buckinghamubadger

Dear new PhD applicants in Political Science,
 
I am writing this post to provide you with a centralized source of information to help you make decisions about where to apply. I decided to provide you with this source because this information was not available to me in any sort of organized fashion, meaning that I had to find and organize it myself. I wish a resource such as this had been available to me when I began applying.  This does not mean that you will not need to do research on the programs to which you consider applying. There is some information that I simply cannot provide you with, such as up to date data on placement rates or how well your research interests match with the departments you are considering. These are among the most important factors you will consider. While I will walk you through how one can go about making these calculations, the main point of this post is to provide you with a starting point- useful data to help you begin to make decisions about where you will apply.
 
Useful Links
 
Rankings
 
The first thing I should say about rankings are that they are only a short cut. There is a lot more noise than one would like. I encourage everyone to ensure that the department in question is placing people rather than assume it blindly because of the rankings (more on that later). There are three main rankings political scientists look at:
 
The NRC
https://www.chronicle.com/article/NRC-Rankings-Overview-/124714
 
Methodology: the NRC rankings use several different methodologies based on multiple objective criteria to determine their five different sets of rankings. The S-Rankings use some 20 different factors that scholars say are important such as faculty research productivity, student completion rates and funding. The Research Rankings are based on measures of the departments research productivity. The Student Rankings are based on measures of student outcomes and quality of life while in the department. The Diversity Rankings are based on measures of diversity. The R-Rankings are a regression model trying to determine the departments that look most like the departments the Scholars Model likes.
 
Pros:
A lot of objective data went into these rankings.
The multi-dimensionality of the rankings allow you to weigh the different dimensions as you see fit. EG if you care more about research productivity than student outcomes, you can look at the Research Rankings and weigh them in your decision of where to apply to.
The S-Rankings most closely resemble the 5-year placement rates I saw when deciding where to apply of any ranking is (including US News and Oprisko)
Cons
Equivocal: there is a lot of noise, and they show it to you. Programs don't have ranks, but rather rank ranges and there are five different sets of rankings.
Infrequent: this set of rankings came out in 2010, the last NRC rankings before that came out in 1998. While I do not think that these rankings are so excited old that they are not useful, a lot can change in eight years.
 
2) US News Rankings
https://www.usnews.com/best-graduate-schools/top-humanities-schools/political-science-rankings
 
Methodology: US News simply surveys scholars on the department reputation, asking them to rank them on a 1 to 5 scale, and ranks departments based on the results
 
Pros:
The most widely used rankings
The only rankings that take reputation into account
Cons:
Reputation is the only factor taken into account, so it could be said that the rankings are completely subjective
 
3) Oprisko
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2303567
 
Methodology: Oprisko looks at outcomes- R1 placements. He counts the number of PhDs from a given institution currently working at a PhD granting institution in Political Science. He comes up with two rankings from that- the raw total number of placements and the number of placement divided by faculty members (placement efficiency)
 
Pros
Makes student outcomes front and center
 
Cons:
Only uses R1 placements
The main rankings does not control for program size. The placement efficiency rankings, however, do.
 
Stipend Information
 
http://www.phdstipends.com
 
This website provides a searchable database of funding offers from various departments. Just search the name of a University and “Political Science” and something should come up.
 
Some of this data may be outdated, so pay attention to the year it was posted. Some schools may not have any data posted on this site. Funding offers may vary.  Better information may be available on the departments webpage. Nonetheless this is a very useful resource for information about funding.
 
When will I hear back?
 
https://forum.thegradcafe.com/topic/100449-decision-timelines-for-particular-universities-and-programs-derived-from-the-gradcafe-data-gregpa-distributions/?tab=comments#comment-1058542321
 
This link shows the timeline in which decisions have been made in the past. You could also search the gradcafe results forum to get a sense for when results will come through.
 
What should my Statement of Purpose look like?
 
http://grad.berkeley.edu/admissions/apply/statement-purpose/
 
Here is some useful advice for drafting a statement of purpose. Tailor it to your specific program. Mention Professors you'd like to work with and programs/institutes that might interest you. Also edit it as much as you possibly can. I made about ten drafts before finally sending it off.

 
GRE/GPA Info
 
Here is the GRE and GPA information on every school I could find. This data either is posted on the departments website or was about six months ago when I searched for it. Use this data to strategize where to apply. If you have a 155/155, it may not be wise to only apply to Stanford, Duke, Cal, UCSD and WashU, as a safety. However, do not let minor discrepancies discourage you from applying from your dream program. These stats are a small part of a number of factors that will determine your success in the application process. Use them to give you a rough idea of how you may fare, not as an absolute predictor of your success.
 
Stanford 163 q/166 v/3.8 GPA Recommended (Rec)
Duke 163 q/163 v/3.8 GPA Average (AVG)
UC Berkeley 161 q/158 v Rec
Northwestern 148 q/160 v Rec
Kansas 148 v/156 q/ 3.5 GPA Avg
UCSD 163 q/166 v/3.9 GPA Avg
Chicago 162 q/166 v/3.8 GPA Avg
Columbia 158 q/161 v/ 3.8 GPA Avg
Penn 161 q/165 v Avg
WashU-STL 161 q/159 v/3.9 GPA Avg
Colorado State 154 q/154 v/ 3.5 GPA Rec
UNLV 148 q/160 v/3.5 GPA Rec
Emory 160 q/160 v/ B+ (or Better) GPA Avg
Princeton 160 q/160 v/3.8 GPA Rec
Notre Dame 158 q/ 165 v Avg
Colorado 154 q/160 v Avg
Oregon 300 total GRE/3.0 GPA Rec
UC Riverside 307 total GRE/3.0 GPA Minimum
Washington 314 total GRE/3.4 GPA Rec
Oklahoma 154 q/153 v Avg.
Iowa 158 q/156 v/3.3 GPA Rec
Hawaii- No GRE required
Baylor 163 q/163 v Avg
Virginia 155 q/153 v Rec
USC 158 q/ 162 v Avg
NYU 165 q/162v/ 3.5 GPA Rec
Stony Brook 163 q/157 v Rec
 
Maximum Master's/Transfer Credit Accepted (in classes)
 
This is the maximum amount of Master's/Transfer credit programs will award. Please note that it is often up to the department's discretion to award or not award people credit for some or all of these courses. These decisions are also often not made until well after you have entered the program.
 
Princeton- Dept Discretion
Columbia- Dept Discretion
UCLA- 6 Classes
Cornell- 3 Classes
Northwestern- 6 Classes
Texas- None
Emory- Start at Advanced Standing
Penn- 4 Classes
Virginia- Advanced Standing
Vanderbilt- Advanced Standing
Washington- 2 Classes
Ohio State-10 Classes
UNC- 6 Classes
Wisconsin- None
Duke- Dept. Discretion
Pitt- 8 Classes
Missouri- 8 Classes
Notre Dame- 8 Classes
UChicago- Dept Discretion
NYU- 8 Classes
UC Irvine- 6 Classes
USC- 8 Classes
Colorado- 3 Classes
 
How to Figure Out Fit
 
This is where things get somewhat subjective. Professors often move around, retire, ect, so it is not wise to attend a university where you believe that you could only work with one professor. Whether you want to apply to a program with one person who really fits your interest and one other who is less of a good fit, but not as well, is a decision you have to make. Most suggest that there should be at least two who you can work with, I applied only to programs where there was no less than three who shared my interests.
 
Go to department websites. Look at the faculty in your subfield. Look at their CVs, search them on Google Scholar. I'd suggest keeping track of them in a notebook and giving points based on how you feel about their work in relation to your own. By the end of this process, you will have a sense of departments that are good for your interests and those that are not.
 
Placement
This is a tricky thing to measure, but you should absolutely take placement into account before you apply. Some departments have very good data on placements (Michigan, WashU, Notre Dame, UNC to name a few), but you have to dig for it. What will shock some is how little the percentage of graduates placed varies from school to school based on it's rank, particularly if you take attrition into account. Based on their own data, at Michigan (USN #4), a starting PhD student has about a 40 percent chance of finishing the program and finding a Tenure Track job within five years of degree completion. At WashU (#19), a starting PhD student has about a 40 percent chance of finishing their degree and finding a Tenure Track job within five years thereafter. What about Notre Dame (#37)? A starting PhD student has about a 40 percent chance of finishing their degree and finding a Tenure Track job within five years of completion. This is not to say that placement does not vary, just that rank is not as big of a factor in whether or not you will get a job as some say.
 
APSA’s studies of placement backs me up on this one:
http://www.apsanet.org/RESOURCES/Data-on-the-Profession
 
Some years the schools in the NRC’s 20-40 and 40-60 range actually have better initial placement rates than those in the 1-20 range.
 
Where rank makes a difference, this study as well as the Oprisko data shows, is the types of institutions one gets placed at. If you absolutely need to get a job at an R1 PhD granting institution or this whole endeavor is not worth it for you, you might be best sticking to top 20 programs (but still do your homework on their placement). Otherwise, if you are fine ending up at an R3, non selective liberal arts college or a directional school, you have a lot more options.
 
So how do you determine a schools placement if this data is not readily available to you? Look on the department’s placement page. You can divide the number of total placements (TT, TT+nonTT, R1 jobs, jobs you would want to take, however you want to break it down) over a set period of time (5-7 years is advisable) and either divide it by the total number of grad students currently in the program (data which you can also usually find on the departments website) or by the planned incoming cohort multiplied by the number of years you are counting placements for (again, 5-7 is advisable). Just make sure you keep your process consistent. There will be some inevitable noise, but this should do enough to let you know what programs look good and which you should stay away from.  You may find that some 'top’ programs do a bad job of placing people, whereas some 'midteirs’ do an excellent job. If you focus on R1 placements, you will likely find that the rankings are excellent predictors.
 
Conclusion
So that just about wraps it up. I hope this advice has been useful. Best of luck to all of you.

 

Dear new PhD applicants in Political Science,
 
I am writing this post to provide you with a centralized source of information to help you make decisions about where to apply. I decided to provide you with this source because this information was not available to me in any sort of organized fashion, meaning that I had to find and organize it myself. I wish a resource such as this had been available to me when I began applying.  This does not mean that you will not need to do research on the programs to which you consider applying. There is some information that I simply cannot provide you with, such as up to date data on placement rates or how well your research interests match with the departments you are considering. These are among the most important factors you will consider. While I will walk you through how one can go about making these calculations, the main point of this post is to provide you with a starting point- useful data to help you begin to make decisions about where you will apply.
 
Useful Links
 
Rankings
 
The first thing I should say about rankings are that they are only a short cut. There is a lot more noise than one would like. I encourage everyone to ensure that the department in question is placing people rather than assume it blindly because of the rankings (more on that later). There are three main rankings political scientists look at:
 
The NRC
https://www.chronicle.com/article/NRC-Rankings-Overview-/124714
 
Methodology: the NRC rankings use several different methodologies based on multiple objective criteria to determine their five different sets of rankings. The S-Rankings use some 20 different factors that scholars say are important such as faculty research productivity, student completion rates and funding. The Research Rankings are based on measures of the departments research productivity. The Student Rankings are based on measures of student outcomes and quality of life while in the department. The Diversity Rankings are based on measures of diversity. The R-Rankings are a regression model trying to determine the departments that look most like the departments the Scholars Model likes.
 
Pros:
A lot of objective data went into these rankings.
The multi-dimensionality of the rankings allow you to weigh the different dimensions as you see fit. EG if you care more about research productivity than student outcomes, you can look at the Research Rankings and weigh them in your decision of where to apply to.
The S-Rankings most closely resemble the 5-year placement rates I saw when deciding where to apply of any ranking is (including US News and Oprisko)
Cons
Equivocal: there is a lot of noise, and they show it to you. Programs don't have ranks, but rather rank ranges and there are five different sets of rankings.
Infrequent: this set of rankings came out in 2010, the last NRC rankings before that came out in 1998. While I do not think that these rankings are so excited old that they are not useful, a lot can change in eight years.
 
2) US News Rankings
https://www.usnews.com/best-graduate-schools/top-humanities-schools/political-science-rankings
 
Methodology: US News simply surveys scholars on the department reputation, asking them to rank them on a 1 to 5 scale, and ranks departments based on the results
 
Pros:
The most widely used rankings
The only rankings that take reputation into account
Cons:
Reputation is the only factor taken into account, so it could be said that the rankings are completely subjective
 
3) Oprisko
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2303567
 
Methodology: Oprisko looks at outcomes- R1 placements. He counts the number of PhDs from a given institution currently working at a PhD granting institution in Political Science. He comes up with two rankings from that- the raw total number of placements and the number of placement divided by faculty members (placement efficiency)
 
Pros
Makes student outcomes front and center
 
Cons:
Only uses R1 placements
The main rankings does not control for program size. The placement efficiency rankings, however, do.
 
Stipend Information
 
http://www.phdstipends.com
 
This website provides a searchable database of funding offers from various departments. Just search the name of a University and “Political Science” and something should come up.
 
Some of this data may be outdated, so pay attention to the year it was posted. Some schools may not have any data posted on this site. Funding offers may vary.  Better information may be available on the departments webpage. Nonetheless this is a very useful resource for information about funding.
 
When will I hear back?
 
https://forum.thegradcafe.com/topic/100449-decision-timelines-for-particular-universities-and-programs-derived-from-the-gradcafe-data-gregpa-distributions/?tab=comments#comment-1058542321
 
This link shows the timeline in which decisions have been made in the past. You could also search the gradcafe results forum to get a sense for when results will come through.
 
What should my Statement of Purpose look like?
 
http://grad.berkeley.edu/admissions/apply/statement-purpose/
 
Here is some useful advice for drafting a statement of purpose. Tailor it to your specific program. Mention Professors you'd like to work with and programs/institutes that might interest you. Also edit it as much as you possibly can. I made about ten drafts before finally sending it off.

 
GRE/GPA Info
 
Here is the GRE and GPA information on every school I could find. This data either is posted on the departments website or was about six months ago when I searched for it. Use this data to strategize where to apply. If you have a 155/155, it may not be wise to only apply to Stanford, Duke, Cal, UCSD and WashU, as a safety. However, do not let minor discrepancies discourage you from applying from your dream program. These stats are a small part of a number of factors that will determine your success in the application process. Use them to give you a rough idea of how you may fare, not as an absolute predictor of your success.
 
Stanford 163 q/166 v/3.8 GPA Recommended (Rec)
Duke 163 q/163 v/3.8 GPA Average (AVG)
UC Berkeley 161 q/158 v Rec
Northwestern 148 q/160 v Rec
Kansas 148 v/156 q/ 3.5 GPA Avg
UCSD 163 q/166 v/3.9 GPA Avg
Chicago 162 q/166 v/3.8 GPA Avg
Columbia 158 q/161 v/ 3.8 GPA Avg
Penn 161 q/165 v Avg
WashU-STL 161 q/159 v/3.9 GPA Avg
Colorado State 154 q/154 v/ 3.5 GPA Rec
UNLV 148 q/160 v/3.5 GPA Rec
Emory 160 q/160 v/ B+ (or Better) GPA Avg
Princeton 160 q/160 v/3.8 GPA Rec
Notre Dame 158 q/ 165 v Avg
Colorado 154 q/160 v Avg
Oregon 300 total GRE/3.0 GPA Rec
UC Riverside 307 total GRE/3.0 GPA Minimum
Washington 314 total GRE/3.4 GPA Rec
Oklahoma 154 q/153 v Avg.
Iowa 158 q/156 v/3.3 GPA Rec
Hawaii- No GRE required
Baylor 163 q/163 v Avg
Virginia 155 q/153 v Rec
USC 158 q/ 162 v Avg
NYU 165 q/162v/ 3.5 GPA Rec
Stony Brook 163 q/157 v Rec
 
Maximum Master's/Transfer Credit Accepted (in classes)
 
This is the maximum amount of Master's/Transfer credit programs will award. Please note that it is often up to the department's discretion to award or not award people credit for some or all of these courses. These decisions are also often not made until well after you have entered the program.
 
Princeton- Dept Discretion
Columbia- Dept Discretion
UCLA- 6 Classes
Cornell- 3 Classes
Northwestern- 6 Classes
Texas- None
Emory- Start at Advanced Standing
Penn- 4 Classes
Virginia- Advanced Standing
Vanderbilt- Advanced Standing
Washington- 2 Classes
Ohio State-10 Classes
UNC- 6 Classes
Wisconsin- None
Duke- Dept. Discretion
Pitt- 8 Classes
Missouri- 8 Classes
Notre Dame- 8 Classes
UChicago- Dept Discretion
NYU- 8 Classes
UC Irvine- 6 Classes
USC- 8 Classes
Colorado- 3 Classes
 
How to Figure Out Fit
 
This is where things get somewhat subjective. Professors often move around, retire, ect, so it is not wise to attend a university where you believe that you could only work with one professor. Whether you want to apply to a program with one person who really fits your interest and one other who is less of a good fit, but not as well, is a decision you have to make. Most suggest that there should be at least two who you can work with, I applied only to programs where there was no less than three who shared my interests.
 
Go to department websites. Look at the faculty in your subfield. Look at their CVs, search them on Google Scholar. I'd suggest keeping track of them in a notebook and giving points based on how you feel about their work in relation to your own. By the end of this process, you will have a sense of departments that are good for your interests and those that are not.
 
Placement
This is a tricky thing to measure, but you should absolutely take placement into account before you apply. Some departments have very good data on placements (Michigan, WashU, Notre Dame, UNC to name a few), but you have to dig for it. What will shock some is how little the percentage of graduates placed varies from school to school based on it's rank, particularly if you take attrition into account. Based on their own data, at Michigan (USN #4), a starting PhD student has about a 40 percent chance of finishing the program and finding a Tenure Track job within five years of degree completion. At WashU (#19), a starting PhD student has about a 40 percent chance of finishing their degree and finding a Tenure Track job within five years thereafter. What about Notre Dame (#37)? A starting PhD student has about a 40 percent chance of finishing their degree and finding a Tenure Track job within five years of completion. This is not to say that placement does not vary, just that rank is not as big of a factor in whether or not you will get a job as some say.
 
APSA’s studies of placement backs me up on this one:
http://www.apsanet.org/RESOURCES/Data-on-the-Profession
 
Some years the schools in the NRC’s 20-40 and 40-60 range actually have better initial placement rates than those in the 1-20 range.
 
Where rank makes a difference, this study as well as the Oprisko data shows, is the types of institutions one gets placed at. If you absolutely need to get a job at an R1 PhD granting institution or this whole endeavor is not worth it for you, you might be best sticking to top 20 programs (but still do your homework on their placement). Otherwise, if you are fine ending up at an R3, non selective liberal arts college or a directional school, you have a lot more options.
 
