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 13,779.4
2 Dartmouth Government 7 academics 9,739.8
3 Harvard Government 24 academics 6,706.3
4 Penn Political Science 15 academics 5,997.5
5 Cornell Government 6 academics 4,939.7
6 Yale Political Science 11 academics 3,945.8
7 Princeton Politics 13 academics 2,786.0
8 Brown Political Science 12 academics 2,618.1

221,567 citations over 1,919 of 2,893 works (66% carry a count). 95 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% 621 459/621 0.7391304347826086%
Penn Political Science 15 15/15 1.0% 14/15 0.9333333333333333% 15/15 1.0% 447 304/447 0.680089485458613%
Princeton Politics 13 13/13 1.0% 9/13 0.6923076923076923% 12/13 0.9230769230769231% 239 184/239 0.7698744769874477%
Brown Political Science 12 12/12 1.0% 7/12 0.5833333333333334% 12/12 1.0% 229 135/229 0.5895196506550219%
Columbia Political Science 12 12/12 1.0% 8/12 0.6666666666666666% 12/12 1.0% 689 348/689 0.5050798258345428%
Yale Political Science 11 11/11 1.0% 10/11 0.9090909090909091% 11/11 1.0% 234 185/234 0.7905982905982906%
Dartmouth Government 7 7/7 1.0% 6/7 0.8571428571428571% 7/7 1.0% 167 142/167 0.8502994011976048%
Cornell Government 6 6/6 1.0% 5/6 0.8333333333333334% 6/6 1.0% 267 162/267 0.6067415730337079%
  • 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% 621 459/621 0.7391304347826086%
Penn Political Science 15 15/15 1.0% 14/15 0.9333333333333333% 15/15 1.0% 447 304/447 0.680089485458613%
Princeton Politics 13 13/13 1.0% 9/13 0.6923076923076923% 12/13 0.9230769230769231% 239 184/239 0.7698744769874477%
Brown Political Science 12 12/12 1.0% 7/12 0.5833333333333334% 12/12 1.0% 229 135/229 0.5895196506550219%
Columbia Political Science 12 12/12 1.0% 8/12 0.6666666666666666% 12/12 1.0% 689 348/689 0.5050798258345428%
Yale Political Science 11 11/11 1.0% 10/11 0.9090909090909091% 11/11 1.0% 234 185/234 0.7905982905982906%
Dartmouth Government 7 7/7 1.0% 6/7 0.8571428571428571% 7/7 1.0% 167 142/167 0.8502994011976048%
Cornell Government 6 6/6 1.0% 5/6 0.8333333333333334% 6/6 1.0% 267 162/267 0.6067415730337079%
  • 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% 621 459/621 0.7391304347826086%
Penn Political Science 15 15/15 1.0% 14/15 0.9333333333333333% 15/15 1.0% 447 304/447 0.680089485458613%
Princeton Politics 13 13/13 1.0% 9/13 0.6923076923076923% 12/13 0.9230769230769231% 239 184/239 0.7698744769874477%
Brown Political Science 12 12/12 1.0% 7/12 0.5833333333333334% 12/12 1.0% 229 135/229 0.5895196506550219%
Columbia Political Science 12 12/12 1.0% 8/12 0.6666666666666666% 12/12 1.0% 689 348/689 0.5050798258345428%
Yale Political Science 11 11/11 1.0% 10/11 0.9090909090909091% 11/11 1.0% 234 185/234 0.7905982905982906%
Dartmouth Government 7 7/7 1.0% 6/7 0.8571428571428571% 7/7 1.0% 167 142/167 0.8502994011976048%
Cornell Government 6 6/6 1.0% 5/6 0.8333333333333334% 6/6 1.0% 267 162/267 0.6067415730337079%
  • 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.0.05,000.010,000.015,000.0Distinguished Dartmouth Government over 7 academics 9,739.89,739.8Distinguished Harvard Government over 24 academics 6,426.96,426.9Distinguished Yale Political Science over 11 academics 3,587.13,587.1Distinguished Princeton Politics over 13 academics 2,571.72,571.7Distinguished Columbia Political Science over 12 academics 12,631.112,631.1Distinguished Cornell Government over 6 academics 4,939.74,939.7Distinguished Penn Political Science over 15 academics 5,997.55,997.5Distinguished Brown Political Science over 12 academics 2,399.92,399.9DistinguishedCitations 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% 621 459/621 0.7391304347826086%
Penn Political Science 15 15/15 1.0% 14/15 0.9333333333333333% 15/15 1.0% 447 304/447 0.680089485458613%
