcsik 1 1/1 1.0% 0/1 0.0% 1/1 1.0% 74 47/74 0.6351351351351351%
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%
Averell Schmidt 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 8 6/8 0.75%
Benjamin A. Valentino 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 43 36/43 0.8372093023255814%
Beth Simmons 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 86 72/86 0.8372093023255814%
Blake Miller 1 1/1 1.0% 0/1 0.0% 1/1 1.0% 7 5/7 0.7142857142857143%
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%
Bryan Garsten 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 16 9/16 0.5625%
Bryn Rosenfeld 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 15 11/15 0.7333333333333333%
Calvin Thrall 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 9 9/9 1.0%
Carles Boix 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 50 44/50 0.88%
Carlo Prato 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 22 20/22 0.9090909090909091%
Charles M. Cameron 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 52 40/52 0.7692307692307693%
Charles T. Mcclean 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 43 27/43 0.627906976744186%
Christian "Chris" Chambers 1 1/1 1.0% 0/1 0.0% 1/1 1.0% 2 1/2 0.5%
Christina L. Davis 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 33 24/33 0.7272727272727273%
Christina M. Kinane 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 6 5/6 0.8333333333333334%
Christoph Mikulaschek 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 9 9/9 1.0%
Christopher Blair 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 31 16/31 0.5161290322580645%
Claudine Gay 1 1/1 1.0% 0/1 0.0% 1/1 1.0% 11 10/11 0.9090909090909091%
Corey Brettschneider 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 37 26/37 0.7027027027027027%
Daniel C. Mattingly 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 16 15/16 0.9375%
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 M. Smith 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 39 27/39 0.6923076923076923%
Daniel N.j. de Kadt 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 13 12/13 0.9230769230769231%
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%
Daryl G. Press 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 62 47/62 0.7580645161290323%
David Alexander Bateman 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 22 16/22 0.7272727272727273%
David C. Johnston 1 1/1 1.0% 0/1 0.0% 1/1 1.0% 3 2/3 0.6666666666666666%
David Skarbek 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 40 35/40 0.875%
Dean Lacy 1 1/1 1.0% 0/1 0.0% 1/1 1.0% 19 18/19 0.9473684210526315%
Deborah J. Yashar 1 1/1 1.0% 0/1 0.0% 1/1 1.0% 15 7/15 0.4666666666666667%
Deborah Jordan Brooks 1 1/1 1.0% 0/1 0.0% 1/1 1.0% 12 12/12 1.0%
Diana C. Mutz 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 76 62/76 0.8157894736842105%
Diana Fu 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 17 16/17 0.9411764705882353%
Didac Queralt 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 14 14/14 1.0%
Dillon Laaker 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 2 2/2 1.0%
Donald P. Green 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 226 203/226 0.8982300884955752%
Donghyun Danny Choi 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 14 12/14 0.8571428571428571%
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%
Egor Lazarev 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 8 5/8 0.625%
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%
Elizabeth Nathan Saunders 1 1/1 1.0% 0/1 0.0% 1/1 1.0% 32 21/32 0.65625%
Elizabeth Parker-Magyar 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 10 4/10 0.4%
Elizabeth R. Nugent 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 22 19/22 0.8636363636363636%
Emily A. Sellars 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 11 10/11 0.9090909090909091%
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%
Eunji Kim 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 16 14/16 0.875%
Feyaad Allie 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 3 3/3 1.0%
Fiona S. Cunningham 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 13 12/13 0.9230769230769231%
Frances E. Lee 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 37 30/37 0.8108108108108109%
Fredrick C. Harris 1 1/1 1.0% 0/1 0.0% 1/1 1.0% 27 13/27 0.48148148148148145%
G. John Ikenberry 1 1/1 1.0% 0/1 0.0% 1/1 1.0% 98 70/98 0.7142857142857143%
Gareth Nellis 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 15 14/15 0.9333333333333333%
Gary King 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 327 271/327 0.8287461773700305%
Gemma Dipoppa 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 12 10/12 0.8333333333333334%
GERARD PADRÓ i MIQUEL 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 26 23/26 0.8846153846153846%
Germán Gieczewski 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 9 9/9 1.0%
Gleason Judd 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 9 9/9 1.0%
Gregory Alain Huber 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 118 112/118 0.9491525423728814%
Gregory Conti 1 1/1 1.0% 0/1 0.0% 1/1 1.0% 19 17/19 0.8947368421052632%
Gregory J. Wawro 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 27 21/27 0.7777777777777778%
Grigore Pop-Eleches 1 1/1 1.0% 0/1 0.0% 1/1 1.0% 44 39/44 0.8863636363636364%