So how do you determine a schools placement if this data is not readily available to you? Look on the department’s placement page. You can divide the number of total placements (TT, TT+nonTT, R1 jobs, jobs you would want to take, however you want to break it down) over a set period of time (5-7 years is advisable) and either divide it by the total number of grad students currently in the program (data which you can also usually find on the departments website) or by the planned incoming cohort multiplied by the number of years you are counting placements for (again, 5-7 is advisable). Just make sure you keep your process consistent. There will be some inevitable noise, but this should do enough to let you know what programs look good and which you should stay away from.  You may find that some 'top’ programs do a bad job of placing people, whereas some 'midteirs’ do an excellent job. If you focus on R1 placements, you will likely find that the rankings are excellent predictors.
 
Conclusion
So that just about wraps it up. I hope this advice has been useful. Best of luck to all of you.

 

PROFILE:
Type of Undergrad Institution: Big State School with an Elite Political Science Department 
Major(s)/Minor(s): Political Science
Undergrad GPA: 3.10 (3.43 in major)
Type of Grad: MA in Political Science at a Regional/Directional Public School
Grad GPA: 3.88
GRE: 163 Q/158 V/ 4.5 AW
Any Special Courses: Took a grad seminar as an undergrad. Also a methods course in my MA program. 
Letters of Recommendation: Four, all from my grad institution. One professor who is semi-famous. Three Associate or Full, one Assistant 
Research Experience: An article under review at the time I applied. Four papers presented at five conferences (at the time I applied, now seven). Also, an RA-ship from my freshman year of college and an independent study project as an undergrad
Teaching Experience: I taught a discussion section at my MA institution, had an internship at a Community College (that I now teach at), TAd some seven intro to American Gov't classes and three upper division classes
Subfield/Research Interests: American Politics, namely Racial Politics and Constitutional Law
Other: I worked/interned in politics for a few years and had a journalistic publication

RESULTS:
Acceptances($$ or no $$): Notre Dame ($$), Missouri ($$), UC Irvine ($$) and Colorado (Funding Info Pending)
Waitlists: Washington University in St. Louis, USC, Brandeis
Rejections: Michigan, University of Washington (Seattle), Princeton
Pending:
Going to: Probably Notre Dame (pending visit/waitlist results)
 
LESSONS LEARNED:
 1) Take it from someone who was waitlisted three times this cycle- there is a lot of randomness to the process.
2) Don't put blind faith in the rankings.  Some high ranking programs don't place their grads very well, and some lower ranking one's do.
3) Fit, Fit, Fit. Make sure you're applying to places that fit your interests.
4). Don't sweat the small stuff after your app is in. I was accepted or waitlisted to multiple programs where my SOP had 5 to 6 typos.
5) It's a hard and stressful process. Make sure you start early and put your best foot forward. Above all else, only do this if you love it. Grad school is not for the faint of heart. You have to take joy from it or you will surely burn out.
SOP:
I effectively walked through my relationship with Politics and Political Science from the time I was 7 to now. I went through my extra-curricular involvement in politics as an undergrad, my time in my MA program and my research experience, explaining why I wanted to become a Professor and why I wanted to study the things I want to study. I devoted one paragraph to program fit for each application. 

Dear new PhD applicants in Political Science,
 
I am writing this post to provide you with a centralized source of information to help you make decisions about where to apply. I decided to provide you with this source because this information was not available to me in any sort of organized fashion, meaning that I had to find and organize it myself. I wish a resource such as this had been available to me when I began applying.  This does not mean that you will not need to do research on the programs to which you consider applying. There is some information that I simply cannot provide you with, such as up to date data on placement rates or how well your research interests match with the departments you are considering. These are among the most important factors you will consider. While I will walk you through how one can go about making these calculations, the main point of this post is to provide you with a starting point- useful data to help you begin to make decisions about where you will apply.
 
Useful Links
 
Rankings
 
The first thing I should say about rankings are that they are only a short cut. There is a lot more noise than one would like. I encourage everyone to ensure that the department in question is placing people rather than assume it blindly because of the rankings (more on that later). There are three main rankings political scientists look at:
 
The NRC
https://www.chronicle.com/article/NRC-Rankings-Overview-/124714
 
Methodology: the NRC rankings use several different methodologies based on multiple objective criteria to determine their five different sets of rankings. The S-Rankings use some 20 different factors that scholars say are important such as faculty research productivity, student completion rates and funding. The Research Rankings are based on measures of the departments research productivity. The Student Rankings are based on measures of student outcomes and quality of life while in the department. The Diversity Rankings are based on measures of diversity. The R-Rankings are a regression model trying to determine the departments that look most like the departments the Scholars Model likes.
 
Pros:
A lot of objective data went into these rankings.
The multi-dimensionality of the rankings allow you to weigh the different dimensions as you see fit. EG if you care more about research productivity than student outcomes, you can look at the Research Rankings and weigh them in your decision of where to apply to.
The S-Rankings most closely resemble the 5-year placement rates I saw when deciding where to apply of any ranking is (including US News and Oprisko)
Cons
Equivocal: there is a lot of noise, and they show it to you. Programs don't have ranks, but rather rank ranges and there are five different sets of rankings.
Infrequent: this set of rankings came out in 2010, the last NRC rankings before that came out in 1998. While I do not think that these rankings are so excited old that they are not useful, a lot can change in eight years.
 
2) US News Rankings
https://www.usnews.com/best-graduate-schools/top-humanities-schools/political-science-rankings
 
Methodology: US News simply surveys scholars on the department reputation, asking them to rank them on a 1 to 5 scale, and ranks departments based on the results
 
Pros:
The most widely used rankings
The only rankings that take reputation into account
Cons:
Reputation is the only factor taken into account, so it could be said that the rankings are completely subjective
 
3) Oprisko
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2303567
 
Methodology: Oprisko looks at outcomes- R1 placements. He counts the number of PhDs from a given institution currently working at a PhD granting institution in Political Science. He comes up with two rankings from that- the raw total number of placements and the number of placement divided by faculty members (placement efficiency)
 
Pros
Makes student outcomes front and center
 
Cons:
Only uses R1 placements
The main rankings does not control for program size. The placement efficiency rankings, however, do.
 
Stipend Information
 
http://www.phdstipends.com
 
This website provides a searchable database of funding offers from various departments. Just search the name of a University and “Political Science” and something should come up.
 
Some of this data may be outdated, so pay attention to the year it was posted. Some schools may not have any data posted on this site. Funding offers may vary.  Better information may be available on the departments webpage. Nonetheless this is a very useful resource for information about funding.
 
When will I hear back?
 
https://forum.thegradcafe.com/topic/100449-decision-timelines-for-particular-universities-and-programs-derived-from-the-gradcafe-data-gregpa-distributions/?tab=comments#comment-1058542321
 
This link shows the timeline in which decisions have been made in the past. You could also search the gradcafe results forum to get a sense for when results will come through.
 
What should my Statement of Purpose look like?
 
http://grad.berkeley.edu/admissions/apply/statement-purpose/
 
Here is some useful advice for drafting a statement of purpose. Tailor it to your specific program. Mention Professors you'd like to work with and programs/institutes that might interest you. Also edit it as much as you possibly can. I made about ten drafts before finally sending it off.

 
GRE/GPA Info
 
Here is the GRE and GPA information on every school I could find. This data either is posted on the departments website or was about six months ago when I searched for it. Use this data to strategize where to apply. If you have a 155/155, it may not be wise to only apply to Stanford, Duke, Cal, UCSD and WashU, as a safety. However, do not let minor discrepancies discourage you from applying from your dream program. These stats are a small part of a number of factors that will determine your success in the application process. Use them to give you a rough idea of how you may fare, not as an absolute predictor of your success.
 
Stanford 163 q/166 v/3.8 GPA Recommended (Rec)
Duke 163 q/163 v/3.8 GPA Average (AVG)
UC Berkeley 161 q/158 v Rec
Northwestern 148 q/160 v Rec
Kansas 148 v/156 q/ 3.5 GPA Avg
UCSD 163 q/166 v/3.9 GPA Avg
Chicago 162 q/166 v/3.8 GPA Avg
Columbia 158 q/161 v/ 3.8 GPA Avg
Penn 161 q/165 v Avg
WashU-STL 161 q/159 v/3.9 GPA Avg
Colorado State 154 q/154 v/ 3.5 GPA Rec
UNLV 148 q/160 v/3.5 GPA Rec
Emory 160 q/160 v/ B+ (or Better) GPA Avg
Princeton 160 q/160 v/3.8 GPA Rec
Notre Dame 158 q/ 165 v Avg
Colorado 154 q/160 v Avg
Oregon 300 total GRE/3.0 GPA Rec
UC Riverside 307 total GRE/3.0 GPA Minimum
Washington 314 total GRE/3.4 GPA Rec
Oklahoma 154 q/153 v Avg.
Iowa 158 q/156 v/3.3 GPA Rec
Hawaii- No GRE required
Baylor 163 q/163 v Avg
Virginia 155 q/153 v Rec
USC 158 q/ 162 v Avg
NYU 165 q/162v/ 3.5 GPA Rec
Stony Brook 163 q/157 v Rec
 
Maximum Master's/Transfer Credit Accepted (in classes)
 
This is the maximum amount of Master's/Transfer credit programs will award. Please note that it is often up to the department's discretion to award or not award people credit for some or all of these courses. These decisions are also often not made until well after you have entered the program.
 
Princeton- Dept Discretion
Columbia- Dept Discretion
UCLA- 6 Classes
Cornell- 3 Classes
Northwestern- 6 Classes
Texas- None
Emory- Start at Advanced Standing
Penn- 4 Classes
Virginia- Advanced Standing
Vanderbilt- Advanced Standing
Washington- 2 Classes
Ohio State-10 Classes
UNC- 6 Classes
Wisconsin- None
Duke- Dept. Discretion
Pitt- 8 Classes
Missouri- 8 Classes
Notre Dame- 8 Classes
UChicago- Dept Discretion
NYU- 8 Classes
UC Irvine- 6 Classes
USC- 8 Classes
Colorado- 3 Classes
 
How to Figure Out Fit
 
This is where things get somewhat subjective. Professors often move around, retire, ect, so it is not wise to attend a university where you believe that you could only work with one professor. Whether you want to apply to a program with one person who really fits your interest and one other who is less of a good fit, but not as well, is a decision you have to make. Most suggest that there should be at least two who you can work with, I applied only to programs where there was no less than three who shared my interests.
 
Go to department websites. Look at the faculty in your subfield. Look at their CVs, search them on Google Scholar. I'd suggest keeping track of them in a notebook and giving points based on how you feel about their work in relation to your own. By the end of this process, you will have a sense of departments that are good for your interests and those that are not.
 
Placement
This is a tricky thing to measure, but you should absolutely take placement into account before you apply. Some departments have very good data on placements (Michigan, WashU, Notre Dame, UNC to name a few), but you have to dig for it. What will shock some is how little the percentage of graduates placed varies from school to school based on it's rank, particularly if you take attrition into account. Based on their own data, at Michigan (USN #4), a starting PhD student has about a 40 percent chance of finishing the program and finding a Tenure Track job within five years of degree completion. At WashU (#19), a starting PhD student has about a 40 percent chance of finishing their degree and finding a Tenure Track job within five years thereafter. What about Notre Dame (#37)? A starting PhD student has about a 40 percent chance of finishing their degree and finding a Tenure Track job within five years of completion. This is not to say that placement does not vary, just that rank is not as big of a factor in whether or not you will get a job as some say.
 
APSA’s studies of placement backs me up on this one:
http://www.apsanet.org/RESOURCES/Data-on-the-Profession
 
Some years the schools in the NRC’s 20-40 and 40-60 range actually have better initial placement rates than those in the 1-20 range.
 
Where rank makes a difference, this study as well as the Oprisko data shows, is the types of institutions one gets placed at. If you absolutely need to get a job at an R1 PhD granting institution or this whole endeavor is not worth it for you, you might be best sticking to top 20 programs (but still do your homework on their placement). Otherwise, if you are fine ending up at an R3, non selective liberal arts college or a directional school, you have a lot more options.
 
So how do you determine a schools placement if this data is not readily available to you? Look on the department’s placement page. You can divide the number of total placements (TT, TT+nonTT, R1 jobs, jobs you would want to take, however you want to break it down) over a set period of time (5-7 years is advisable) and either divide it by the total number of grad students currently in the program (data which you can also usually find on the departments website) or by the planned incoming cohort multiplied by the number of years you are counting placements for (again, 5-7 is advisable). Just make sure you keep your process consistent. There will be some inevitable noise, but this should do enough to let you know what programs look good and which you should stay away from.  You may find that some 'top’ programs do a bad job of placing people, whereas some 'midteirs’ do an excellent job. If you focus on R1 placements, you will likely find that the rankings are excellent predictors.
 
Conclusion
So that just about wraps it up. I hope this advice has been useful. Best of luck to all of you.

 

Dear new PhD applicants in Political Science,
 
I am writing this post to provide you with a centralized source of information to help you make decisions about where to apply. I decided to provide you with this source because this information was not available to me in any sort of organized fashion, meaning that I had to find and organize it myself. I wish a resource such as this had been available to me when I began applying.  This does not mean that you will not need to do research on the programs to which you consider applying. There is some information that I simply cannot provide you with, such as up to date data on placement rates or how well your research interests match with the departments you are considering. These are among the most important factors you will consider. While I will walk you through how one can go about making these calculations, the main point of this post is to provide you with a starting point- useful data to help you begin to make decisions about where you will apply.
 
Useful Links
 
Rankings
 
The first thing I should say about rankings are that they are only a short cut. There is a lot more noise than one would like. I encourage everyone to ensure that the department in question is placing people rather than assume it blindly because of the rankings (more on that later). There are three main rankings political scientists look at:
 
The NRC
https://www.chronicle.com/article/NRC-Rankings-Overview-/124714
 
Methodology: the NRC rankings use several different methodologies based on multiple objective criteria to determine their five different sets of rankings. The S-Rankings use some 20 different factors that scholars say are important such as faculty research productivity, student completion rates and funding. The Research Rankings are based on measures of the departments research productivity. The Student Rankings are based on measures of student outcomes and quality of life while in the department. The Diversity Rankings are based on measures of diversity. The R-Rankings are a regression model trying to determine the departments that look most like the departments the Scholars Model likes.
 
Pros:
A lot of objective data went into these rankings.
The multi-dimensionality of the rankings allow you to weigh the different dimensions as you see fit. EG if you care more about research productivity than student outcomes, you can look at the Research Rankings and weigh them in your decision of where to apply to.
The S-Rankings most closely resemble the 5-year placement rates I saw when deciding where to apply of any ranking is (including US News and Oprisko)
Cons
Equivocal: there is a lot of noise, and they show it to you. Programs don't have ranks, but rather rank ranges and there are five different sets of rankings.
Infrequent: this set of rankings came out in 2010, the last NRC rankings before that came out in 1998. While I do not think that these rankings are so excited old that they are not useful, a lot can change in eight years.
 
2) US News Rankings
https://www.usnews.com/best-graduate-schools/top-humanities-schools/political-science-rankings
 
Methodology: US News simply surveys scholars on the department reputation, asking them to rank them on a 1 to 5 scale, and ranks departments based on the results
 
Pros:
The most widely used rankings
The only rankings that take reputation into account
Cons:
Reputation is the only factor taken into account, so it could be said that the rankings are completely subjective
 
3) Oprisko
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2303567
 
Methodology: Oprisko looks at outcomes- R1 placements. He counts the number of PhDs from a given institution currently working at a PhD granting institution in Political Science. He comes up with two rankings from that- the raw total number of placements and the number of placement divided by faculty members (placement efficiency)
 
Pros
Makes student outcomes front and center
 
Cons:
Only uses R1 placements
The main rankings does not control for program size. The placement efficiency rankings, however, do.
 
Stipend Information
 
http://www.phdstipends.com
 
This website provides a searchable database of funding offers from various departments. Just search the name of a University and “Political Science” and something should come up.
 
Some of this data may be outdated, so pay attention to the year it was posted. Some schools may not have any data posted on this site. Funding offers may vary.  Better information may be available on the departments webpage. Nonetheless this is a very useful resource for information about funding.
 
When will I hear back?
 
https://forum.thegradcafe.com/topic/100449-decision-timelines-for-particular-universities-and-programs-derived-from-the-gradcafe-data-gregpa-distributions/?tab=comments#comment-1058542321
 
This link shows the timeline in which decisions have been made in the past. You could also search the gradcafe results forum to get a sense for when results will come through.
 
What should my Statement of Purpose look like?
 
http://grad.berkeley.edu/admissions/apply/statement-purpose/
 
Here is some useful advice for drafting a statement of purpose. Tailor it to your specific program. Mention Professors you'd like to work with and programs/institutes that might interest you. Also edit it as much as you possibly can. I made about ten drafts before finally sending it off.

 
GRE/GPA Info
 
Here is the GRE and GPA information on every school I could find. This data either is posted on the departments website or was about six months ago when I searched for it. Use this data to strategize where to apply. If you have a 155/155, it may not be wise to only apply to Stanford, Duke, Cal, UCSD and WashU, as a safety. However, do not let minor discrepancies discourage you from applying from your dream program. These stats are a small part of a number of factors that will determine your success in the application process. Use them to give you a rough idea of how you may fare, not as an absolute predictor of your success.
 
Stanford 163 q/166 v/3.8 GPA Recommended (Rec)
Duke 163 q/163 v/3.8 GPA Average (AVG)
UC Berkeley 161 q/158 v Rec
Northwestern 148 q/160 v Rec
Kansas 148 v/156 q/ 3.5 GPA Avg
UCSD 163 q/166 v/3.9 GPA Avg
Chicago 162 q/166 v/3.8 GPA Avg
Columbia 158 q/161 v/ 3.8 GPA Avg
Penn 161 q/165 v Avg
WashU-STL 161 q/159 v/3.9 GPA Avg
Colorado State 154 q/154 v/ 3.5 GPA Rec
UNLV 148 q/160 v/3.5 GPA Rec
Emory 160 q/160 v/ B+ (or Better) GPA Avg
Princeton 160 q/160 v/3.8 GPA Rec
Notre Dame 158 q/ 165 v Avg
Colorado 154 q/160 v Avg
Oregon 300 total GRE/3.0 GPA Rec
UC Riverside 307 total GRE/3.0 GPA Minimum
Washington 314 total GRE/3.4 GPA Rec
Oklahoma 154 q/153 v Avg.
Iowa 158 q/156 v/3.3 GPA Rec
Hawaii- No GRE required
Baylor 163 q/163 v Avg
Virginia 155 q/153 v Rec
USC 158 q/ 162 v Avg
NYU 165 q/162v/ 3.5 GPA Rec
Stony Brook 163 q/157 v Rec
 
Maximum Master's/Transfer Credit Accepted (in classes)
 
This is the maximum amount of Master's/Transfer credit programs will award. Please note that it is often up to the department's discretion to award or not award people credit for some or all of these courses. These decisions are also often not made until well after you have entered the program.
 