Princeton Politics 13 13/13 1.0% 9/13 0.6923076923076923% 12/13 0.9230769230769231% 239 184/239 0.7698744769874477%
Brown Political Science 12 12/12 1.0% 7/12 0.5833333333333334% 12/12 1.0% 229 135/229 0.5895196506550219%
Columbia Political Science 12 12/12 1.0% 8/12 0.6666666666666666% 12/12 1.0% 689 348/689 0.5050798258345428%
Yale Political Science 11 11/11 1.0% 10/11 0.9090909090909091% 11/11 1.0% 234 185/234 0.7905982905982906%
Dartmouth Government 7 7/7 1.0% 6/7 0.8571428571428571% 7/7 1.0% 167 142/167 0.8502994011976048%
Cornell Government 6 6/6 1.0% 5/6 0.8333333333333334% 6/6 1.0% 267 162/267 0.6067415730337079%
  • 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.010000200003000040000500001 Dartmouth Government Brendan Nyhan 276811 Harvard Government Dustin Tingley 102181 Yale Political Science Gregory Alain Huber 34651 Princeton Politics Helen V. Milner 36201 Columbia Political Science Andrew Gelman 437601 Cornell Government Sarah E. Kreps 57911 Penn Political Science Matthew Levendusky 108761 Brown Political Science Eric M. Patashnik 37162 Dartmouth Government Jennifer Jerit 17882 Harvard Government Steven Levitsky 100452 Yale Political Science Milan Svolik 30712 Princeton Politics Arthur Spirling 24982 Columbia Political Science Donald P. Green 99422 Cornell Government Thomas B. Pepinsky 49062 Penn Political Science Guy Grossman 37532 Brown Political Science Peter Andreas 26993 Dartmouth Government William C. Wohlforth 11583 Harvard Government Gary King 87963 Yale Political Science Alan S. Gerber 30103 Princeton Politics G. John Ikenberry 17163 Columbia Political Science Nadia Urbinati 20663 Cornell Government Douglas L. Kriner 29053 Penn Political Science Daniel J. Hopkins 36993 Brown Political Science Jeff D. Colgan 18824 Dartmouth Government John Michael Carey 11084 Harvard Government Joshua David Kertzer 35514 Yale Political Science Jacob S. Hacker 22744 Princeton Politics Nolan McCarty 12124 Columbia Political Science Timothy M. Frye 10034 Cornell Government Suzanne Mettler 14254 Penn Political Science Michael Horowitz 32714 Brown Political Science Mark McGann Blyth 12185 Dartmouth Government Jason Lyall 6605 Harvard Government Peter A. Hall 29085 Yale Political Science Elisabeth Jean Wood 14275 Princeton Politics Rafaela Dancygier 10745 Columbia Political Science Andreas Wimmer 8105 Cornell Government Peter Joachim Katzenstein 1875 Penn Political Science Diana C. Mutz 30945 Brown Political Science ROSE McDERMOTT 55012345CitationsRank

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
Michael J. Hiscox 1 1/1 1.0% 0/1 0.0% 1/1 1.0% 0 —
Robert Y. Shapiro 1 1/1 1.0% 0/1 0.0% 1/1 1.0% 0 —
Edward S. Steinfeld 1 1/1 1.0% 0/1 0.0% 1/1 1.0% 1 0/1 0.0%
Melissa Sharon Lane 1 1/1 1.0% 0/1 0.0% 0/1 0.0% 15 0/15 0.0%
Steven I. Wilkinson 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 2 0/2 0.0%
Adam Meirowitz 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 7 7/7 1.0%
Alan S. Gerber 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 42 38/42 0.9047619047619048%
Amaney A. Jamal 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 29 25/29 0.8620689655172413%
Amy Gutmann 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 14 7/14 0.5%
Andreas Wimmer 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 31 22/31 0.7096774193548387%
Andrew Gelman 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 179 159/179 0.888268156424581%
Andrew J. Nathan 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 294 36/294 0.12244897959183673%
Arthur Spirling 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 20 18/20 0.9%
Ashutosh Varshney 1 1/1 1.0% 0/1 0.0% 1/1 1.0% 9 6/9 0.6666666666666666%
Atul Kohli 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 9 7/9 0.7777777777777778%