Grzegorz Ekiert 1 1/1 1.0% 0/1 0.0% 1/1 1.0% 41 21/41 0.5121951219512195%
Guadalupe Tuñón 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 11 11/11 1.0%
Gustavo A. Flores-Macías 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 54 25/54 0.46296296296296297%
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%
Hye Young You 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 22 22/22 1.0%
Hélène Landemore 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 54 42/54 0.7777777777777778%
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%
Isabel María Perera 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 32 21/32 0.65625%
Ismail K. White 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 31 25/31 0.8064516129032258%
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 Bernard Murphy 1 1/1 1.0% 1/1 1.0% 0/1 0.0% 36 25/36 0.6944444444444444%
James M. Snyder, Jr. 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 139 130/139 0.935251798561151%
James Raymond Vreeland 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 63 46/63 0.7301587301587301%
Jamila Michener 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 63 46/63 0.7301587301587301%
Jane Esberg 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 13 10/13 0.7692307692307693%
Jason Barabas 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 28 27/28 0.9642857142857143%
Jason Frank 1 1/1 1.0% 0/1 0.0% 1/1 1.0% 22 11/22 0.5%
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%
Jeffrey A. Friedman 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 32 24/32 0.75%
Jeffrey Edward Green 1 1/1 1.0% 0/1 0.0% 1/1 1.0% 30 19/30 0.6333333333333333%
Jeffrey R. Lax 1 1/1 1.0% 0/1 0.0% 1/1 1.0% 23 23/23 1.0%
Jennifer A. Widner 1 1/1 1.0% 0/1 0.0% 1/1 1.0% 17 12/17 0.7058823529411765%
Jennifer Gandhi 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 20 16/20 0.8%
Jennifer Hadden 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 30 24/30 0.8%
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%
JENNIFER M. LIND 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 54 40/54 0.7407407407407407%
Jeremy Ferwerda 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 20 20/20 1.0%
John Benedict Londregan 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 32 24/32 0.75%
John D. Huber 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 35 33/35 0.9428571428571428%
John Marshall 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 28 26/28 0.9285714285714286%
John Michael Carey 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 95 56/95 0.5894736842105263%
Jonathan Mummolo 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 23 23/23 1.0%
Jonathan P. Kastellec 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 35 34/35 0.9714285714285714%
Joshua David Kertzer 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 52 44/52 0.8461538461538461%
Joshua Kalla 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 27 26/27 0.9629629629629629%
Julia Gray 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 28 24/28 0.8571428571428571%
Julia Lynch 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 57 42/57 0.7368421052631579%
Julie L. Rose 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 10 8/10 0.8%
Junyan Jiang 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 18 16/18 0.8888888888888888%
Justin H. Phillips 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 25 24/25 0.96%
Kate Baldwin 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 19 19/19 1.0%
Katherine Irajpanah 1 1/1 1.0% 0/1 0.0% 1/1 1.0% 3 2/3 0.6666666666666666%
Katherine Tate 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 38 25/38 0.6578947368421053%
Kathleen E. Powers 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 13 9/13 0.6923076923076923%
Keidrick J. Roy 1 1/1 1.0% 0/1 0.0% 1/1 1.0% 8 6/8 0.75%
Kenneth Roberts 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 88 57/88 0.6477272727272727%
Kevin DeLuca 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 6 6/6 1.0%
Kosuke Imai 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 161 139/161 0.8633540372670807%
Kristopher W. Ramsay 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 33 28/33 0.8484848484848485%
Lafleur Stephens-Dougan 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 6 5/6 0.8333333333333334%
Layna Mosley 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 68 40/68 0.5882352941176471%
Leonard Wantchekon 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 58 51/58 0.8793103448275862%
Lisa Baldez 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 34 15/34 0.4411764705882353%
Loren Goldman 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 17 14/17 0.8235294117647058%
Luca Bellodi 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 3 3/3 1.0%
Lucas Swaine 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 28 23/28 0.8214285714285714%
Marc Meredith 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 42 37/42 0.8809523809523809%
Marcel F. Roman 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% 44 32/44 0.7272727272727273%
Maria Victoria Murillo 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 88 70/88 0.7954545454545454%
Mark McGann Blyth 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 108 67/108 0.6203703703703703%
Markus Prior 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 25 25/25 1.0%