Princeton- Dept Discretion
Columbia- Dept Discretion
UCLA- 6 Classes
Cornell- 3 Classes
Northwestern- 6 Classes
Texas- None
Emory- Start at Advanced Standing
Penn- 4 Classes
Virginia- Advanced Standing
Vanderbilt- Advanced Standing
Washington- 2 Classes
Ohio State-10 Classes
UNC- 6 Classes
Wisconsin- None
Duke- Dept. Discretion
Pitt- 8 Classes
Missouri- 8 Classes
Notre Dame- 8 Classes
UChicago- Dept Discretion
NYU- 8 Classes
UC Irvine- 6 Classes
USC- 8 Classes
Colorado- 3 Classes
 
How to Figure Out Fit
 
This is where things get somewhat subjective. Professors often move around, retire, ect, so it is not wise to attend a university where you believe that you could only work with one professor. Whether you want to apply to a program with one person who really fits your interest and one other who is less of a good fit, but not as well, is a decision you have to make. Most suggest that there should be at least two who you can work with, I applied only to programs where there was no less than three who shared my interests.
 
Go to department websites. Look at the faculty in your subfield. Look at their CVs, search them on Google Scholar. I'd suggest keeping track of them in a notebook and giving points based on how you feel about their work in relation to your own. By the end of this process, you will have a sense of departments that are good for your interests and those that are not.
 
Placement
This is a tricky thing to measure, but you should absolutely take placement into account before you apply. Some departments have very good data on placements (Michigan, WashU, Notre Dame, UNC to name a few), but you have to dig for it. What will shock some is how little the percentage of graduates placed varies from school to school based on it's rank, particularly if you take attrition into account. Based on their own data, at Michigan (USN #4), a starting PhD student has about a 40 percent chance of finishing the program and finding a Tenure Track job within five years of degree completion. At WashU (#19), a starting PhD student has about a 40 percent chance of finishing their degree and finding a Tenure Track job within five years thereafter. What about Notre Dame (#37)? A starting PhD student has about a 40 percent chance of finishing their degree and finding a Tenure Track job within five years of completion. This is not to say that placement does not vary, just that rank is not as big of a factor in whether or not you will get a job as some say.
 
APSA’s studies of placement backs me up on this one:
http://www.apsanet.org/RESOURCES/Data-on-the-Profession
 
Some years the schools in the NRC’s 20-40 and 40-60 range actually have better initial placement rates than those in the 1-20 range.
 
Where rank makes a difference, this study as well as the Oprisko data shows, is the types of institutions one gets placed at. If you absolutely need to get a job at an R1 PhD granting institution or this whole endeavor is not worth it for you, you might be best sticking to top 20 programs (but still do your homework on their placement). Otherwise, if you are fine ending up at an R3, non selective liberal arts college or a directional school, you have a lot more options.
 
So how do you determine a schools placement if this data is not readily available to you? Look on the department’s placement page. You can divide the number of total placements (TT, TT+nonTT, R1 jobs, jobs you would want to take, however you want to break it down) over a set period of time (5-7 years is advisable) and either divide it by the total number of grad students currently in the program (data which you can also usually find on the departments website) or by the planned incoming cohort multiplied by the number of years you are counting placements for (again, 5-7 is advisable). Just make sure you keep your process consistent. There will be some inevitable noise, but this should do enough to let you know what programs look good and which you should stay away from.  You may find that some 'top’ programs do a bad job of placing people, whereas some 'midteirs’ do an excellent job. If you focus on R1 placements, you will likely find that the rankings are excellent predictors.
 
Conclusion
So that just about wraps it up. I hope this advice has been useful. Best of luck to all of you.

 

Dear new PhD applicants in Political Science,
 
I am writing this post to provide you with a centralized source of information to help you make decisions about where to apply. I decided to provide you with this source because this information was not available to me in any sort of organized fashion, meaning that I had to find and organize it myself. I wish a resource such as this had been available to me when I began applying.  This does not mean that you will not need to do research on the programs to which you consider applying. There is some information that I simply cannot provide you with, such as up to date data on placement rates or how well your research interests match with the departments you are considering. These are among the most important factors you will consider. While I will walk you through how one can go about making these calculations, the main point of this post is to provide you with a starting point- useful data to help you begin to make decisions about where you will apply.
 
Useful Links
 
Rankings
 
The first thing I should say about rankings are that they are only a short cut. There is a lot more noise than one would like. I encourage everyone to ensure that the department in question is placing people rather than assume it blindly because of the rankings (more on that later). There are three main rankings political scientists look at:
 
The NRC
https://www.chronicle.com/article/NRC-Rankings-Overview-/124714
 
Methodology: the NRC rankings use several different methodologies based on multiple objective criteria to determine their five different sets of rankings. The S-Rankings use some 20 different factors that scholars say are important such as faculty research productivity, student completion rates and funding. The Research Rankings are based on measures of the departments research productivity. The Student Rankings are based on measures of student outcomes and quality of life while in the department. The Diversity Rankings are based on measures of diversity. The R-Rankings are a regression model trying to determine the departments that look most like the departments the Scholars Model likes.
 
Pros:
A lot of objective data went into these rankings.
The multi-dimensionality of the rankings allow you to weigh the different dimensions as you see fit. EG if you care more about research productivity than student outcomes, you can look at the Research Rankings and weigh them in your decision of where to apply to.
The S-Rankings most closely resemble the 5-year placement rates I saw when deciding where to apply of any ranking is (including US News and Oprisko)
Cons
Equivocal: there is a lot of noise, and they show it to you. Programs don't have ranks, but rather rank ranges and there are five different sets of rankings.
Infrequent: this set of rankings came out in 2010, the last NRC rankings before that came out in 1998. While I do not think that these rankings are so excited old that they are not useful, a lot can change in eight years.
 
2) US News Rankings
https://www.usnews.com/best-graduate-schools/top-humanities-schools/political-science-rankings
 
Methodology: US News simply surveys scholars on the department reputation, asking them to rank them on a 1 to 5 scale, and ranks departments based on the results
 
Pros:
The most widely used rankings
The only rankings that take reputation into account
Cons:
Reputation is the only factor taken into account, so it could be said that the rankings are completely subjective
 
3) Oprisko
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2303567
 
Methodology: Oprisko looks at outcomes- R1 placements. He counts the number of PhDs from a given institution currently working at a PhD granting institution in Political Science. He comes up with two rankings from that- the raw total number of placements and the number of placement divided by faculty members (placement efficiency)
 
Pros
Makes student outcomes front and center
 
Cons:
Only uses R1 placements
The main rankings does not control for program size. The placement efficiency rankings, however, do.
 
Stipend Information
 
http://www.phdstipends.com
 
This website provides a searchable database of funding offers from various departments. Just search the name of a University and “Political Science” and something should come up.
 
Some of this data may be outdated, so pay attention to the year it was posted. Some schools may not have any data posted on this site. Funding offers may vary.  Better information may be available on the departments webpage. Nonetheless this is a very useful resource for information about funding.
 
When will I hear back?
 
https://forum.thegradcafe.com/topic/100449-decision-timelines-for-particular-universities-and-programs-derived-from-the-gradcafe-data-gregpa-distributions/?tab=comments#comment-1058542321
 
This link shows the timeline in which decisions have been made in the past. You could also search the gradcafe results forum to get a sense for when results will come through.
 
What should my Statement of Purpose look like?
 
http://grad.berkeley.edu/admissions/apply/statement-purpose/
 
Here is some useful advice for drafting a statement of purpose. Tailor it to your specific program. Mention Professors you'd like to work with and programs/institutes that might interest you. Also edit it as much as you possibly can. I made about ten drafts before finally sending it off.

 
GRE/GPA Info
 
Here is the GRE and GPA information on every school I could find. This data either is posted on the departments website or was about six months ago when I searched for it. Use this data to strategize where to apply. If you have a 155/155, it may not be wise to only apply to Stanford, Duke, Cal, UCSD and WashU, as a safety. However, do not let minor discrepancies discourage you from applying from your dream program. These stats are a small part of a number of factors that will determine your success in the application process. Use them to give you a rough idea of how you may fare, not as an absolute predictor of your success.
 
Stanford 163 q/166 v/3.8 GPA Recommended (Rec)
Duke 163 q/163 v/3.8 GPA Average (AVG)
UC Berkeley 161 q/158 v Rec
Northwestern 148 q/160 v Rec
Kansas 148 v/156 q/ 3.5 GPA Avg
UCSD 163 q/166 v/3.9 GPA Avg
Chicago 162 q/166 v/3.8 GPA Avg
Columbia 158 q/161 v/ 3.8 GPA Avg
Penn 161 q/165 v Avg
WashU-STL 161 q/159 v/3.9 GPA Avg
Colorado State 154 q/154 v/ 3.5 GPA Rec
UNLV 148 q/160 v/3.5 GPA Rec
Emory 160 q/160 v/ B+ (or Better) GPA Avg
Princeton 160 q/160 v/3.8 GPA Rec
Notre Dame 158 q/ 165 v Avg
Colorado 154 q/160 v Avg
Oregon 300 total GRE/3.0 GPA Rec
UC Riverside 307 total GRE/3.0 GPA Minimum
Washington 314 total GRE/3.4 GPA Rec
Oklahoma 154 q/153 v Avg.
Iowa 158 q/156 v/3.3 GPA Rec
Hawaii- No GRE required
Baylor 163 q/163 v Avg
Virginia 155 q/153 v Rec
USC 158 q/ 162 v Avg
NYU 165 q/162v/ 3.5 GPA Rec
Stony Brook 163 q/157 v Rec
 
Maximum Master's/Transfer Credit Accepted (in classes)
 
This is the maximum amount of Master's/Transfer credit programs will award. Please note that it is often up to the department's discretion to award or not award people credit for some or all of these courses. These decisions are also often not made until well after you have entered the program.
 
Princeton- Dept Discretion
Columbia- Dept Discretion
UCLA- 6 Classes
Cornell- 3 Classes
Northwestern- 6 Classes
Texas- None
Emory- Start at Advanced Standing
Penn- 4 Classes
Virginia- Advanced Standing
Vanderbilt- Advanced Standing
Washington- 2 Classes
Ohio State-10 Classes
UNC- 6 Classes
Wisconsin- None
Duke- Dept. Discretion
Pitt- 8 Classes
Missouri- 8 Classes
Notre Dame- 8 Classes
UChicago- Dept Discretion
NYU- 8 Classes
UC Irvine- 6 Classes
USC- 8 Classes
Colorado- 3 Classes
 
How to Figure Out Fit
 
This is where things get somewhat subjective. Professors often move around, retire, ect, so it is not wise to attend a university where you believe that you could only work with one professor. Whether you want to apply to a program with one person who really fits your interest and one other who is less of a good fit, but not as well, is a decision you have to make. Most suggest that there should be at least two who you can work with, I applied only to programs where there was no less than three who shared my interests.
 
Go to department websites. Look at the faculty in your subfield. Look at their CVs, search them on Google Scholar. I'd suggest keeping track of them in a notebook and giving points based on how you feel about their work in relation to your own. By the end of this process, you will have a sense of departments that are good for your interests and those that are not.
 
Placement
This is a tricky thing to measure, but you should absolutely take placement into account before you apply. Some departments have very good data on placements (Michigan, WashU, Notre Dame, UNC to name a few), but you have to dig for it. What will shock some is how little the percentage of graduates placed varies from school to school based on it's rank, particularly if you take attrition into account. Based on their own data, at Michigan (USN #4), a starting PhD student has about a 40 percent chance of finishing the program and finding a Tenure Track job within five years of degree completion. At WashU (#19), a starting PhD student has about a 40 percent chance of finishing their degree and finding a Tenure Track job within five years thereafter. What about Notre Dame (#37)? A starting PhD student has about a 40 percent chance of finishing their degree and finding a Tenure Track job within five years of completion. This is not to say that placement does not vary, just that rank is not as big of a factor in whether or not you will get a job as some say.
 
APSA’s studies of placement backs me up on this one:
http://www.apsanet.org/RESOURCES/Data-on-the-Profession
 
Some years the schools in the NRC’s 20-40 and 40-60 range actually have better initial placement rates than those in the 1-20 range.
 
Where rank makes a difference, this study as well as the Oprisko data shows, is the types of institutions one gets placed at. If you absolutely need to get a job at an R1 PhD granting institution or this whole endeavor is not worth it for you, you might be best sticking to top 20 programs (but still do your homework on their placement). Otherwise, if you are fine ending up at an R3, non selective liberal arts college or a directional school, you have a lot more options.
 
So how do you determine a schools placement if this data is not readily available to you? Look on the department’s placement page. You can divide the number of total placements (TT, TT+nonTT, R1 jobs, jobs you would want to take, however you want to break it down) over a set period of time (5-7 years is advisable) and either divide it by the total number of grad students currently in the program (data which you can also usually find on the departments website) or by the planned incoming cohort multiplied by the number of years you are counting placements for (again, 5-7 is advisable). Just make sure you keep your process consistent. There will be some inevitable noise, but this should do enough to let you know what programs look good and which you should stay away from.  You may find that some 'top’ programs do a bad job of placing people, whereas some 'midteirs’ do an excellent job. If you focus on R1 placements, you will likely find that the rankings are excellent predictors.
 
Conclusion
So that just about wraps it up. I hope this advice has been useful. Best of luck to all of you.

 

Dear new PhD applicants in Political Science,
 
I am writing this post to provide you with a centralized source of information to help you make decisions about where to apply. I decided to provide you with this source because this information was not available to me in any sort of organized fashion, meaning that I had to find and organize it myself. I wish a resource such as this had been available to me when I began applying.  This does not mean that you will not need to do research on the programs to which you consider applying. There is some information that I simply cannot provide you with, such as up to date data on placement rates or how well your research interests match with the departments you are considering. These are among the most important factors you will consider. While I will walk you through how one can go about making these calculations, the main point of this post is to provide you with a starting point- useful data to help you begin to make decisions about where you will apply.
 
Useful Links
 
Rankings
 
The first thing I should say about rankings are that they are only a short cut. There is a lot more noise than one would like. I encourage everyone to ensure that the department in question is placing people rather than assume it blindly because of the rankings (more on that later). There are three main rankings political scientists look at:
 
The NRC
https://www.chronicle.com/article/NRC-Rankings-Overview-/124714
 
Methodology: the NRC rankings use several different methodologies based on multiple objective criteria to determine their five different sets of rankings. The S-Rankings use some 20 different factors that scholars say are important such as faculty research productivity, student completion rates and funding. The Research Rankings are based on measures of the departments research productivity. The Student Rankings are based on measures of student outcomes and quality of life while in the department. The Diversity Rankings are based on measures of diversity. The R-Rankings are a regression model trying to determine the departments that look most like the departments the Scholars Model likes.
 
Pros:
A lot of objective data went into these rankings.
The multi-dimensionality of the rankings allow you to weigh the different dimensions as you see fit. EG if you care more about research productivity than student outcomes, you can look at the Research Rankings and weigh them in your decision of where to apply to.
The S-Rankings most closely resemble the 5-year placement rates I saw when deciding where to apply of any ranking is (including US News and Oprisko)
Cons
Equivocal: there is a lot of noise, and they show it to you. Programs don't have ranks, but rather rank ranges and there are five different sets of rankings.
Infrequent: this set of rankings came out in 2010, the last NRC rankings before that came out in 1998. While I do not think that these rankings are so excited old that they are not useful, a lot can change in eight years.
 
2) US News Rankings
https://www.usnews.com/best-graduate-schools/top-humanities-schools/political-science-rankings
 
Methodology: US News simply surveys scholars on the department reputation, asking them to rank them on a 1 to 5 scale, and ranks departments based on the results
 
Pros:
The most widely used rankings
The only rankings that take reputation into account
Cons:
Reputation is the only factor taken into account, so it could be said that the rankings are completely subjective
 
3) Oprisko
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2303567
 
Methodology: Oprisko looks at outcomes- R1 placements. He counts the number of PhDs from a given institution currently working at a PhD granting institution in Political Science. He comes up with two rankings from that- the raw total number of placements and the number of placement divided by faculty members (placement efficiency)
 
Pros
Makes student outcomes front and center
 
Cons:
Only uses R1 placements
The main rankings does not control for program size. The placement efficiency rankings, however, do.
 
Stipend Information
 
http://www.phdstipends.com
 
This website provides a searchable database of funding offers from various departments. Just search the name of a University and “Political Science” and something should come up.
 
Some of this data may be outdated, so pay attention to the year it was posted. Some schools may not have any data posted on this site. Funding offers may vary.  Better information may be available on the departments webpage. Nonetheless this is a very useful resource for information about funding.
 
When will I hear back?
 
https://forum.thegradcafe.com/topic/100449-decision-timelines-for-particular-universities-and-programs-derived-from-the-gradcafe-data-gregpa-distributions/?tab=comments#comment-1058542321
 
This link shows the timeline in which decisions have been made in the past. You could also search the gradcafe results forum to get a sense for when results will come through.
 
What should my Statement of Purpose look like?
 
http://grad.berkeley.edu/admissions/apply/statement-purpose/
 
Here is some useful advice for drafting a statement of purpose. Tailor it to your specific program. Mention Professors you'd like to work with and programs/institutes that might interest you. Also edit it as much as you possibly can. I made about ten drafts before finally sending it off.

 
GRE/GPA Info
 
Here is the GRE and GPA information on every school I could find. This data either is posted on the departments website or was about six months ago when I searched for it. Use this data to strategize where to apply. If you have a 155/155, it may not be wise to only apply to Stanford, Duke, Cal, UCSD and WashU, as a safety. However, do not let minor discrepancies discourage you from applying from your dream program. These stats are a small part of a number of factors that will determine your success in the application process. Use them to give you a rough idea of how you may fare, not as an absolute predictor of your success.
 