Beth Simmons 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 32 28/32 0.875%
Brendan Nyhan 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 74 72/74 0.972972972972973%
Brendan O'Leary 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 82 27/82 0.32926829268292684%
Carles Boix 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 15 13/15 0.8666666666666667%
Christina L. Davis 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 18 14/18 0.7777777777777778%
Claudine Gay 1 1/1 1.0% 0/1 0.0% 1/1 1.0% 1 1/1 1.0%
Daniel Gillion 1 1/1 1.0% 0/1 0.0% 1/1 1.0% 7 7/7 1.0%
Daniel J. Hopkins 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 43 42/43 0.9767441860465116%
Daniel Paul Carpenter 1 1/1 1.0% 1/1 1.0% 0/1 0.0% 45 28/45 0.6222222222222222%
Daniel Ziblatt 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 45 26/45 0.5777777777777777%
Danielle S. Allen 1 1/1 1.0% 0/1 0.0% 1/1 1.0% 22 13/22 0.5909090909090909%
David Skarbek 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 16 11/16 0.6875%
Deborah J. Yashar 1 1/1 1.0% 0/1 0.0% 1/1 1.0% 8 4/8 0.5%
Diana C. Mutz 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 26 20/26 0.7692307692307693%
Donald P. Green 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 58 53/58 0.9137931034482759%
Douglas L. Kriner 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 52 38/52 0.7307692307692307%
Dustin Tingley 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 48 45/48 0.9375%
Edward D. Mansfield 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 18 16/18 0.8888888888888888%
Elisabeth Jean Wood 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 21 16/21 0.7619047619047619%
Elizabeth J. Perry 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 23 12/23 0.5217391304347826%
Eric M. Patashnik 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 34 18/34 0.5294117647058824%
Eric Nelson 1 1/1 1.0% 0/1 0.0% 1/1 1.0% 8 5/8 0.625%
Erik Wibbels 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 22 21/22 0.9545454545454546%
G. John Ikenberry 1 1/1 1.0% 0/1 0.0% 1/1 1.0% 10 9/10 0.9%
Gary King 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 83 72/83 0.8674698795180723%
GERARD PADRÓ i MIQUEL 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 12 10/12 0.8333333333333334%
Gregory Alain Huber 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 71 66/71 0.9295774647887324%
Grzegorz Ekiert 1 1/1 1.0% 0/1 0.0% 1/1 1.0% 5 5/5 1.0%
Guy Grossman 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 34 33/34 0.9705882352941176%
Helen V. Milner 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 41 38/41 0.926829268292683%
Ian Shapiro 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 21 19/21 0.9047619047619048%
Ira I. Katznelson 1 1/1 1.0% 0/1 0.0% 1/1 1.0% 7 5/7 0.7142857142857143%
Jack L. Snyder 1 1/1 1.0% 0/1 0.0% 1/1 1.0% 8 6/8 0.75%
Jacob S. Hacker 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 42 18/42 0.42857142857142855%
James M. Snyder, Jr. 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 19 19/19 1.0%
Jason Lyall 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 9 9/9 1.0%
Jean Louise Cohen 1 1/1 1.0% 0/1 0.0% 1/1 1.0% 2 2/2 1.0%
Jeff D. Colgan 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 41 23/41 0.5609756097560976%
Jennifer Hochschild 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 22 15/22 0.6818181818181818%
Jennifer Jerit 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 16 13/16 0.8125%
John Michael Carey 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 32 21/32 0.65625%
Joshua David Kertzer 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 38 33/38 0.868421052631579%