Marques Zárate 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 7 4/7 0.5714285714285714%
Mashail Malik 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 8 7/8 0.875%
Matias Iaryczower 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 18 18/18 1.0%
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 Lee 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 16 12/16 0.75%
Melissa Lee Sands 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 14 13/14 0.9285714285714286%
Melissa Schwartzberg 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 36 25/36 0.6944444444444444%
Melvin L. Rogers 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 42 20/42 0.47619047619047616%
Mia Costa 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 25 18/25 0.72%
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%
Michael M. Ting 1 1/1 1.0% 0/1 0.0% 1/1 1.0% 34 33/34 0.9705882352941176%
Michele F. Margolis 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 18 18/18 1.0%
Michelle T. Clarke 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 13 11/13 0.8461538461538461%
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%
Naima Green-Riley 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 3 2/3 0.6666666666666666%
Nicholas Kuipers 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 16 15/16 0.9375%
Nicholas L. Miller 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 43 25/43 0.5813953488372093%
Nicholas Sambanis 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 62 52/62 0.8387096774193549%
Nikhar Gaikwad 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 18 16/18 0.8888888888888888%
Noah Zucker 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 10 9/10 0.9%
Noam Reich 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 2 2/2 1.0%
Nolan McCarty 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 64 43/64 0.671875%
Oumar Ba 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 47 22/47 0.46808510638297873%
P. M. Aronow 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 51 49/51 0.9607843137254902%
Parrish Bergquist 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 19 19/19 1.0%
patchen markell 1 1/1 1.0% 0/1 0.0% 1/1 1.0% 19 16/19 0.8421052631578947%
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 E. Buisseret 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 16 16/16 1.0%
Peter Joachim Katzenstein 1 1/1 1.0% 0/1 0.0% 1/1 1.0% 79 49/79 0.620253164556962%
Peter John Loewen 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 106 93/106 0.8773584905660378%
Peter K. Enns 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 64 46/64 0.71875%
Pia J. Raffler 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 8 8/8 1.0%
Prerna Singh 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 25 11/25 0.44%
Rachel Beatty Riedl 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 28 23/28 0.8214285714285714%
Rafaela Dancygier 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 28 22/28 0.7857142857142857%
Rebecca Weitz-Shapiro 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 24 22/24 0.9166666666666666%
Reid B. C. Pauly 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 16 12/16 0.75%
Richard F. Bensel 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 30 15/30 0.5%
Richard Owen Snyder 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 34 27/34 0.7941176470588235%
Robert A. Blair 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 42 40/42 0.9523809523809523%
Robert Y. Shapiro 1 1/1 1.0% 0/1 0.0% 1/1 1.0% 110 62/110 0.5636363636363636%
Rocío Titiunik 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 41 39/41 0.9512195121951219%
Rory Truex 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 25 17/25 0.68%
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%
Rudra Sil 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 31 26/31 0.8387096774193549%
Russell Muirhead 1 1/1 1.0% 0/1 0.0% 1/1 1.0% 21 18/21 0.8571428571428571%
Ryan D. Enos 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 39 28/39 0.717948717948718%
Sabrina M. Karim 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 45 34/45 0.7555555555555555%
Sarah Bush 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 35 27/35 0.7714285714285715%
Sarah E. Kreps 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 146 96/146 0.6575342465753424%
Sarah F. Thompson 1 1/1 1.0% 1/1 1.0% 0/1 0.0% 1 1/1 1.0%
Sarah Zukerman Daly 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 31 20/31 0.6451612903225806%
Sean J. Westwood 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 45 38/45 0.8444444444444444%
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%
Shigeo Hirano 1 1/1 1.0% 0/1 0.0% 1/1 1.0% 18 18/18 1.0%
Shiro Kuriwaki 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 18 18/18 1.0%
Sonu Bedi 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 15 14/15 0.9333333333333333%
Soosun You 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 3 2/3 0.6666666666666666%
Soyoung Lee 1 1/1 1.0% 0/1 0.0% 1/1 1.0% 4 4/4 1.0%
Stephanie Ternullo 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 18 11/18 0.6111111111111112%
Stephen Chaudoin 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 26 26/26 1.0%
Stephen Daniel Ansolabehere 1 1/1 1.0% 0/1 0.0% 1/1 1.0% 79 74/79 0.9367088607594937%
Stephen G. Brooks 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 51 41/51 0.803921568627451%