Stanford 163 q/166 v/3.8 GPA Recommended (Rec)
Duke 163 q/163 v/3.8 GPA Average (AVG)
UC Berkeley 161 q/158 v Rec
Northwestern 148 q/160 v Rec
Kansas 148 v/156 q/ 3.5 GPA Avg
UCSD 163 q/166 v/3.9 GPA Avg
Chicago 162 q/166 v/3.8 GPA Avg
Columbia 158 q/161 v/ 3.8 GPA Avg
Penn 161 q/165 v Avg
WashU-STL 161 q/159 v/3.9 GPA Avg
Colorado State 154 q/154 v/ 3.5 GPA Rec
UNLV 148 q/160 v/3.5 GPA Rec
Emory 160 q/160 v/ B+ (or Better) GPA Avg
Princeton 160 q/160 v/3.8 GPA Rec
Notre Dame 158 q/ 165 v Avg
Colorado 154 q/160 v Avg
Oregon 300 total GRE/3.0 GPA Rec
UC Riverside 307 total GRE/3.0 GPA Minimum
Washington 314 total GRE/3.4 GPA Rec
Oklahoma 154 q/153 v Avg.
Iowa 158 q/156 v/3.3 GPA Rec
Hawaii- No GRE required
Baylor 163 q/163 v Avg
Virginia 155 q/153 v Rec
USC 158 q/ 162 v Avg
NYU 165 q/162v/ 3.5 GPA Rec
Stony Brook 163 q/157 v Rec
 
Maximum Master's/Transfer Credit Accepted (in classes)
 
This is the maximum amount of Master's/Transfer credit programs will award. Please note that it is often up to the department's discretion to award or not award people credit for some or all of these courses. These decisions are also often not made until well after you have entered the program.
 
Princeton- Dept Discretion
Columbia- Dept Discretion
UCLA- 6 Classes
Cornell- 3 Classes
Northwestern- 6 Classes
Texas- None
Emory- Start at Advanced Standing
Penn- 4 Classes
Virginia- Advanced Standing
Vanderbilt- Advanced Standing
Washington- 2 Classes
Ohio State-10 Classes
UNC- 6 Classes
Wisconsin- None
Duke- Dept. Discretion
Pitt- 8 Classes
Missouri- 8 Classes
Notre Dame- 8 Classes
UChicago- Dept Discretion
NYU- 8 Classes
UC Irvine- 6 Classes
USC- 8 Classes
Colorado- 3 Classes
 
How to Figure Out Fit
 
This is where things get somewhat subjective. Professors often move around, retire, ect, so it is not wise to attend a university where you believe that you could only work with one professor. Whether you want to apply to a program with one person who really fits your interest and one other who is less of a good fit, but not as well, is a decision you have to make. Most suggest that there should be at least two who you can work with, I applied only to programs where there was no less than three who shared my interests.
 
Go to department websites. Look at the faculty in your subfield. Look at their CVs, search them on Google Scholar. I'd suggest keeping track of them in a notebook and giving points based on how you feel about their work in relation to your own. By the end of this process, you will have a sense of departments that are good for your interests and those that are not.
 
Placement
This is a tricky thing to measure, but you should absolutely take placement into account before you apply. Some departments have very good data on placements (Michigan, WashU, Notre Dame, UNC to name a few), but you have to dig for it. What will shock some is how little the percentage of graduates placed varies from school to school based on it's rank, particularly if you take attrition into account. Based on their own data, at Michigan (USN #4), a starting PhD student has about a 40 percent chance of finishing the program and finding a Tenure Track job within five years of degree completion. At WashU (#19), a starting PhD student has about a 40 percent chance of finishing their degree and finding a Tenure Track job within five years thereafter. What about Notre Dame (#37)? A starting PhD student has about a 40 percent chance of finishing their degree and finding a Tenure Track job within five years of completion. This is not to say that placement does not vary, just that rank is not as big of a factor in whether or not you will get a job as some say.
 
APSA’s studies of placement backs me up on this one:
http://www.apsanet.org/RESOURCES/Data-on-the-Profession
 
Some years the schools in the NRC’s 20-40 and 40-60 range actually have better initial placement rates than those in the 1-20 range.
 
Where rank makes a difference, this study as well as the Oprisko data shows, is the types of institutions one gets placed at. If you absolutely need to get a job at an R1 PhD granting institution or this whole endeavor is not worth it for you, you might be best sticking to top 20 programs (but still do your homework on their placement). Otherwise, if you are fine ending up at an R3, non selective liberal arts college or a directional school, you have a lot more options.
 
So how do you determine a schools placement if this data is not readily available to you? Look on the department’s placement page. You can divide the number of total placements (TT, TT+nonTT, R1 jobs, jobs you would want to take, however you want to break it down) over a set period of time (5-7 years is advisable) and either divide it by the total number of grad students currently in the program (data which you can also usually find on the departments website) or by the planned incoming cohort multiplied by the number of years you are counting placements for (again, 5-7 is advisable). Just make sure you keep your process consistent. There will be some inevitable noise, but this should do enough to let you know what programs look good and which you should stay away from.  You may find that some 'top’ programs do a bad job of placing people, whereas some 'midteirs’ do an excellent job. If you focus on R1 placements, you will likely find that the rankings are excellent predictors.
 
Conclusion
So that just about wraps it up. I hope this advice has been useful. Best of luck to all of you.

 

There is a lot of stress and everything going around right now, so to make you guys feel a little better I want to tell you my story. 
I was an AP scholar with distinction in high school and entered to one of the best public universities in the country with sophomore standing, but couldn't even get into my state's flagship (Cal is tough to get into). Once I got to college I struggled academically and put more focus on extra curriculars. At one point I had a 2.6 GPA. But I began to turn it around about the time I started interning in the state legislature. I thought my academic career would end with undergrad until I wanted to write a senior thesis and the Political Science department convinced me to take a grad seminar instead. I loved it, but I didn't do particularly well. I got an AB, which is like the B+/A- range at my undergrad institution. I realized that I wanted to go back to grad school, but thought that this was another 5 to 10 years or so away.
Then I graduated. My first job out of college was working on my last political campaign, and I hate campaign work, so I was miserable. I decided to move back home. I was unemployed for six months until I got a job in a law firm that I also hated. I decided to go back to grad school a lot sooner than I expected, but I knew what I wanted to do- teach undergrads.
So I enrolled in the closest MA program to my house. When I got there, I put in the work and I excelled. I earned a 3.9 GPA, presented work at seven different conferences and became the first student in the program's history to get an article under peer review (though I have yet to publish anything). 
Now, I'm 24. I'm have a master's. I have been admitted to three PhD programs already and I am starting a semester long job as an adjunct professor at a local Community College. If you had told me at basically any point in my undergrad career that I could achieve these things so quickly, I would not have believed you. Is my first job out of grad school going to be at NYU? Probably not. But I'm still proud of how far I have come and I know I have it in me to go farther.
So I know rejection stings. I hope no one strikes out on the cycle, but some of us may. But above all else, pick yourself up, lick your wounds and keep going! Maybe some of us will decide that we don't want to be academics after all. That's okay as long as you do what you love and go as far as you can with it. Your life isn't over because you didn't get into Princeton or even if you don't get in anywhere. If the latter is the case, work hard and either try again next cycle or go do something else you like. This is a particularly tough profession, but it's tough to do anything well. We have to be resilient. I want to remind people who are being rejected from top schools that there are plenty of good programs and those who see the rejections piling up without an acceptance that all it takes is one! So please, please, please, don't lose hope.

Dear new PhD applicants in Political Science,
 
I am writing this post to provide you with a centralized source of information to help you make decisions about where to apply. I decided to provide you with this source because this information was not available to me in any sort of organized fashion, meaning that I had to find and organize it myself. I wish a resource such as this had been available to me when I began applying.  This does not mean that you will not need to do research on the programs to which you consider applying. There is some information that I simply cannot provide you with, such as up to date data on placement rates or how well your research interests match with the departments you are considering. These are among the most important factors you will consider. While I will walk you through how one can go about making these calculations, the main point of this post is to provide you with a starting point- useful data to help you begin to make decisions about where you will apply.
 
Useful Links
 
Rankings
 
The first thing I should say about rankings are that they are only a short cut. There is a lot more noise than one would like. I encourage everyone to ensure that the department in question is placing people rather than assume it blindly because of the rankings (more on that later). There are three main rankings political scientists look at:
 
The NRC
https://www.chronicle.com/article/NRC-Rankings-Overview-/124714
 
Methodology: the NRC rankings use several different methodologies based on multiple objective criteria to determine their five different sets of rankings. The S-Rankings use some 20 different factors that scholars say are important such as faculty research productivity, student completion rates and funding. The Research Rankings are based on measures of the departments research productivity. The Student Rankings are based on measures of student outcomes and quality of life while in the department. The Diversity Rankings are based on measures of diversity. The R-Rankings are a regression model trying to determine the departments that look most like the departments the Scholars Model likes.
 
Pros:
A lot of objective data went into these rankings.
The multi-dimensionality of the rankings allow you to weigh the different dimensions as you see fit. EG if you care more about research productivity than student outcomes, you can look at the Research Rankings and weigh them in your decision of where to apply to.
The S-Rankings most closely resemble the 5-year placement rates I saw when deciding where to apply of any ranking is (including US News and Oprisko)
Cons
Equivocal: there is a lot of noise, and they show it to you. Programs don't have ranks, but rather rank ranges and there are five different sets of rankings.
Infrequent: this set of rankings came out in 2010, the last NRC rankings before that came out in 1998. While I do not think that these rankings are so excited old that they are not useful, a lot can change in eight years.
 
2) US News Rankings
https://www.usnews.com/best-graduate-schools/top-humanities-schools/political-science-rankings
 
Methodology: US News simply surveys scholars on the department reputation, asking them to rank them on a 1 to 5 scale, and ranks departments based on the results
 
Pros:
The most widely used rankings
The only rankings that take reputation into account
Cons:
Reputation is the only factor taken into account, so it could be said that the rankings are completely subjective
 
3) Oprisko
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2303567
 
Methodology: Oprisko looks at outcomes- R1 placements. He counts the number of PhDs from a given institution currently working at a PhD granting institution in Political Science. He comes up with two rankings from that- the raw total number of placements and the number of placement divided by faculty members (placement efficiency)
 
Pros
Makes student outcomes front and center
 
Cons:
Only uses R1 placements
The main rankings does not control for program size. The placement efficiency rankings, however, do.
 
Stipend Information
 
http://www.phdstipends.com
 
This website provides a searchable database of funding offers from various departments. Just search the name of a University and “Political Science” and something should come up.
 
Some of this data may be outdated, so pay attention to the year it was posted. Some schools may not have any data posted on this site. Funding offers may vary.  Better information may be available on the departments webpage. Nonetheless this is a very useful resource for information about funding.
 
When will I hear back?
 
https://forum.thegradcafe.com/topic/100449-decision-timelines-for-particular-universities-and-programs-derived-from-the-gradcafe-data-gregpa-distributions/?tab=comments#comment-1058542321
 
This link shows the timeline in which decisions have been made in the past. You could also search the gradcafe results forum to get a sense for when results will come through.
 
What should my Statement of Purpose look like?
 
http://grad.berkeley.edu/admissions/apply/statement-purpose/
 
Here is some useful advice for drafting a statement of purpose. Tailor it to your specific program. Mention Professors you'd like to work with and programs/institutes that might interest you. Also edit it as much as you possibly can. I made about ten drafts before finally sending it off.

 
GRE/GPA Info
 
Here is the GRE and GPA information on every school I could find. This data either is posted on the departments website or was about six months ago when I searched for it. Use this data to strategize where to apply. If you have a 155/155, it may not be wise to only apply to Stanford, Duke, Cal, UCSD and WashU, as a safety. However, do not let minor discrepancies discourage you from applying from your dream program. These stats are a small part of a number of factors that will determine your success in the application process. Use them to give you a rough idea of how you may fare, not as an absolute predictor of your success.
 
Stanford 163 q/166 v/3.8 GPA Recommended (Rec)
Duke 163 q/163 v/3.8 GPA Average (AVG)
UC Berkeley 161 q/158 v Rec
Northwestern 148 q/160 v Rec
Kansas 148 v/156 q/ 3.5 GPA Avg
UCSD 163 q/166 v/3.9 GPA Avg
Chicago 162 q/166 v/3.8 GPA Avg
Columbia 158 q/161 v/ 3.8 GPA Avg
Penn 161 q/165 v Avg
WashU-STL 161 q/159 v/3.9 GPA Avg
Colorado State 154 q/154 v/ 3.5 GPA Rec
UNLV 148 q/160 v/3.5 GPA Rec
Emory 160 q/160 v/ B+ (or Better) GPA Avg
Princeton 160 q/160 v/3.8 GPA Rec
Notre Dame 158 q/ 165 v Avg
Colorado 154 q/160 v Avg
Oregon 300 total GRE/3.0 GPA Rec
UC Riverside 307 total GRE/3.0 GPA Minimum
Washington 314 total GRE/3.4 GPA Rec
Oklahoma 154 q/153 v Avg.
Iowa 158 q/156 v/3.3 GPA Rec
Hawaii- No GRE required
Baylor 163 q/163 v Avg
Virginia 155 q/153 v Rec
USC 158 q/ 162 v Avg
NYU 165 q/162v/ 3.5 GPA Rec
Stony Brook 163 q/157 v Rec
 
Maximum Master's/Transfer Credit Accepted (in classes)
 
This is the maximum amount of Master's/Transfer credit programs will award. Please note that it is often up to the department's discretion to award or not award people credit for some or all of these courses. These decisions are also often not made until well after you have entered the program.
 
Princeton- Dept Discretion
Columbia- Dept Discretion
UCLA- 6 Classes
Cornell- 3 Classes
Northwestern- 6 Classes
Texas- None
Emory- Start at Advanced Standing
Penn- 4 Classes
Virginia- Advanced Standing
Vanderbilt- Advanced Standing
Washington- 2 Classes
Ohio State-10 Classes
UNC- 6 Classes
Wisconsin- None
Duke- Dept. Discretion
Pitt- 8 Classes
Missouri- 8 Classes
Notre Dame- 8 Classes
UChicago- Dept Discretion
NYU- 8 Classes
UC Irvine- 6 Classes
USC- 8 Classes
Colorado- 3 Classes
 
How to Figure Out Fit
 
This is where things get somewhat subjective. Professors often move around, retire, ect, so it is not wise to attend a university where you believe that you could only work with one professor. Whether you want to apply to a program with one person who really fits your interest and one other who is less of a good fit, but not as well, is a decision you have to make. Most suggest that there should be at least two who you can work with, I applied only to programs where there was no less than three who shared my interests.
 
Go to department websites. Look at the faculty in your subfield. Look at their CVs, search them on Google Scholar. I'd suggest keeping track of them in a notebook and giving points based on how you feel about their work in relation to your own. By the end of this process, you will have a sense of departments that are good for your interests and those that are not.
 
Placement
This is a tricky thing to measure, but you should absolutely take placement into account before you apply. Some departments have very good data on placements (Michigan, WashU, Notre Dame, UNC to name a few), but you have to dig for it. What will shock some is how little the percentage of graduates placed varies from school to school based on it's rank, particularly if you take attrition into account. Based on their own data, at Michigan (USN #4), a starting PhD student has about a 40 percent chance of finishing the program and finding a Tenure Track job within five years of degree completion. At WashU (#19), a starting PhD student has about a 40 percent chance of finishing their degree and finding a Tenure Track job within five years thereafter. What about Notre Dame (#37)? A starting PhD student has about a 40 percent chance of finishing their degree and finding a Tenure Track job within five years of completion. This is not to say that placement does not vary, just that rank is not as big of a factor in whether or not you will get a job as some say.
 
APSA’s studies of placement backs me up on this one:
http://www.apsanet.org/RESOURCES/Data-on-the-Profession
 
Some years the schools in the NRC’s 20-40 and 40-60 range actually have better initial placement rates than those in the 1-20 range.
 
Where rank makes a difference, this study as well as the Oprisko data shows, is the types of institutions one gets placed at. If you absolutely need to get a job at an R1 PhD granting institution or this whole endeavor is not worth it for you, you might be best sticking to top 20 programs (but still do your homework on their placement). Otherwise, if you are fine ending up at an R3, non selective liberal arts college or a directional school, you have a lot more options.
 
So how do you determine a schools placement if this data is not readily available to you? Look on the department’s placement page. You can divide the number of total placements (TT, TT+nonTT, R1 jobs, jobs you would want to take, however you want to break it down) over a set period of time (5-7 years is advisable) and either divide it by the total number of grad students currently in the program (data which you can also usually find on the departments website) or by the planned incoming cohort multiplied by the number of years you are counting placements for (again, 5-7 is advisable). Just make sure you keep your process consistent. There will be some inevitable noise, but this should do enough to let you know what programs look good and which you should stay away from.  You may find that some 'top’ programs do a bad job of placing people, whereas some 'midteirs’ do an excellent job. If you focus on R1 placements, you will likely find that the rankings are excellent predictors.
 
Conclusion
So that just about wraps it up. I hope this advice has been useful. Best of luck to all of you.

 

Dear new PhD applicants in Political Science,
 
I am writing this post to provide you with a centralized source of information to help you make decisions about where to apply. I decided to provide you with this source because this information was not available to me in any sort of organized fashion, meaning that I had to find and organize it myself. I wish a resource such as this had been available to me when I began applying.  This does not mean that you will not need to do research on the programs to which you consider applying. There is some information that I simply cannot provide you with, such as up to date data on placement rates or how well your research interests match with the departments you are considering. These are among the most important factors you will consider. While I will walk you through how one can go about making these calculations, the main point of this post is to provide you with a starting point- useful data to help you begin to make decisions about where you will apply.
 
Useful Links
 
Rankings
 
The first thing I should say about rankings are that they are only a short cut. There is a lot more noise than one would like. I encourage everyone to ensure that the department in question is placing people rather than assume it blindly because of the rankings (more on that later). There are three main rankings political scientists look at:
 
The NRC
https://www.chronicle.com/article/NRC-Rankings-Overview-/124714
 
Methodology: the NRC rankings use several different methodologies based on multiple objective criteria to determine their five different sets of rankings. The S-Rankings use some 20 different factors that scholars say are important such as faculty research productivity, student completion rates and funding. The Research Rankings are based on measures of the departments research productivity. The Student Rankings are based on measures of student outcomes and quality of life while in the department. The Diversity Rankings are based on measures of diversity. The R-Rankings are a regression model trying to determine the departments that look most like the departments the Scholars Model likes.
 
Pros:
A lot of objective data went into these rankings.
The multi-dimensionality of the rankings allow you to weigh the different dimensions as you see fit. EG if you care more about research productivity than student outcomes, you can look at the Research Rankings and weigh them in your decision of where to apply to.
The S-Rankings most closely resemble the 5-year placement rates I saw when deciding where to apply of any ranking is (including US News and Oprisko)
Cons
Equivocal: there is a lot of noise, and they show it to you. Programs don't have ranks, but rather rank ranges and there are five different sets of rankings.
Infrequent: this set of rankings came out in 2010, the last NRC rankings before that came out in 1998. While I do not think that these rankings are so excited old that they are not useful, a lot can change in eight years.
 