Margaret M. Weir 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 12 5/12 0.4166666666666667%
Mark McGann Blyth 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 38 18/38 0.47368421052631576%
Matthew Levendusky 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 33 27/33 0.8181818181818182%
Melani Cammett 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 16 14/16 0.875%
Melissa Schwartzberg 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 21 15/21 0.7142857142857143%
Michael Eric ROSEN 1 1/1 1.0% 0/1 0.0% 1/1 1.0% 6 5/6 0.8333333333333334%
Michael Horowitz 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 87 43/87 0.4942528735632184%
Michael Jones-Correa 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 20 14/20 0.7%
Milan Svolik 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 8 8/8 1.0%
Nadia Urbinati 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 76 41/76 0.5394736842105263%
Nicholas Sambanis 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 27 24/27 0.8888888888888888%
Nolan McCarty 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 14 11/14 0.7857142857142857%
Paul E. Peterson 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 89 51/89 0.5730337078651685%
Peter A. Hall 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 28 26/28 0.9285714285714286%
Peter Andreas 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 9 6/9 0.6666666666666666%
Peter Joachim Katzenstein 1 1/1 1.0% 0/1 0.0% 1/1 1.0% 14 6/14 0.42857142857142855%
Rafaela Dancygier 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 25 19/25 0.76%
Richard F. Bensel 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 5 2/5 0.4%
ROSE McDERMOTT 1 1/1 1.0% 0/1 0.0% 1/1 1.0% 41 24/41 0.5853658536585366%
Roxanne L. Euben 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 7 3/7 0.42857142857142855%
Russell Muirhead 1 1/1 1.0% 0/1 0.0% 1/1 1.0% 14 11/14 0.7857142857142857%
Sarah E. Kreps 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 95 60/95 0.631578947368421%
Sharon R. Krause 1 1/1 1.0% 0/1 0.0% 1/1 1.0% 10 8/10 0.8%
Sharyn O’Halloran 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 7 4/7 0.5714285714285714%
Sonu Bedi 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 5 5/5 1.0%
Stephen Daniel Ansolabehere 1 1/1 1.0% 0/1 0.0% 1/1 1.0% 3 3/3 1.0%
Stephen Macedo 1 1/1 1.0% 0/1 0.0% 1/1 1.0% 10 8/10 0.8%
Stephen Skowronek 1 1/1 1.0% 0/1 0.0% 1/1 1.0% 8 5/8 0.625%
Steven Levitsky 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 43 32/43 0.7441860465116279%
Susan L. Moffitt 1 1/1 1.0% 0/1 0.0% 1/1 1.0% 9 9/9 1.0%
Suzanne Mettler 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 34 23/34 0.6764705882352942%
Taeku Lee 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 19 15/19 0.7894736842105263%
Tali Mendelberg 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 27 22/27 0.8148148148148148%
TARIQ THACHIL 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 13 10/13 0.7692307692307693%
Theda Skocpol 1 1/1 1.0% 0/1 0.0% 1/1 1.0% 17 7/17 0.4117647058823529%
Thomas B. Pepinsky 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 87 52/87 0.5977011494252874%
Timothy M. Frye 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 22 16/22 0.7272727272727273%
Torben Iversen 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 16 13/16 0.8125%
Tulia G. Falleti 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 13 10/13 0.7692307692307693%
Virginia Page Fortna 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 6 5/6 0.8333333333333334%
Wendy J. Schiller 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 10 8/10 0.8%
William C. Wohlforth 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 25 19/25 0.76%
Yuhua Wang 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 19 15/19 0.7894736842105263%