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%
Talbot M. Andrews 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 36 32/36 0.8888888888888888%
Tali Mendelberg 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 60 47/60 0.7833333333333333%
Tanushree Goyal 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 5 5/5 1.0%
TARIQ THACHIL 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 16 14/16 0.875%
Temi Ogunye 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 1 1/1 1.0%
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%
Turkuler ISIKSEL 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 19 13/19 0.6842105263157895%
Tyler Jost 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 12 12/12 1.0%
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%
William R. Hobbs 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 22 19/22 0.8636363636363636%
Xu Xu 1 1/1 1.0% 0/1 0.0% 1/1 1.0% 13 13/13 1.0%
Yamil Ricardo Velez 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 27 27/27 1.0%
Yang-Yang Zhou 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 14 14/14 1.0%
Yuhua Wang 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 26 23/26 0.8846153846153846%
Zeyang (Arthur) Yu 1 1/1 1.0% 1/1 1.0% 0/1 0.0% 4 4/4 1.0%
  • 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 21 academics 7.07.0Associate Harvard Government median of 24 academics 5.05.0Associate Yale Political Science median of 20 academics 6.06.0Associate Princeton Politics median of 31 academics 7.07.0Associate Columbia Political Science median of 23 academics 6.06.0Associate Cornell Government median of 19 academics 8.08.0Associate Penn Political Science median of 25 academics 7.07.0Associate Brown Political Science median of 20 academics 7.07.0Full or distinguished Dartmouth Government median of 16 academics 14.514.5Full or distinguished Harvard Government median of 24 academics 8.08.0Full or distinguished Yale Political Science median of 14 academics 8.08.0Full or distinguished Princeton Politics median of 29 academics 12.012.0Full or distinguished Columbia Political Science median of 20 academics 10.510.5Full or distinguished Cornell Government median of 11 academics 12.012.0Full or distinguished Penn Political Science median of 20 academics 11.011.0Full or distinguished Brown Political Science median of 13 academics 12.012.0AssociateFull 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
Princeton Politics 47 47/47 1.0% 38/47 0.8085106382978723% 45/47 0.9574468085106383% 1629 1266/1629 0.7771639042357275%
Columbia Political Science 35 35/35 1.0% 24/35 0.6857142857142857% 35/35 1.0% 2756 1665/2756 0.6041364296081277%
Harvard Government 34 34/34 1.0% 26/34 0.7647058823529411% 33/34 0.9705882352941176% 2415 1800/2415 0.7453416149068323%
Yale Political Science 34 34/34 1.0% 32/34 0.9411764705882353% 33/34 0.9705882352941176% 1130 885/1130 0.7831858407079646%
Penn Political Science 33 33/33 1.0% 28/33 0.8484848484848485% 33/33 1.0% 1468 1033/1468 0.7036784741144414%
Cornell Government 31 31/31 1.0% 26/31 0.8387096774193549% 30/31 0.967741935483871% 1296 873/1296 0.6736111111111112%
Dartmouth Government 28 28/28 1.0% 24/28 0.8571428571428571% 26/28 0.9285714285714286% 895 695/895 0.776536312849162%
Brown Political Science 27 27/27 1.0% 21/27 0.7777777777777778% 27/27 1.0% 1014 702/1014 0.6923076923076923%
  • 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 665665The Journal of PoliticsThe Journal of Politics 352352American Journal of Political ScienceAmerican Journal of Political Science 342342American Political Science ReviewAmerican Political Science Review 336336Perspectives on PoliticsPerspectives on Politics 248248International OrganizationInternational Organization 190190Comparative Political StudiesComparative Political Studies 152152Education nextEducation next 142142PS Political Science & PoliticsPS Political Science & Politics 141141Political AnalysisPolitical Analysis 138138World PoliticsWorld Politics 129129Public Opinion QuarterlyPublic Opinion Quarterly 123123The Monkey CageThe Monkey Cage 122122British Journal of Political ScienceBritish Journal of Political Science 121121International SecurityInternational Security 1091090250500JournalWorks

The twelve venues highest on this reading, of 1,407.

What these filters select, per department not what the graph divided by
Department Academics CVScholarOpenAlex Works With a count
Princeton Politics 47 47/47 1.0% 38/47 0.8085106382978723% 45/47 0.9574468085106383% 1629 1266/1629 0.7771639042357275%
Columbia Political Science 35 35/35 1.0% 24/35 0.6857142857142857% 35/35 1.0% 2756 1665/2756 0.6041364296081277%
Harvard Government 34 34/34 1.0% 26/34 0.7647058823529411% 33/34 0.9705882352941176% 2415 1800/2415 0.7453416149068323%
Yale Political Science 34 34/34 1.0% 32/34 0.9411764705882353% 33/34 0.9705882352941176% 1130 885/1130 0.7831858407079646%
Penn Political Science 33 33/33 1.0% 28/33 0.8484848484848485% 33/33 1.0% 1468 1033/1468 0.7036784741144414%
Cornell Government 31 31/31 1.0% 26/31 0.8387096774193549% 30/31 0.967741935483871% 1296 873/1296 0.6736111111111112%
Dartmouth Government 28 28/28 1.0% 24/28 0.8571428571428571% 26/28 0.9285714285714286% 895 695/895 0.776536312849162%
Brown Political Science 27 27/27 1.0% 21/27 0.7777777777777778% 27/27 1.0% 1014 702/1014 0.6923076923076923%
  • 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.