2) US News Rankings
https://www.usnews.com/best-graduate-schools/top-humanities-schools/political-science-rankings
 
Methodology: US News simply surveys scholars on the department reputation, asking them to rank them on a 1 to 5 scale, and ranks departments based on the results
 
Pros:
The most widely used rankings
The only rankings that take reputation into account
Cons:
Reputation is the only factor taken into account, so it could be said that the rankings are completely subjective
 
3) Oprisko
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2303567
 
Methodology: Oprisko looks at outcomes- R1 placements. He counts the number of PhDs from a given institution currently working at a PhD granting institution in Political Science. He comes up with two rankings from that- the raw total number of placements and the number of placement divided by faculty members (placement efficiency)
 
Pros
Makes student outcomes front and center
 
Cons:
Only uses R1 placements
The main rankings does not control for program size. The placement efficiency rankings, however, do.
 
Stipend Information
 
http://www.phdstipends.com
 
This website provides a searchable database of funding offers from various departments. Just search the name of a University and “Political Science” and something should come up.
 
Some of this data may be outdated, so pay attention to the year it was posted. Some schools may not have any data posted on this site. Funding offers may vary.  Better information may be available on the departments webpage. Nonetheless this is a very useful resource for information about funding.
 
When will I hear back?
 
https://forum.thegradcafe.com/topic/100449-decision-timelines-for-particular-universities-and-programs-derived-from-the-gradcafe-data-gregpa-distributions/?tab=comments#comment-1058542321
 
This link shows the timeline in which decisions have been made in the past. You could also search the gradcafe results forum to get a sense for when results will come through.
 
What should my Statement of Purpose look like?
 
http://grad.berkeley.edu/admissions/apply/statement-purpose/
 
Here is some useful advice for drafting a statement of purpose. Tailor it to your specific program. Mention Professors you'd like to work with and programs/institutes that might interest you. Also edit it as much as you possibly can. I made about ten drafts before finally sending it off.

 
GRE/GPA Info
 
Here is the GRE and GPA information on every school I could find. This data either is posted on the departments website or was about six months ago when I searched for it. Use this data to strategize where to apply. If you have a 155/155, it may not be wise to only apply to Stanford, Duke, Cal, UCSD and WashU, as a safety. However, do not let minor discrepancies discourage you from applying from your dream program. These stats are a small part of a number of factors that will determine your success in the application process. Use them to give you a rough idea of how you may fare, not as an absolute predictor of your success.
 
Stanford 163 q/166 v/3.8 GPA Recommended (Rec)
Duke 163 q/163 v/3.8 GPA Average (AVG)
UC Berkeley 161 q/158 v Rec
Northwestern 148 q/160 v Rec
Kansas 148 v/156 q/ 3.5 GPA Avg
UCSD 163 q/166 v/3.9 GPA Avg
Chicago 162 q/166 v/3.8 GPA Avg
Columbia 158 q/161 v/ 3.8 GPA Avg
Penn 161 q/165 v Avg
WashU-STL 161 q/159 v/3.9 GPA Avg
Colorado State 154 q/154 v/ 3.5 GPA Rec
UNLV 148 q/160 v/3.5 GPA Rec
Emory 160 q/160 v/ B+ (or Better) GPA Avg
Princeton 160 q/160 v/3.8 GPA Rec
Notre Dame 158 q/ 165 v Avg
Colorado 154 q/160 v Avg
Oregon 300 total GRE/3.0 GPA Rec
UC Riverside 307 total GRE/3.0 GPA Minimum
Washington 314 total GRE/3.4 GPA Rec
Oklahoma 154 q/153 v Avg.
Iowa 158 q/156 v/3.3 GPA Rec
Hawaii- No GRE required
Baylor 163 q/163 v Avg
Virginia 155 q/153 v Rec
USC 158 q/ 162 v Avg
NYU 165 q/162v/ 3.5 GPA Rec
Stony Brook 163 q/157 v Rec
 
Maximum Master's/Transfer Credit Accepted (in classes)
 
This is the maximum amount of Master's/Transfer credit programs will award. Please note that it is often up to the department's discretion to award or not award people credit for some or all of these courses. These decisions are also often not made until well after you have entered the program.
 
Princeton- Dept Discretion
Columbia- Dept Discretion
UCLA- 6 Classes
Cornell- 3 Classes
Northwestern- 6 Classes
Texas- None
Emory- Start at Advanced Standing
Penn- 4 Classes
Virginia- Advanced Standing
Vanderbilt- Advanced Standing
Washington- 2 Classes
Ohio State-10 Classes
UNC- 6 Classes
Wisconsin- None
Duke- Dept. Discretion
Pitt- 8 Classes
Missouri- 8 Classes
Notre Dame- 8 Classes
UChicago- Dept Discretion
NYU- 8 Classes
UC Irvine- 6 Classes
USC- 8 Classes
Colorado- 3 Classes
 
How to Figure Out Fit
 
This is where things get somewhat subjective. Professors often move around, retire, ect, so it is not wise to attend a university where you believe that you could only work with one professor. Whether you want to apply to a program with one person who really fits your interest and one other who is less of a good fit, but not as well, is a decision you have to make. Most suggest that there should be at least two who you can work with, I applied only to programs where there was no less than three who shared my interests.
 
Go to department websites. Look at the faculty in your subfield. Look at their CVs, search them on Google Scholar. I'd suggest keeping track of them in a notebook and giving points based on how you feel about their work in relation to your own. By the end of this process, you will have a sense of departments that are good for your interests and those that are not.
 
Placement
This is a tricky thing to measure, but you should absolutely take placement into account before you apply. Some departments have very good data on placements (Michigan, WashU, Notre Dame, UNC to name a few), but you have to dig for it. What will shock some is how little the percentage of graduates placed varies from school to school based on it's rank, particularly if you take attrition into account. Based on their own data, at Michigan (USN #4), a starting PhD student has about a 40 percent chance of finishing the program and finding a Tenure Track job within five years of degree completion. At WashU (#19), a starting PhD student has about a 40 percent chance of finishing their degree and finding a Tenure Track job within five years thereafter. What about Notre Dame (#37)? A starting PhD student has about a 40 percent chance of finishing their degree and finding a Tenure Track job within five years of completion. This is not to say that placement does not vary, just that rank is not as big of a factor in whether or not you will get a job as some say.
 
APSA’s studies of placement backs me up on this one:
http://www.apsanet.org/RESOURCES/Data-on-the-Profession
 
Some years the schools in the NRC’s 20-40 and 40-60 range actually have better initial placement rates than those in the 1-20 range.
 
Where rank makes a difference, this study as well as the Oprisko data shows, is the types of institutions one gets placed at. If you absolutely need to get a job at an R1 PhD granting institution or this whole endeavor is not worth it for you, you might be best sticking to top 20 programs (but still do your homework on their placement). Otherwise, if you are fine ending up at an R3, non selective liberal arts college or a directional school, you have a lot more options.
 
So how do you determine a schools placement if this data is not readily available to you? Look on the department’s placement page. You can divide the number of total placements (TT, TT+nonTT, R1 jobs, jobs you would want to take, however you want to break it down) over a set period of time (5-7 years is advisable) and either divide it by the total number of grad students currently in the program (data which you can also usually find on the departments website) or by the planned incoming cohort multiplied by the number of years you are counting placements for (again, 5-7 is advisable). Just make sure you keep your process consistent. There will be some inevitable noise, but this should do enough to let you know what programs look good and which you should stay away from.  You may find that some 'top’ programs do a bad job of placing people, whereas some 'midteirs’ do an excellent job. If you focus on R1 placements, you will likely find that the rankings are excellent predictors.
 
Conclusion
So that just about wraps it up. I hope this advice has been useful. Best of luck to all of you.

 

Dear new PhD applicants in Political Science,
 
I am writing this post to provide you with a centralized source of information to help you make decisions about where to apply. I decided to provide you with this source because this information was not available to me in any sort of organized fashion, meaning that I had to find and organize it myself. I wish a resource such as this had been available to me when I began applying.  This does not mean that you will not need to do research on the programs to which you consider applying. There is some information that I simply cannot provide you with, such as up to date data on placement rates or how well your research interests match with the departments you are considering. These are among the most important factors you will consider. While I will walk you through how one can go about making these calculations, the main point of this post is to provide you with a starting point- useful data to help you begin to make decisions about where you will apply.
 
Useful Links
 
Rankings
 
The first thing I should say about rankings are that they are only a short cut. There is a lot more noise than one would like. I encourage everyone to ensure that the department in question is placing people rather than assume it blindly because of the rankings (more on that later). There are three main rankings political scientists look at:
 
The NRC
https://www.chronicle.com/article/NRC-Rankings-Overview-/124714
 
Methodology: the NRC rankings use several different methodologies based on multiple objective criteria to determine their five different sets of rankings. The S-Rankings use some 20 different factors that scholars say are important such as faculty research productivity, student completion rates and funding. The Research Rankings are based on measures of the departments research productivity. The Student Rankings are based on measures of student outcomes and quality of life while in the department. The Diversity Rankings are based on measures of diversity. The R-Rankings are a regression model trying to determine the departments that look most like the departments the Scholars Model likes.
 
Pros:
A lot of objective data went into these rankings.
The multi-dimensionality of the rankings allow you to weigh the different dimensions as you see fit. EG if you care more about research productivity than student outcomes, you can look at the Research Rankings and weigh them in your decision of where to apply to.
The S-Rankings most closely resemble the 5-year placement rates I saw when deciding where to apply of any ranking is (including US News and Oprisko)
Cons
Equivocal: there is a lot of noise, and they show it to you. Programs don't have ranks, but rather rank ranges and there are five different sets of rankings.
Infrequent: this set of rankings came out in 2010, the last NRC rankings before that came out in 1998. While I do not think that these rankings are so excited old that they are not useful, a lot can change in eight years.
 
2) US News Rankings
https://www.usnews.com/best-graduate-schools/top-humanities-schools/political-science-rankings
 
Methodology: US News simply surveys scholars on the department reputation, asking them to rank them on a 1 to 5 scale, and ranks departments based on the results
 
Pros:
The most widely used rankings
The only rankings that take reputation into account
Cons:
Reputation is the only factor taken into account, so it could be said that the rankings are completely subjective
 
3) Oprisko
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2303567
 
Methodology: Oprisko looks at outcomes- R1 placements. He counts the number of PhDs from a given institution currently working at a PhD granting institution in Political Science. He comes up with two rankings from that- the raw total number of placements and the number of placement divided by faculty members (placement efficiency)
 
Pros
Makes student outcomes front and center
 
Cons:
Only uses R1 placements
The main rankings does not control for program size. The placement efficiency rankings, however, do.
 
Stipend Information
 
http://www.phdstipends.com
 
This website provides a searchable database of funding offers from various departments. Just search the name of a University and “Political Science” and something should come up.
 
Some of this data may be outdated, so pay attention to the year it was posted. Some schools may not have any data posted on this site. Funding offers may vary.  Better information may be available on the departments webpage. Nonetheless this is a very useful resource for information about funding.
 
When will I hear back?
 
https://forum.thegradcafe.com/topic/100449-decision-timelines-for-particular-universities-and-programs-derived-from-the-gradcafe-data-gregpa-distributions/?tab=comments#comment-1058542321
 
This link shows the timeline in which decisions have been made in the past. You could also search the gradcafe results forum to get a sense for when results will come through.
 
What should my Statement of Purpose look like?
 
http://grad.berkeley.edu/admissions/apply/statement-purpose/
 
Here is some useful advice for drafting a statement of purpose. Tailor it to your specific program. Mention Professors you'd like to work with and programs/institutes that might interest you. Also edit it as much as you possibly can. I made about ten drafts before finally sending it off.

 
GRE/GPA Info
 
Here is the GRE and GPA information on every school I could find. This data either is posted on the departments website or was about six months ago when I searched for it. Use this data to strategize where to apply. If you have a 155/155, it may not be wise to only apply to Stanford, Duke, Cal, UCSD and WashU, as a safety. However, do not let minor discrepancies discourage you from applying from your dream program. These stats are a small part of a number of factors that will determine your success in the application process. Use them to give you a rough idea of how you may fare, not as an absolute predictor of your success.
 
Stanford 163 q/166 v/3.8 GPA Recommended (Rec)
Duke 163 q/163 v/3.8 GPA Average (AVG)
UC Berkeley 161 q/158 v Rec
Northwestern 148 q/160 v Rec
Kansas 148 v/156 q/ 3.5 GPA Avg
UCSD 163 q/166 v/3.9 GPA Avg
Chicago 162 q/166 v/3.8 GPA Avg
Columbia 158 q/161 v/ 3.8 GPA Avg
Penn 161 q/165 v Avg
WashU-STL 161 q/159 v/3.9 GPA Avg
Colorado State 154 q/154 v/ 3.5 GPA Rec
UNLV 148 q/160 v/3.5 GPA Rec
Emory 160 q/160 v/ B+ (or Better) GPA Avg
Princeton 160 q/160 v/3.8 GPA Rec
Notre Dame 158 q/ 165 v Avg
Colorado 154 q/160 v Avg
Oregon 300 total GRE/3.0 GPA Rec
UC Riverside 307 total GRE/3.0 GPA Minimum
Washington 314 total GRE/3.4 GPA Rec
Oklahoma 154 q/153 v Avg.
Iowa 158 q/156 v/3.3 GPA Rec
Hawaii- No GRE required
Baylor 163 q/163 v Avg
Virginia 155 q/153 v Rec
USC 158 q/ 162 v Avg
NYU 165 q/162v/ 3.5 GPA Rec
Stony Brook 163 q/157 v Rec
 
Maximum Master's/Transfer Credit Accepted (in classes)
 
This is the maximum amount of Master's/Transfer credit programs will award. Please note that it is often up to the department's discretion to award or not award people credit for some or all of these courses. These decisions are also often not made until well after you have entered the program.
 
Princeton- Dept Discretion
Columbia- Dept Discretion
UCLA- 6 Classes
Cornell- 3 Classes
Northwestern- 6 Classes
Texas- None
Emory- Start at Advanced Standing
Penn- 4 Classes
Virginia- Advanced Standing
Vanderbilt- Advanced Standing
Washington- 2 Classes
Ohio State-10 Classes
UNC- 6 Classes
Wisconsin- None
Duke- Dept. Discretion
Pitt- 8 Classes
Missouri- 8 Classes
Notre Dame- 8 Classes
UChicago- Dept Discretion
NYU- 8 Classes
UC Irvine- 6 Classes
USC- 8 Classes
Colorado- 3 Classes
 
How to Figure Out Fit
 
This is where things get somewhat subjective. Professors often move around, retire, ect, so it is not wise to attend a university where you believe that you could only work with one professor. Whether you want to apply to a program with one person who really fits your interest and one other who is less of a good fit, but not as well, is a decision you have to make. Most suggest that there should be at least two who you can work with, I applied only to programs where there was no less than three who shared my interests.
 
Go to department websites. Look at the faculty in your subfield. Look at their CVs, search them on Google Scholar. I'd suggest keeping track of them in a notebook and giving points based on how you feel about their work in relation to your own. By the end of this process, you will have a sense of departments that are good for your interests and those that are not.
 
Placement
This is a tricky thing to measure, but you should absolutely take placement into account before you apply. Some departments have very good data on placements (Michigan, WashU, Notre Dame, UNC to name a few), but you have to dig for it. What will shock some is how little the percentage of graduates placed varies from school to school based on it's rank, particularly if you take attrition into account. Based on their own data, at Michigan (USN #4), a starting PhD student has about a 40 percent chance of finishing the program and finding a Tenure Track job within five years of degree completion. At WashU (#19), a starting PhD student has about a 40 percent chance of finishing their degree and finding a Tenure Track job within five years thereafter. What about Notre Dame (#37)? A starting PhD student has about a 40 percent chance of finishing their degree and finding a Tenure Track job within five years of completion. This is not to say that placement does not vary, just that rank is not as big of a factor in whether or not you will get a job as some say.
 
APSA’s studies of placement backs me up on this one:
http://www.apsanet.org/RESOURCES/Data-on-the-Profession
 
Some years the schools in the NRC’s 20-40 and 40-60 range actually have better initial placement rates than those in the 1-20 range.
 
Where rank makes a difference, this study as well as the Oprisko data shows, is the types of institutions one gets placed at. If you absolutely need to get a job at an R1 PhD granting institution or this whole endeavor is not worth it for you, you might be best sticking to top 20 programs (but still do your homework on their placement). Otherwise, if you are fine ending up at an R3, non selective liberal arts college or a directional school, you have a lot more options.
 
So how do you determine a schools placement if this data is not readily available to you? Look on the department’s placement page. You can divide the number of total placements (TT, TT+nonTT, R1 jobs, jobs you would want to take, however you want to break it down) over a set period of time (5-7 years is advisable) and either divide it by the total number of grad students currently in the program (data which you can also usually find on the departments website) or by the planned incoming cohort multiplied by the number of years you are counting placements for (again, 5-7 is advisable). Just make sure you keep your process consistent. There will be some inevitable noise, but this should do enough to let you know what programs look good and which you should stay away from.  You may find that some 'top’ programs do a bad job of placing people, whereas some 'midteirs’ do an excellent job. If you focus on R1 placements, you will likely find that the rankings are excellent predictors.
 
Conclusion
So that just about wraps it up. I hope this advice has been useful. Best of luck to all of you.

 

Dear new PhD applicants in Political Science,
 
I am writing this post to provide you with a centralized source of information to help you make decisions about where to apply. I decided to provide you with this source because this information was not available to me in any sort of organized fashion, meaning that I had to find and organize it myself. I wish a resource such as this had been available to me when I began applying.  This does not mean that you will not need to do research on the programs to which you consider applying. There is some information that I simply cannot provide you with, such as up to date data on placement rates or how well your research interests match with the departments you are considering. These are among the most important factors you will consider. While I will walk you through how one can go about making these calculations, the main point of this post is to provide you with a starting point- useful data to help you begin to make decisions about where you will apply.
 
Useful Links
 
Rankings
 
The first thing I should say about rankings are that they are only a short cut. There is a lot more noise than one would like. I encourage everyone to ensure that the department in question is placing people rather than assume it blindly because of the rankings (more on that later). There are three main rankings political scientists look at:
 
The NRC
https://www.chronicle.com/article/NRC-Rankings-Overview-/124714
 
Methodology: the NRC rankings use several different methodologies based on multiple objective criteria to determine their five different sets of rankings. The S-Rankings use some 20 different factors that scholars say are important such as faculty research productivity, student completion rates and funding. The Research Rankings are based on measures of the departments research productivity. The Student Rankings are based on measures of student outcomes and quality of life while in the department. The Diversity Rankings are based on measures of diversity. The R-Rankings are a regression model trying to determine the departments that look most like the departments the Scholars Model likes.
 