  • 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, Cornell Government, Penn Political Science, Brown Political Science.0.05.010.015.0Associate Harvard Government median of 2 academics 6.56.5Associate Penn Political Science median of 1 academics 7.07.0Associate Brown Political Science median of 1 academics 7.07.0Full or distinguished Dartmouth Government median of 2 academics 12.512.5Full or distinguished Harvard Government median of 2 academics 9.59.5Full or distinguished Yale Political Science median of 1 academics 12.012.0Full or distinguished Princeton Politics median of 2 academics 12.012.0Full or distinguished Cornell Government median of 3 academics 12.012.0Full or distinguished Penn Political Science median of 7 academics 11.011.0Full or distinguished Brown Political Science median of 3 academics 13.013.0AssociateFull or distinguishedYears since the PhDRank reached

Dartmouth GovernmentHarvard GovernmentYale Political SciencePrinceton PoliticsCornell 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% 621 459/621 0.7391304347826086%
Penn Political Science 15 15/15 1.0% 14/15 0.9333333333333333% 15/15 1.0% 447 304/447 0.680089485458613%
Princeton Politics 13 13/13 1.0% 9/13 0.6923076923076923% 12/13 0.9230769230769231% 239 184/239 0.7698744769874477%
Brown Political Science 12 12/12 1.0% 7/12 0.5833333333333334% 12/12 1.0% 229 135/229 0.5895196506550219%
Columbia Political Science 12 12/12 1.0% 8/12 0.6666666666666666% 12/12 1.0% 689 348/689 0.5050798258345428%
Yale Political Science 11 11/11 1.0% 10/11 0.9090909090909091% 11/11 1.0% 234 185/234 0.7905982905982906%
Dartmouth Government 7 7/7 1.0% 6/7 0.8571428571428571% 7/7 1.0% 167 142/167 0.8502994011976048%
Cornell Government 6 6/6 1.0% 5/6 0.8333333333333334% 6/6 1.0% 267 162/267 0.6067415730337079%
  • 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 324324The Journal of PoliticsThe Journal of Politics 7171Perspectives on PoliticsPerspectives on Politics 6969American Journal of Political ScienceAmerican Journal of Political Science 5252The Irish TimesThe Irish Times 4545International OrganizationInternational Organization 4040Education nextEducation next 3939Proceedings of the National Academy of SciencesProceedings of the National Academy of Sciences 3434American Political Science ReviewAmerican Political Science Review 3333Cambridge University Press eBooksCambridge University Press eBooks 3232Comparative Political StudiesComparative Political Studies 3131British Journal of Political ScienceBritish Journal of Political Science 2929PS Political Science & PoliticsPS Political Science & Politics 2929Journal of democracyJournal of democracy 2727Journal of Health Politics Policy and LawJournal of Health Politics Policy and Law 27270100200300JournalWorks

The twelve venues highest on this reading, of 562.

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% 621 459/621 0.7391304347826086%
Penn Political Science 15 15/15 1.0% 14/15 0.9333333333333333% 15/15 1.0% 447 304/447 0.680089485458613%
Princeton Politics 13 13/13 1.0% 9/13 0.6923076923076923% 12/13 0.9230769230769231% 239 184/239 0.7698744769874477%
Brown Political Science 12 12/12 1.0% 7/12 0.5833333333333334% 12/12 1.0% 229 135/229 0.5895196506550219%
Columbia Political Science 12 12/12 1.0% 8/12 0.6666666666666666% 12/12 1.0% 689 348/689 0.5050798258345428%
Yale Political Science 11 11/11 1.0% 10/11 0.9090909090909091% 11/11 1.0% 234 185/234 0.7905982905982906%
Dartmouth Government 7 7/7 1.0% 6/7 0.8571428571428571% 7/7 1.0% 167 142/167 0.8502994011976048%
Cornell Government 6 6/6 1.0% 5/6 0.8333333333333334% 6/6 1.0% 267 162/267 0.6067415730337079%
  • 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.