Pros:
A lot of objective data went into these rankings.
The multi-dimensionality of the rankings allow you to weigh the different dimensions as you see fit. EG if you care more about research productivity than student outcomes, you can look at the Research Rankings and weigh them in your decision of where to apply to.
The S-Rankings most closely resemble the 5-year placement rates I saw when deciding where to apply of any ranking is (including US News and Oprisko)
Cons
Equivocal: there is a lot of noise, and they show it to you. Programs don't have ranks, but rather rank ranges and there are five different sets of rankings.
Infrequent: this set of rankings came out in 2010, the last NRC rankings before that came out in 1998. While I do not think that these rankings are so excited old that they are not useful, a lot can change in eight years.
 
2) US News Rankings
https://www.usnews.com/best-graduate-schools/top-humanities-schools/political-science-rankings
 
Methodology: US News simply surveys scholars on the department reputation, asking them to rank them on a 1 to 5 scale, and ranks departments based on the results
 
Pros:
The most widely used rankings
The only rankings that take reputation into account
Cons:
Reputation is the only factor taken into account, so it could be said that the rankings are completely subjective
 
3) Oprisko
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2303567
 
Methodology: Oprisko looks at outcomes- R1 placements. He counts the number of PhDs from a given institution currently working at a PhD granting institution in Political Science. He comes up with two rankings from that- the raw total number of placements and the number of placement divided by faculty members (placement efficiency)
 
Pros
Makes student outcomes front and center
 
Cons:
Only uses R1 placements
The main rankings does not control for program size. The placement efficiency rankings, however, do.
 
Stipend Information
 
http://www.phdstipends.com
 
This website provides a searchable database of funding offers from various departments. Just search the name of a University and “Political Science” and something should come up.
 
Some of this data may be outdated, so pay attention to the year it was posted. Some schools may not have any data posted on this site. Funding offers may vary.  Better information may be available on the departments webpage. Nonetheless this is a very useful resource for information about funding.
 
When will I hear back?
 
https://forum.thegradcafe.com/topic/100449-decision-timelines-for-particular-universities-and-programs-derived-from-the-gradcafe-data-gregpa-distributions/?tab=comments#comment-1058542321
 
This link shows the timeline in which decisions have been made in the past. You could also search the gradcafe results forum to get a sense for when results will come through.
 
What should my Statement of Purpose look like?
 
http://grad.berkeley.edu/admissions/apply/statement-purpose/
 
Here is some useful advice for drafting a statement of purpose. Tailor it to your specific program. Mention Professors you'd like to work with and programs/institutes that might interest you. Also edit it as much as you possibly can. I made about ten drafts before finally sending it off.

 
GRE/GPA Info
 
Here is the GRE and GPA information on every school I could find. This data either is posted on the departments website or was about six months ago when I searched for it. Use this data to strategize where to apply. If you have a 155/155, it may not be wise to only apply to Stanford, Duke, Cal, UCSD and WashU, as a safety. However, do not let minor discrepancies discourage you from applying from your dream program. These stats are a small part of a number of factors that will determine your success in the application process. Use them to give you a rough idea of how you may fare, not as an absolute predictor of your success.
 
Stanford 163 q/166 v/3.8 GPA Recommended (Rec)
Duke 163 q/163 v/3.8 GPA Average (AVG)
UC Berkeley 161 q/158 v Rec
Northwestern 148 q/160 v Rec
Kansas 148 v/156 q/ 3.5 GPA Avg
UCSD 163 q/166 v/3.9 GPA Avg
Chicago 162 q/166 v/3.8 GPA Avg
Columbia 158 q/161 v/ 3.8 GPA Avg
Penn 161 q/165 v Avg
WashU-STL 161 q/159 v/3.9 GPA Avg
Colorado State 154 q/154 v/ 3.5 GPA Rec
UNLV 148 q/160 v/3.5 GPA Rec
Emory 160 q/160 v/ B+ (or Better) GPA Avg
Princeton 160 q/160 v/3.8 GPA Rec
Notre Dame 158 q/ 165 v Avg
Colorado 154 q/160 v Avg
Oregon 300 total GRE/3.0 GPA Rec
UC Riverside 307 total GRE/3.0 GPA Minimum
Washington 314 total GRE/3.4 GPA Rec
Oklahoma 154 q/153 v Avg.
Iowa 158 q/156 v/3.3 GPA Rec
Hawaii- No GRE required
Baylor 163 q/163 v Avg
Virginia 155 q/153 v Rec
USC 158 q/ 162 v Avg
NYU 165 q/162v/ 3.5 GPA Rec
Stony Brook 163 q/157 v Rec
 
Maximum Master's/Transfer Credit Accepted (in classes)
 
This is the maximum amount of Master's/Transfer credit programs will award. Please note that it is often up to the department's discretion to award or not award people credit for some or all of these courses. These decisions are also often not made until well after you have entered the program.
 
Princeton- Dept Discretion
Columbia- Dept Discretion
UCLA- 6 Classes
Cornell- 3 Classes
Northwestern- 6 Classes
Texas- None
Emory- Start at Advanced Standing
Penn- 4 Classes
Virginia- Advanced Standing
Vanderbilt- Advanced Standing
Washington- 2 Classes
Ohio State-10 Classes
UNC- 6 Classes
Wisconsin- None
Duke- Dept. Discretion
Pitt- 8 Classes
Missouri- 8 Classes
Notre Dame- 8 Classes
UChicago- Dept Discretion
NYU- 8 Classes
UC Irvine- 6 Classes
USC- 8 Classes
Colorado- 3 Classes
 
How to Figure Out Fit
 
This is where things get somewhat subjective. Professors often move around, retire, ect, so it is not wise to attend a university where you believe that you could only work with one professor. Whether you want to apply to a program with one person who really fits your interest and one other who is less of a good fit, but not as well, is a decision you have to make. Most suggest that there should be at least two who you can work with, I applied only to programs where there was no less than three who shared my interests.
 
Go to department websites. Look at the faculty in your subfield. Look at their CVs, search them on Google Scholar. I'd suggest keeping track of them in a notebook and giving points based on how you feel about their work in relation to your own. By the end of this process, you will have a sense of departments that are good for your interests and those that are not.
 
Placement
This is a tricky thing to measure, but you should absolutely take placement into account before you apply. Some departments have very good data on placements (Michigan, WashU, Notre Dame, UNC to name a few), but you have to dig for it. What will shock some is how little the percentage of graduates placed varies from school to school based on it's rank, particularly if you take attrition into account. Based on their own data, at Michigan (USN #4), a starting PhD student has about a 40 percent chance of finishing the program and finding a Tenure Track job within five years of degree completion. At WashU (#19), a starting PhD student has about a 40 percent chance of finishing their degree and finding a Tenure Track job within five years thereafter. What about Notre Dame (#37)? A starting PhD student has about a 40 percent chance of finishing their degree and finding a Tenure Track job within five years of completion. This is not to say that placement does not vary, just that rank is not as big of a factor in whether or not you will get a job as some say.
 
APSA’s studies of placement backs me up on this one:
http://www.apsanet.org/RESOURCES/Data-on-the-Profession
 
Some years the schools in the NRC’s 20-40 and 40-60 range actually have better initial placement rates than those in the 1-20 range.
 
Where rank makes a difference, this study as well as the Oprisko data shows, is the types of institutions one gets placed at. If you absolutely need to get a job at an R1 PhD granting institution or this whole endeavor is not worth it for you, you might be best sticking to top 20 programs (but still do your homework on their placement). Otherwise, if you are fine ending up at an R3, non selective liberal arts college or a directional school, you have a lot more options.
 
So how do you determine a schools placement if this data is not readily available to you? Look on the department’s placement page. You can divide the number of total placements (TT, TT+nonTT, R1 jobs, jobs you would want to take, however you want to break it down) over a set period of time (5-7 years is advisable) and either divide it by the total number of grad students currently in the program (data which you can also usually find on the departments website) or by the planned incoming cohort multiplied by the number of years you are counting placements for (again, 5-7 is advisable). Just make sure you keep your process consistent. There will be some inevitable noise, but this should do enough to let you know what programs look good and which you should stay away from.  You may find that some 'top’ programs do a bad job of placing people, whereas some 'midteirs’ do an excellent job. If you focus on R1 placements, you will likely find that the rankings are excellent predictors.
 
Conclusion
So that just about wraps it up. I hope this advice has been useful. Best of luck to all of you.

 

Dear new PhD applicants in Political Science,
 
I am writing this post to provide you with a centralized source of information to help you make decisions about where to apply. I decided to provide you with this source because this information was not available to me in any sort of organized fashion, meaning that I had to find and organize it myself. I wish a resource such as this had been available to me when I began applying.  This does not mean that you will not need to do research on the programs to which you consider applying. There is some information that I simply cannot provide you with, such as up to date data on placement rates or how well your research interests match with the departments you are considering. These are among the most important factors you will consider. While I will walk you through how one can go about making these calculations, the main point of this post is to provide you with a starting point- useful data to help you begin to make decisions about where you will apply.
 
Useful Links
 
Rankings
 
The first thing I should say about rankings are that they are only a short cut. There is a lot more noise than one would like. I encourage everyone to ensure that the department in question is placing people rather than assume it blindly because of the rankings (more on that later). There are three main rankings political scientists look at:
 
The NRC
https://www.chronicle.com/article/NRC-Rankings-Overview-/124714
 
Methodology: the NRC rankings use several different methodologies based on multiple objective criteria to determine their five different sets of rankings. The S-Rankings use some 20 different factors that scholars say are important such as faculty research productivity, student completion rates and funding. The Research Rankings are based on measures of the departments research productivity. The Student Rankings are based on measures of student outcomes and quality of life while in the department. The Diversity Rankings are based on measures of diversity. The R-Rankings are a regression model trying to determine the departments that look most like the departments the Scholars Model likes.
 
Pros:
A lot of objective data went into these rankings.
The multi-dimensionality of the rankings allow you to weigh the different dimensions as you see fit. EG if you care more about research productivity than student outcomes, you can look at the Research Rankings and weigh them in your decision of where to apply to.
The S-Rankings most closely resemble the 5-year placement rates I saw when deciding where to apply of any ranking is (including US News and Oprisko)
Cons
Equivocal: there is a lot of noise, and they show it to you. Programs don't have ranks, but rather rank ranges and there are five different sets of rankings.
Infrequent: this set of rankings came out in 2010, the last NRC rankings before that came out in 1998. While I do not think that these rankings are so excited old that they are not useful, a lot can change in eight years.
 
2) US News Rankings
https://www.usnews.com/best-graduate-schools/top-humanities-schools/political-science-rankings
 
Methodology: US News simply surveys scholars on the department reputation, asking them to rank them on a 1 to 5 scale, and ranks departments based on the results
 
Pros:
The most widely used rankings
The only rankings that take reputation into account
Cons:
Reputation is the only factor taken into account, so it could be said that the rankings are completely subjective
 
3) Oprisko
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2303567
 
Methodology: Oprisko looks at outcomes- R1 placements. He counts the number of PhDs from a given institution currently working at a PhD granting institution in Political Science. He comes up with two rankings from that- the raw total number of placements and the number of placement divided by faculty members (placement efficiency)
 
Pros
Makes student outcomes front and center
 
Cons:
Only uses R1 placements
The main rankings does not control for program size. The placement efficiency rankings, however, do.
 
Stipend Information
 
http://www.phdstipends.com
 
This website provides a searchable database of funding offers from various departments. Just search the name of a University and “Political Science” and something should come up.
 
Some of this data may be outdated, so pay attention to the year it was posted. Some schools may not have any data posted on this site. Funding offers may vary.  Better information may be available on the departments webpage. Nonetheless this is a very useful resource for information about funding.
 
When will I hear back?
 
https://forum.thegradcafe.com/topic/100449-decision-timelines-for-particular-universities-and-programs-derived-from-the-gradcafe-data-gregpa-distributions/?tab=comments#comment-1058542321
 
This link shows the timeline in which decisions have been made in the past. You could also search the gradcafe results forum to get a sense for when results will come through.
 
What should my Statement of Purpose look like?
 
http://grad.berkeley.edu/admissions/apply/statement-purpose/
 
Here is some useful advice for drafting a statement of purpose. Tailor it to your specific program. Mention Professors you'd like to work with and programs/institutes that might interest you. Also edit it as much as you possibly can. I made about ten drafts before finally sending it off.

 
GRE/GPA Info
 
Here is the GRE and GPA information on every school I could find. This data either is posted on the departments website or was about six months ago when I searched for it. Use this data to strategize where to apply. If you have a 155/155, it may not be wise to only apply to Stanford, Duke, Cal, UCSD and WashU, as a safety. However, do not let minor discrepancies discourage you from applying from your dream program. These stats are a small part of a number of factors that will determine your success in the application process. Use them to give you a rough idea of how you may fare, not as an absolute predictor of your success.
 
Stanford 163 q/166 v/3.8 GPA Recommended (Rec)
Duke 163 q/163 v/3.8 GPA Average (AVG)
UC Berkeley 161 q/158 v Rec
Northwestern 148 q/160 v Rec
Kansas 148 v/156 q/ 3.5 GPA Avg
UCSD 163 q/166 v/3.9 GPA Avg
Chicago 162 q/166 v/3.8 GPA Avg
Columbia 158 q/161 v/ 3.8 GPA Avg
Penn 161 q/165 v Avg
WashU-STL 161 q/159 v/3.9 GPA Avg
Colorado State 154 q/154 v/ 3.5 GPA Rec
UNLV 148 q/160 v/3.5 GPA Rec
Emory 160 q/160 v/ B+ (or Better) GPA Avg
Princeton 160 q/160 v/3.8 GPA Rec
Notre Dame 158 q/ 165 v Avg
Colorado 154 q/160 v Avg
Oregon 300 total GRE/3.0 GPA Rec
UC Riverside 307 total GRE/3.0 GPA Minimum
Washington 314 total GRE/3.4 GPA Rec
Oklahoma 154 q/153 v Avg.
Iowa 158 q/156 v/3.3 GPA Rec
Hawaii- No GRE required
Baylor 163 q/163 v Avg
Virginia 155 q/153 v Rec
USC 158 q/ 162 v Avg
NYU 165 q/162v/ 3.5 GPA Rec
Stony Brook 163 q/157 v Rec
 
Maximum Master's/Transfer Credit Accepted (in classes)
 
This is the maximum amount of Master's/Transfer credit programs will award. Please note that it is often up to the department's discretion to award or not award people credit for some or all of these courses. These decisions are also often not made until well after you have entered the program.
 
Princeton- Dept Discretion
Columbia- Dept Discretion
UCLA- 6 Classes
Cornell- 3 Classes
Northwestern- 6 Classes
Texas- None
Emory- Start at Advanced Standing
Penn- 4 Classes
Virginia- Advanced Standing
Vanderbilt- Advanced Standing
Washington- 2 Classes
Ohio State-10 Classes
UNC- 6 Classes
Wisconsin- None
Duke- Dept. Discretion
Pitt- 8 Classes
Missouri- 8 Classes
Notre Dame- 8 Classes
UChicago- Dept Discretion
NYU- 8 Classes
UC Irvine- 6 Classes
USC- 8 Classes
Colorado- 3 Classes
 
How to Figure Out Fit
 
This is where things get somewhat subjective. Professors often move around, retire, ect, so it is not wise to attend a university where you believe that you could only work with one professor. Whether you want to apply to a program with one person who really fits your interest and one other who is less of a good fit, but not as well, is a decision you have to make. Most suggest that there should be at least two who you can work with, I applied only to programs where there was no less than three who shared my interests.
 
Go to department websites. Look at the faculty in your subfield. Look at their CVs, search them on Google Scholar. I'd suggest keeping track of them in a notebook and giving points based on how you feel about their work in relation to your own. By the end of this process, you will have a sense of departments that are good for your interests and those that are not.
 
Placement
This is a tricky thing to measure, but you should absolutely take placement into account before you apply. Some departments have very good data on placements (Michigan, WashU, Notre Dame, UNC to name a few), but you have to dig for it. What will shock some is how little the percentage of graduates placed varies from school to school based on it's rank, particularly if you take attrition into account. Based on their own data, at Michigan (USN #4), a starting PhD student has about a 40 percent chance of finishing the program and finding a Tenure Track job within five years of degree completion. At WashU (#19), a starting PhD student has about a 40 percent chance of finishing their degree and finding a Tenure Track job within five years thereafter. What about Notre Dame (#37)? A starting PhD student has about a 40 percent chance of finishing their degree and finding a Tenure Track job within five years of completion. This is not to say that placement does not vary, just that rank is not as big of a factor in whether or not you will get a job as some say.
 
APSA’s studies of placement backs me up on this one:
http://www.apsanet.org/RESOURCES/Data-on-the-Profession
 
Some years the schools in the NRC’s 20-40 and 40-60 range actually have better initial placement rates than those in the 1-20 range.
 
Where rank makes a difference, this study as well as the Oprisko data shows, is the types of institutions one gets placed at. If you absolutely need to get a job at an R1 PhD granting institution or this whole endeavor is not worth it for you, you might be best sticking to top 20 programs (but still do your homework on their placement). Otherwise, if you are fine ending up at an R3, non selective liberal arts college or a directional school, you have a lot more options.
 
So how do you determine a schools placement if this data is not readily available to you? Look on the department’s placement page. You can divide the number of total placements (TT, TT+nonTT, R1 jobs, jobs you would want to take, however you want to break it down) over a set period of time (5-7 years is advisable) and either divide it by the total number of grad students currently in the program (data which you can also usually find on the departments website) or by the planned incoming cohort multiplied by the number of years you are counting placements for (again, 5-7 is advisable). Just make sure you keep your process consistent. There will be some inevitable noise, but this should do enough to let you know what programs look good and which you should stay away from.  You may find that some 'top’ programs do a bad job of placing people, whereas some 'midteirs’ do an excellent job. If you focus on R1 placements, you will likely find that the rankings are excellent predictors.
 
Conclusion
So that just about wraps it up. I hope this advice has been useful. Best of luck to all of you.

 

Wow it's been 10 years...Wonder if some of the folks here are our professors now

Dear new PhD applicants in Political Science,
 
I am writing this post to provide you with a centralized source of information to help you make decisions about where to apply. I decided to provide you with this source because this information was not available to me in any sort of organized fashion, meaning that I had to find and organize it myself. I wish a resource such as this had been available to me when I began applying.  This does not mean that you will not need to do research on the programs to which you consider applying. There is some information that I simply cannot provide you with, such as up to date data on placement rates or how well your research interests match with the departments you are considering. These are among the most important factors you will consider. While I will walk you through how one can go about making these calculations, the main point of this post is to provide you with a starting point- useful data to help you begin to make decisions about where you will apply.
 
Useful Links
 
Rankings
 
The first thing I should say about rankings are that they are only a short cut. There is a lot more noise than one would like. I encourage everyone to ensure that the department in question is placing people rather than assume it blindly because of the rankings (more on that later). There are three main rankings political scientists look at:
 
The NRC
https://www.chronicle.com/article/NRC-Rankings-Overview-/124714
 
Methodology: the NRC rankings use several different methodologies based on multiple objective criteria to determine their five different sets of rankings. The S-Rankings use some 20 different factors that scholars say are important such as faculty research productivity, student completion rates and funding. The Research Rankings are based on measures of the departments research productivity. The Student Rankings are based on measures of student outcomes and quality of life while in the department. The Diversity Rankings are based on measures of diversity. The R-Rankings are a regression model trying to determine the departments that look most like the departments the Scholars Model likes.
 
Pros:
A lot of objective data went into these rankings.
The multi-dimensionality of the rankings allow you to weigh the different dimensions as you see fit. EG if you care more about research productivity than student outcomes, you can look at the Research Rankings and weigh them in your decision of where to apply to.
The S-Rankings most closely resemble the 5-year placement rates I saw when deciding where to apply of any ranking is (including US News and Oprisko)
Cons
Equivocal: there is a lot of noise, and they show it to you. Programs don't have ranks, but rather rank ranges and there are five different sets of rankings.
Infrequent: this set of rankings came out in 2010, the last NRC rankings before that came out in 1998. While I do not think that these rankings are so excited old that they are not useful, a lot can change in eight years.
 
2) US News Rankings
https://www.usnews.com/best-graduate-schools/top-humanities-schools/political-science-rankings
 
Methodology: US News simply surveys scholars on the department reputation, asking them to rank them on a 1 to 5 scale, and ranks departments based on the results
 
Pros:
The most widely used rankings
The only rankings that take reputation into account
Cons:
Reputation is the only factor taken into account, so it could be said that the rankings are completely subjective
 
3) Oprisko
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2303567
 
Methodology: Oprisko looks at outcomes- R1 placements. He counts the number of PhDs from a given institution currently working at a PhD granting institution in Political Science. He comes up with two rankings from that- the raw total number of placements and the number of placement divided by faculty members (placement efficiency)
 
Pros
Makes student outcomes front and center
 
Cons:
Only uses R1 placements
The main rankings does not control for program size. The placement efficiency rankings, however, do.
 
Stipend Information
 
http://www.phdstipends.com
 
This website provides a searchable database of funding offers from various departments. Just search the name of a University and “Political Science” and something should come up.
 
Some of this data may be outdated, so pay attention to the year it was posted. Some schools may not have any data posted on this site. Funding offers may vary.  Better information may be available on the departments webpage. Nonetheless this is a very useful resource for information about funding.
 
When will I hear back?
 
https://forum.thegradcafe.com/topic/100449-decision-timelines-for-particular-universities-and-programs-derived-from-the-gradcafe-data-gregpa-distributions/?tab=comments#comment-1058542321
 
This link shows the timeline in which decisions have been made in the past. You could also search the gradcafe results forum to get a sense for when results will come through.
 
What should my Statement of Purpose look like?
 
http://grad.berkeley.edu/admissions/apply/statement-purpose/
 
Here is some useful advice for drafting a statement of purpose. Tailor it to your specific program. Mention Professors you'd like to work with and programs/institutes that might interest you. Also edit it as much as you possibly can. I made about ten drafts before finally sending it off.

 
GRE/GPA Info
 
Here is the GRE and GPA information on every school I could find. This data either is posted on the departments website or was about six months ago when I searched for it. Use this data to strategize where to apply. If you have a 155/155, it may not be wise to only apply to Stanford, Duke, Cal, UCSD and WashU, as a safety. However, do not let minor discrepancies discourage you from applying from your dream program. These stats are a small part of a number of factors that will determine your success in the application process. Use them to give you a rough idea of how you may fare, not as an absolute predictor of your success.
 
Stanford 163 q/166 v/3.8 GPA Recommended (Rec)
Duke 163 q/163 v/3.8 GPA Average (AVG)
UC Berkeley 161 q/158 v Rec
Northwestern 148 q/160 v Rec
Kansas 148 v/156 q/ 3.5 GPA Avg
UCSD 163 q/166 v/3.9 GPA Avg
Chicago 162 q/166 v/3.8 GPA Avg
Columbia 158 q/161 v/ 3.8 GPA Avg
Penn 161 q/165 v Avg
WashU-STL 161 q/159 v/3.9 GPA Avg
Colorado State 154 q/154 v/ 3.5 GPA Rec
UNLV 148 q/160 v/3.5 GPA Rec
Emory 160 q/160 v/ B+ (or Better) GPA Avg
Princeton 160 q/160 v/3.8 GPA Rec
Notre Dame 158 q/ 165 v Avg
Colorado 154 q/160 v Avg
Oregon 300 total GRE/3.0 GPA Rec
UC Riverside 307 total GRE/3.0 GPA Minimum
Washington 314 total GRE/3.4 GPA Rec
Oklahoma 154 q/153 v Avg.
Iowa 158 q/156 v/3.3 GPA Rec
Hawaii- No GRE required
Baylor 163 q/163 v Avg
Virginia 155 q/153 v Rec
USC 158 q/ 162 v Avg
NYU 165 q/162v/ 3.5 GPA Rec
Stony Brook 163 q/157 v Rec
 
Maximum Master's/Transfer Credit Accepted (in classes)
 
This is the maximum amount of Master's/Transfer credit programs will award. Please note that it is often up to the department's discretion to award or not award people credit for some or all of these courses. These decisions are also often not made until well after you have entered the program.
 
Princeton- Dept Discretion
Columbia- Dept Discretion
UCLA- 6 Classes
Cornell- 3 Classes
Northwestern- 6 Classes
Texas- None
Emory- Start at Advanced Standing
Penn- 4 Classes
Virginia- Advanced Standing
Vanderbilt- Advanced Standing
Washington- 2 Classes
Ohio State-10 Classes
UNC- 6 Classes
Wisconsin- None
Duke- Dept. Discretion
Pitt- 8 Classes
Missouri- 8 Classes
Notre Dame- 8 Classes
UChicago- Dept Discretion
NYU- 8 Classes
UC Irvine- 6 Classes
USC- 8 Classes
Colorado- 3 Classes
 
How to Figure Out Fit
 
This is where things get somewhat subjective. Professors often move around, retire, ect, so it is not wise to attend a university where you believe that you could only work with one professor. Whether you want to apply to a program with one person who really fits your interest and one other who is less of a good fit, but not as well, is a decision you have to make. Most suggest that there should be at least two who you can work with, I applied only to programs where there was no less than three who shared my interests.
 
Go to department websites. Look at the faculty in your subfield. Look at their CVs, search them on Google Scholar. I'd suggest keeping track of them in a notebook and giving points based on how you feel about their work in relation to your own. By the end of this process, you will have a sense of departments that are good for your interests and those that are not.
 
Placement
This is a tricky thing to measure, but you should absolutely take placement into account before you apply. Some departments have very good data on placements (Michigan, WashU, Notre Dame, UNC to name a few), but you have to dig for it. What will shock some is how little the percentage of graduates placed varies from school to school based on it's rank, particularly if you take attrition into account. Based on their own data, at Michigan (USN #4), a starting PhD student has about a 40 percent chance of finishing the program and finding a Tenure Track job within five years of degree completion. At WashU (#19), a starting PhD student has about a 40 percent chance of finishing their degree and finding a Tenure Track job within five years thereafter. What about Notre Dame (#37)? A starting PhD student has about a 40 percent chance of finishing their degree and finding a Tenure Track job within five years of completion. This is not to say that placement does not vary, just that rank is not as big of a factor in whether or not you will get a job as some say.
 
APSA’s studies of placement backs me up on this one:
http://www.apsanet.org/RESOURCES/Data-on-the-Profession
 
Some years the schools in the NRC’s 20-40 and 40-60 range actually have better initial placement rates than those in the 1-20 range.
 
Where rank makes a difference, this study as well as the Oprisko data shows, is the types of institutions one gets placed at. If you absolutely need to get a job at an R1 PhD granting institution or this whole endeavor is not worth it for you, you might be best sticking to top 20 programs (but still do your homework on their placement). Otherwise, if you are fine ending up at an R3, non selective liberal arts college or a directional school, you have a lot more options.
 
So how do you determine a schools placement if this data is not readily available to you? Look on the department’s placement page. You can divide the number of total placements (TT, TT+nonTT, R1 jobs, jobs you would want to take, however you want to break it down) over a set period of time (5-7 years is advisable) and either divide it by the total number of grad students currently in the program (data which you can also usually find on the departments website) or by the planned incoming cohort multiplied by the number of years you are counting placements for (again, 5-7 is advisable). Just make sure you keep your process consistent. There will be some inevitable noise, but this should do enough to let you know what programs look good and which you should stay away from.  You may find that some 'top’ programs do a bad job of placing people, whereas some 'midteirs’ do an excellent job. If you focus on R1 placements, you will likely find that the rankings are excellent predictors.
 
Conclusion
So that just about wraps it up. I hope this advice has been useful. Best of luck to all of you.

 

Dear new PhD applicants in Political Science,
 
I am writing this post to provide you with a centralized source of information to help you make decisions about where to apply. I decided to provide you with this source because this information was not available to me in any sort of organized fashion, meaning that I had to find and organize it myself. I wish a resource such as this had been available to me when I began applying.  This does not mean that you will not need to do research on the programs to which you consider applying. There is some information that I simply cannot provide you with, such as up to date data on placement rates or how well your research interests match with the departments you are considering. These are among the most important factors you will consider. While I will walk you through how one can go about making these calculations, the main point of this post is to provide you with a starting point- useful data to help you begin to make decisions about where you will apply.
 
Useful Links
 
Rankings
 
The first thing I should say about rankings are that they are only a short cut. There is a lot more noise than one would like. I encourage everyone to ensure that the department in question is placing people rather than assume it blindly because of the rankings (more on that later). There are three main rankings political scientists look at:
 
The NRC
https://www.chronicle.com/article/NRC-Rankings-Overview-/124714
 
Methodology: the NRC rankings use several different methodologies based on multiple objective criteria to determine their five different sets of rankings. The S-Rankings use some 20 different factors that scholars say are important such as faculty research productivity, student completion rates and funding. The Research Rankings are based on measures of the departments research productivity. The Student Rankings are based on measures of student outcomes and quality of life while in the department. The Diversity Rankings are based on measures of diversity. The R-Rankings are a regression model trying to determine the departments that look most like the departments the Scholars Model likes.
 
Pros:
A lot of objective data went into these rankings.
The multi-dimensionality of the rankings allow you to weigh the different dimensions as you see fit. EG if you care more about research productivity than student outcomes, you can look at the Research Rankings and weigh them in your decision of where to apply to.
The S-Rankings most closely resemble the 5-year placement rates I saw when deciding where to apply of any ranking is (including US News and Oprisko)
Cons
Equivocal: there is a lot of noise, and they show it to you. Programs don't have ranks, but rather rank ranges and there are five different sets of rankings.
Infrequent: this set of rankings came out in 2010, the last NRC rankings before that came out in 1998. While I do not think that these rankings are so excited old that they are not useful, a lot can change in eight years.
 
2) US News Rankings
https://www.usnews.com/best-graduate-schools/top-humanities-schools/political-science-rankings
 
Methodology: US News simply surveys scholars on the department reputation, asking them to rank them on a 1 to 5 scale, and ranks departments based on the results
 
Pros:
The most widely used rankings
The only rankings that take reputation into account
Cons:
Reputation is the only factor taken into account, so it could be said that the rankings are completely subjective
 
3) Oprisko
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2303567
 
Methodology: Oprisko looks at outcomes- R1 placements. He counts the number of PhDs from a given institution currently working at a PhD granting institution in Political Science. He comes up with two rankings from that- the raw total number of placements and the number of placement divided by faculty members (placement efficiency)
 
Pros
Makes student outcomes front and center
 
Cons:
Only uses R1 placements
The main rankings does not control for program size. The placement efficiency rankings, however, do.
 
Stipend Information
 
http://www.phdstipends.com
 
This website provides a searchable database of funding offers from various departments. Just search the name of a University and “Political Science” and something should come up.
 
Some of this data may be outdated, so pay attention to the year it was posted. Some schools may not have any data posted on this site. Funding offers may vary.  Better information may be available on the departments webpage. Nonetheless this is a very useful resource for information about funding.
 
When will I hear back?
 
https://forum.thegradcafe.com/topic/100449-decision-timelines-for-particular-universities-and-programs-derived-from-the-gradcafe-data-gregpa-distributions/?tab=comments#comment-1058542321
 
This link shows the timeline in which decisions have been made in the past. You could also search the gradcafe results forum to get a sense for when results will come through.
 
What should my Statement of Purpose look like?
 
http://grad.berkeley.edu/admissions/apply/statement-purpose/
 
Here is some useful advice for drafting a statement of purpose. Tailor it to your specific program. Mention Professors you'd like to work with and programs/institutes that might interest you. Also edit it as much as you possibly can. I made about ten drafts before finally sending it off.

 
GRE/GPA Info
 
Here is the GRE and GPA information on every school I could find. This data either is posted on the departments website or was about six months ago when I searched for it. Use this data to strategize where to apply. If you have a 155/155, it may not be wise to only apply to Stanford, Duke, Cal, UCSD and WashU, as a safety. However, do not let minor discrepancies discourage you from applying from your dream program. These stats are a small part of a number of factors that will determine your success in the application process. Use them to give you a rough idea of how you may fare, not as an absolute predictor of your success.
 
Stanford 163 q/166 v/3.8 GPA Recommended (Rec)
Duke 163 q/163 v/3.8 GPA Average (AVG)
UC Berkeley 161 q/158 v Rec
Northwestern 148 q/160 v Rec
Kansas 148 v/156 q/ 3.5 GPA Avg
UCSD 163 q/166 v/3.9 GPA Avg
Chicago 162 q/166 v/3.8 GPA Avg
Columbia 158 q/161 v/ 3.8 GPA Avg
Penn 161 q/165 v Avg
WashU-STL 161 q/159 v/3.9 GPA Avg
Colorado State 154 q/154 v/ 3.5 GPA Rec
UNLV 148 q/160 v/3.5 GPA Rec
Emory 160 q/160 v/ B+ (or Better) GPA Avg
Princeton 160 q/160 v/3.8 GPA Rec
Notre Dame 158 q/ 165 v Avg
Colorado 154 q/160 v Avg
Oregon 300 total GRE/3.0 GPA Rec
UC Riverside 307 total GRE/3.0 GPA Minimum
Washington 314 total GRE/3.4 GPA Rec
Oklahoma 154 q/153 v Avg.
Iowa 158 q/156 v/3.3 GPA Rec
Hawaii- No GRE required
Baylor 163 q/163 v Avg
Virginia 155 q/153 v Rec
USC 158 q/ 162 v Avg
NYU 165 q/162v/ 3.5 GPA Rec
Stony Brook 163 q/157 v Rec
 
Maximum Master's/Transfer Credit Accepted (in classes)
 
This is the maximum amount of Master's/Transfer credit programs will award. Please note that it is often up to the department's discretion to award or not award people credit for some or all of these courses. These decisions are also often not made until well after you have entered the program.
 
Princeton- Dept Discretion
Columbia- Dept Discretion
UCLA- 6 Classes
Cornell- 3 Classes
Northwestern- 6 Classes
Texas- None
Emory- Start at Advanced Standing
Penn- 4 Classes
Virginia- Advanced Standing
Vanderbilt- Advanced Standing
Washington- 2 Classes
Ohio State-10 Classes
UNC- 6 Classes
Wisconsin- None
Duke- Dept. Discretion
Pitt- 8 Classes
Missouri- 8 Classes
Notre Dame- 8 Classes
UChicago- Dept Discretion
NYU- 8 Classes
UC Irvine- 6 Classes
USC- 8 Classes
Colorado- 3 Classes
 
How to Figure Out Fit
 
This is where things get somewhat subjective. Professors often move around, retire, ect, so it is not wise to attend a university where you believe that you could only work with one professor. Whether you want to apply to a program with one person who really fits your interest and one other who is less of a good fit, but not as well, is a decision you have to make. Most suggest that there should be at least two who you can work with, I applied only to programs where there was no less than three who shared my interests.
 
Go to department websites. Look at the faculty in your subfield. Look at their CVs, search them on Google Scholar. I'd suggest keeping track of them in a notebook and giving points based on how you feel about their work in relation to your own. By the end of this process, you will have a sense of departments that are good for your interests and those that are not.
 
Placement
This is a tricky thing to measure, but you should absolutely take placement into account before you apply. Some departments have very good data on placements (Michigan, WashU, Notre Dame, UNC to name a few), but you have to dig for it. What will shock some is how little the percentage of graduates placed varies from school to school based on it's rank, particularly if you take attrition into account. Based on their own data, at Michigan (USN #4), a starting PhD student has about a 40 percent chance of finishing the program and finding a Tenure Track job within five years of degree completion. At WashU (#19), a starting PhD student has about a 40 percent chance of finishing their degree and finding a Tenure Track job within five years thereafter. What about Notre Dame (#37)? A starting PhD student has about a 40 percent chance of finishing their degree and finding a Tenure Track job within five years of completion. This is not to say that placement does not vary, just that rank is not as big of a factor in whether or not you will get a job as some say.
 
APSA’s studies of placement backs me up on this one:
http://www.apsanet.org/RESOURCES/Data-on-the-Profession
 
Some years the schools in the NRC’s 20-40 and 40-60 range actually have better initial placement rates than those in the 1-20 range.
 
Where rank makes a difference, this study as well as the Oprisko data shows, is the types of institutions one gets placed at. If you absolutely need to get a job at an R1 PhD granting institution or this whole endeavor is not worth it for you, you might be best sticking to top 20 programs (but still do your homework on their placement). Otherwise, if you are fine ending up at an R3, non selective liberal arts college or a directional school, you have a lot more options.
 
So how do you determine a schools placement if this data is not readily available to you? Look on the department’s placement page. You can divide the number of total placements (TT, TT+nonTT, R1 jobs, jobs you would want to take, however you want to break it down) over a set period of time (5-7 years is advisable) and either divide it by the total number of grad students currently in the program (data which you can also usually find on the departments website) or by the planned incoming cohort multiplied by the number of years you are counting placements for (again, 5-7 is advisable). Just make sure you keep your process consistent. There will be some inevitable noise, but this should do enough to let you know what programs look good and which you should stay away from.  You may find that some 'top’ programs do a bad job of placing people, whereas some 'midteirs’ do an excellent job. If you focus on R1 placements, you will likely find that the rankings are excellent predictors.
 
Conclusion
So that just about wraps it up. I hope this advice has been useful. Best of luck to all of you.

 

Dear new PhD applicants in Political Science,
 
I am writing this post to provide you with a centralized source of information to help you make decisions about where to apply. I decided to provide you with this source because this information was not available to me in any sort of organized fashion, meaning that I had to find and organize it myself. I wish a resource such as this had been available to me when I began applying.  This does not mean that you will not need to do research on the programs to which you consider applying. There is some information that I simply cannot provide you with, such as up to date data on placement rates or how well your research interests match with the departments you are considering. These are among the most important factors you will consider. While I will walk you through how one can go about making these calculations, the main point of this post is to provide you with a starting point- useful data to help you begin to make decisions about where you will apply.
 
Useful Links
 
Rankings
 
The first thing I should say about rankings are that they are only a short cut. There is a lot more noise than one would like. I encourage everyone to ensure that the department in question is placing people rather than assume it blindly because of the rankings (more on that later). There are three main rankings political scientists look at:
 
The NRC
https://www.chronicle.com/article/NRC-Rankings-Overview-/124714
 
Methodology: the NRC rankings use several different methodologies based on multiple objective criteria to determine their five different sets of rankings. The S-Rankings use some 20 different factors that scholars say are important such as faculty research productivity, student completion rates and funding. The Research Rankings are based on measures of the departments research productivity. The Student Rankings are based on measures of student outcomes and quality of life while in the department. The Diversity Rankings are based on measures of diversity. The R-Rankings are a regression model trying to determine the departments that look most like the departments the Scholars Model likes.
 
Pros:
A lot of objective data went into these rankings.
The multi-dimensionality of the rankings allow you to weigh the different dimensions as you see fit. EG if you care more about research productivity than student outcomes, you can look at the Research Rankings and weigh them in your decision of where to apply to.
The S-Rankings most closely resemble the 5-year placement rates I saw when deciding where to apply of any ranking is (including US News and Oprisko)
Cons
Equivocal: there is a lot of noise, and they show it to you. Programs don't have ranks, but rather rank ranges and there are five different sets of rankings.
Infrequent: this set of rankings came out in 2010, the last NRC rankings before that came out in 1998. While I do not think that these rankings are so excited old that they are not useful, a lot can change in eight years.
 
2) US News Rankings
https://www.usnews.com/best-graduate-schools/top-humanities-schools/political-science-rankings
 
Methodology: US News simply surveys scholars on the department reputation, asking them to rank them on a 1 to 5 scale, and ranks departments based on the results
 
Pros:
The most widely used rankings
The only rankings that take reputation into account
Cons:
Reputation is the only factor taken into account, so it could be said that the rankings are completely subjective
 
3) Oprisko
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2303567
 
Methodology: Oprisko looks at outcomes- R1 placements. He counts the number of PhDs from a given institution currently working at a PhD granting institution in Political Science. He comes up with two rankings from that- the raw total number of placements and the number of placement divided by faculty members (placement efficiency)
 
Pros
Makes student outcomes front and center
 
Cons:
Only uses R1 placements
The main rankings does not control for program size. The placement efficiency rankings, however, do.
 
Stipend Information
 
http://www.phdstipends.com
 
This website provides a searchable database of funding offers from various departments. Just search the name of a University and “Political Science” and something should come up.
 
Some of this data may be outdated, so pay attention to the year it was posted. Some schools may not have any data posted on this site. Funding offers may vary.  Better information may be available on the departments webpage. Nonetheless this is a very useful resource for information about funding.
 
When will I hear back?
 
https://forum.thegradcafe.com/topic/100449-decision-timelines-for-particular-universities-and-programs-derived-from-the-gradcafe-data-gregpa-distributions/?tab=comments#comment-1058542321
 
This link shows the timeline in which decisions have been made in the past. You could also search the gradcafe results forum to get a sense for when results will come through.
 
What should my Statement of Purpose look like?
 
http://grad.berkeley.edu/admissions/apply/statement-purpose/
 
Here is some useful advice for drafting a statement of purpose. Tailor it to your specific program. Mention Professors you'd like to work with and programs/institutes that might interest you. Also edit it as much as you possibly can. I made about ten drafts before finally sending it off.

 
GRE/GPA Info
 
Here is the GRE and GPA information on every school I could find. This data either is posted on the departments website or was about six months ago when I searched for it. Use this data to strategize where to apply. If you have a 155/155, it may not be wise to only apply to Stanford, Duke, Cal, UCSD and WashU, as a safety. However, do not let minor discrepancies discourage you from applying from your dream program. These stats are a small part of a number of factors that will determine your success in the application process. Use them to give you a rough idea of how you may fare, not as an absolute predictor of your success.
 
Stanford 163 q/166 v/3.8 GPA Recommended (Rec)
Duke 163 q/163 v/3.8 GPA Average (AVG)
UC Berkeley 161 q/158 v Rec
Northwestern 148 q/160 v Rec
Kansas 148 v/156 q/ 3.5 GPA Avg
UCSD 163 q/166 v/3.9 GPA Avg
Chicago 162 q/166 v/3.8 GPA Avg
Columbia 158 q/161 v/ 3.8 GPA Avg
Penn 161 q/165 v Avg
WashU-STL 161 q/159 v/3.9 GPA Avg
Colorado State 154 q/154 v/ 3.5 GPA Rec
UNLV 148 q/160 v/3.5 GPA Rec
Emory 160 q/160 v/ B+ (or Better) GPA Avg
Princeton 160 q/160 v/3.8 GPA Rec
Notre Dame 158 q/ 165 v Avg
Colorado 154 q/160 v Avg
Oregon 300 total GRE/3.0 GPA Rec
UC Riverside 307 total GRE/3.0 GPA Minimum
Washington 314 total GRE/3.4 GPA Rec
Oklahoma 154 q/153 v Avg.
Iowa 158 q/156 v/3.3 GPA Rec
Hawaii- No GRE required
Baylor 163 q/163 v Avg
Virginia 155 q/153 v Rec
USC 158 q/ 162 v Avg
NYU 165 q/162v/ 3.5 GPA Rec
Stony Brook 163 q/157 v Rec
 
Maximum Master's/Transfer Credit Accepted (in classes)
 
This is the maximum amount of Master's/Transfer credit programs will award. Please note that it is often up to the department's discretion to award or not award people credit for some or all of these courses. These decisions are also often not made until well after you have entered the program.
 
Princeton- Dept Discretion
Columbia- Dept Discretion
UCLA- 6 Classes
Cornell- 3 Classes
Northwestern- 6 Classes
Texas- None
Emory- Start at Advanced Standing
Penn- 4 Classes
Virginia- Advanced Standing
Vanderbilt- Advanced Standing
Washington- 2 Classes
Ohio State-10 Classes
UNC- 6 Classes
Wisconsin- None
Duke- Dept. Discretion
Pitt- 8 Classes
Missouri- 8 Classes
Notre Dame- 8 Classes
UChicago- Dept Discretion
NYU- 8 Classes
UC Irvine- 6 Classes
USC- 8 Classes
Colorado- 3 Classes
 
How to Figure Out Fit
 
This is where things get somewhat subjective. Professors often move around, retire, ect, so it is not wise to attend a university where you believe that you could only work with one professor. Whether you want to apply to a program with one person who really fits your interest and one other who is less of a good fit, but not as well, is a decision you have to make. Most suggest that there should be at least two who you can work with, I applied only to programs where there was no less than three who shared my interests.
 
Go to department websites. Look at the faculty in your subfield. Look at their CVs, search them on Google Scholar. I'd suggest keeping track of them in a notebook and giving points based on how you feel about their work in relation to your own. By the end of this process, you will have a sense of departments that are good for your interests and those that are not.
 
Placement
This is a tricky thing to measure, but you should absolutely take placement into account before you apply. Some departments have very good data on placements (Michigan, WashU, Notre Dame, UNC to name a few), but you have to dig for it. What will shock some is how little the percentage of graduates placed varies from school to school based on it's rank, particularly if you take attrition into account. Based on their own data, at Michigan (USN #4), a starting PhD student has about a 40 percent chance of finishing the program and finding a Tenure Track job within five years of degree completion. At WashU (#19), a starting PhD student has about a 40 percent chance of finishing their degree and finding a Tenure Track job within five years thereafter. What about Notre Dame (#37)? A starting PhD student has about a 40 percent chance of finishing their degree and finding a Tenure Track job within five years of completion. This is not to say that placement does not vary, just that rank is not as big of a factor in whether or not you will get a job as some say.
 
APSA’s studies of placement backs me up on this one:
http://www.apsanet.org/RESOURCES/Data-on-the-Profession
 
Some years the schools in the NRC’s 20-40 and 40-60 range actually have better initial placement rates than those in the 1-20 range.
 
Where rank makes a difference, this study as well as the Oprisko data shows, is the types of institutions one gets placed at. If you absolutely need to get a job at an R1 PhD granting institution or this whole endeavor is not worth it for you, you might be best sticking to top 20 programs (but still do your homework on their placement). Otherwise, if you are fine ending up at an R3, non selective liberal arts college or a directional school, you have a lot more options.
 
So how do you determine a schools placement if this data is not readily available to you? Look on the department’s placement page. You can divide the number of total placements (TT, TT+nonTT, R1 jobs, jobs you would want to take, however you want to break it down) over a set period of time (5-7 years is advisable) and either divide it by the total number of grad students currently in the program (data which you can also usually find on the departments website) or by the planned incoming cohort multiplied by the number of years you are counting placements for (again, 5-7 is advisable). Just make sure you keep your process consistent. There will be some inevitable noise, but this should do enough to let you know what programs look good and which you should stay away from.  You may find that some 'top’ programs do a bad job of placing people, whereas some 'midteirs’ do an excellent job. If you focus on R1 placements, you will likely find that the rankings are excellent predictors.
 
Conclusion
So that just about wraps it up. I hope this advice has been useful. Best of luck to all of you.

 

Anybody else coming away from visits even more confused than when they went in? Thought these would help clear things up, but they've only made me more unsure of my decision making process over the next month!
 

Dear new PhD applicants in Political Science,
 
I am writing this post to provide you with a centralized source of information to help you make decisions about where to apply. I decided to provide you with this source because this information was not available to me in any sort of organized fashion, meaning that I had to find and organize it myself. I wish a resource such as this had been available to me when I began applying.  This does not mean that you will not need to do research on the programs to which you consider applying. There is some information that I simply cannot provide you with, such as up to date data on placement rates or how well your research interests match with the departments you are considering. These are among the most important factors you will consider. While I will walk you through how one can go about making these calculations, the main point of this post is to provide you with a starting point- useful data to help you begin to make decisions about where you will apply.
 
Useful Links
 
Rankings
 
The first thing I should say about rankings are that they are only a short cut. There is a lot more noise than one would like. I encourage everyone to ensure that the department in question is placing people rather than assume it blindly because of the rankings (more on that later). There are three main rankings political scientists look at:
 
The NRC
https://www.chronicle.com/article/NRC-Rankings-Overview-/124714
 
Methodology: the NRC rankings use several different methodologies based on multiple objective criteria to determine their five different sets of rankings. The S-Rankings use some 20 different factors that scholars say are important such as faculty research productivity, student completion rates and funding. The Research Rankings are based on measures of the departments research productivity. The Student Rankings are based on measures of student outcomes and quality of life while in the department. The Diversity Rankings are based on measures of diversity. The R-Rankings are a regression model trying to determine the departments that look most like the departments the Scholars Model likes.
 
Pros:
A lot of objective data went into these rankings.
The multi-dimensionality of the rankings allow you to weigh the different dimensions as you see fit. EG if you care more about research productivity than student outcomes, you can look at the Research Rankings and weigh them in your decision of where to apply to.
The S-Rankings most closely resemble the 5-year placement rates I saw when deciding where to apply of any ranking is (including US News and Oprisko)
Cons
Equivocal: there is a lot of noise, and they show it to you. Programs don't have ranks, but rather rank ranges and there are five different sets of rankings.
Infrequent: this set of rankings came out in 2010, the last NRC rankings before that came out in 1998. While I do not think that these rankings are so excited old that they are not useful, a lot can change in eight years.
 
2) US News Rankings
https://www.usnews.com/best-graduate-schools/top-humanities-schools/political-science-rankings
 
Methodology: US News simply surveys scholars on the department reputation, asking them to rank them on a 1 to 5 scale, and ranks departments based on the results
 
Pros:
The most widely used rankings
The only rankings that take reputation into account
Cons:
Reputation is the only factor taken into account, so it could be said that the rankings are completely subjective
 
3) Oprisko
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2303567
 
Methodology: Oprisko looks at outcomes- R1 placements. He counts the number of PhDs from a given institution currently working at a PhD granting institution in Political Science. He comes up with two rankings from that- the raw total number of placements and the number of placement divided by faculty members (placement efficiency)
 
Pros
Makes student outcomes front and center
 
Cons:
Only uses R1 placements
The main rankings does not control for program size. The placement efficiency rankings, however, do.
 
Stipend Information
 
http://www.phdstipends.com
 
This website provides a searchable database of funding offers from various departments. Just search the name of a University and “Political Science” and something should come up.
 
Some of this data may be outdated, so pay attention to the year it was posted. Some schools may not have any data posted on this site. Funding offers may vary.  Better information may be available on the departments webpage. Nonetheless this is a very useful resource for information about funding.
 
When will I hear back?
 
https://forum.thegradcafe.com/topic/100449-decision-timelines-for-particular-universities-and-programs-derived-from-the-gradcafe-data-gregpa-distributions/?tab=comments#comment-1058542321
 
This link shows the timeline in which decisions have been made in the past. You could also search the gradcafe results forum to get a sense for when results will come through.
 
What should my Statement of Purpose look like?
 
http://grad.berkeley.edu/admissions/apply/statement-purpose/
 
Here is some useful advice for drafting a statement of purpose. Tailor it to your specific program. Mention Professors you'd like to work with and programs/institutes that might interest you. Also edit it as much as you possibly can. I made about ten drafts before finally sending it off.

 
GRE/GPA Info
 
Here is the GRE and GPA information on every school I could find. This data either is posted on the departments website or was about six months ago when I searched for it. Use this data to strategize where to apply. If you have a 155/155, it may not be wise to only apply to Stanford, Duke, Cal, UCSD and WashU, as a safety. However, do not let minor discrepancies discourage you from applying from your dream program. These stats are a small part of a number of factors that will determine your success in the application process. Use them to give you a rough idea of how you may fare, not as an absolute predictor of your success.
 
Stanford 163 q/166 v/3.8 GPA Recommended (Rec)
Duke 163 q/163 v/3.8 GPA Average (AVG)
UC Berkeley 161 q/158 v Rec
Northwestern 148 q/160 v Rec
Kansas 148 v/156 q/ 3.5 GPA Avg
UCSD 163 q/166 v/3.9 GPA Avg
Chicago 162 q/166 v/3.8 GPA Avg
Columbia 158 q/161 v/ 3.8 GPA Avg
Penn 161 q/165 v Avg
WashU-STL 161 q/159 v/3.9 GPA Avg
Colorado State 154 q/154 v/ 3.5 GPA Rec
UNLV 148 q/160 v/3.5 GPA Rec
Emory 160 q/160 v/ B+ (or Better) GPA Avg
Princeton 160 q/160 v/3.8 GPA Rec
Notre Dame 158 q/ 165 v Avg
Colorado 154 q/160 v Avg
Oregon 300 total GRE/3.0 GPA Rec
UC Riverside 307 total GRE/3.0 GPA Minimum
Washington 314 total GRE/3.4 GPA Rec
Oklahoma 154 q/153 v Avg.
Iowa 158 q/156 v/3.3 GPA Rec
Hawaii- No GRE required
Baylor 163 q/163 v Avg
Virginia 155 q/153 v Rec
USC 158 q/ 162 v Avg
NYU 165 q/162v/ 3.5 GPA Rec
Stony Brook 163 q/157 v Rec
 
Maximum Master's/Transfer Credit Accepted (in classes)
 
This is the maximum amount of Master's/Transfer credit programs will award. Please note that it is often up to the department's discretion to award or not award people credit for some or all of these courses. These decisions are also often not made until well after you have entered the program.
 
Princeton- Dept Discretion
Columbia- Dept Discretion
UCLA- 6 Classes
Cornell- 3 Classes
Northwestern- 6 Classes
Texas- None
Emory- Start at Advanced Standing
Penn- 4 Classes
Virginia- Advanced Standing
Vanderbilt- Advanced Standing
Washington- 2 Classes
Ohio State-10 Classes
UNC- 6 Classes
Wisconsin- None
Duke- Dept. Discretion
Pitt- 8 Classes
Missouri- 8 Classes
Notre Dame- 8 Classes
UChicago- Dept Discretion
NYU- 8 Classes
UC Irvine- 6 Classes
USC- 8 Classes
Colorado- 3 Classes
 
How to Figure Out Fit
 
This is where things get somewhat subjective. Professors often move around, retire, ect, so it is not wise to attend a university where you believe that you could only work with one professor. Whether you want to apply to a program with one person who really fits your interest and one other who is less of a good fit, but not as well, is a decision you have to make. Most suggest that there should be at least two who you can work with, I applied only to programs where there was no less than three who shared my interests.
 
Go to department websites. Look at the faculty in your subfield. Look at their CVs, search them on Google Scholar. I'd suggest keeping track of them in a notebook and giving points based on how you feel about their work in relation to your own. By the end of this process, you will have a sense of departments that are good for your interests and those that are not.
 
Placement
This is a tricky thing to measure, but you should absolutely take placement into account before you apply. Some departments have very good data on placements (Michigan, WashU, Notre Dame, UNC to name a few), but you have to dig for it. What will shock some is how little the percentage of graduates placed varies from school to school based on it's rank, particularly if you take attrition into account. Based on their own data, at Michigan (USN #4), a starting PhD student has about a 40 percent chance of finishing the program and finding a Tenure Track job within five years of degree completion. At WashU (#19), a starting PhD student has about a 40 percent chance of finishing their degree and finding a Tenure Track job within five years thereafter. What about Notre Dame (#37)? A starting PhD student has about a 40 percent chance of finishing their degree and finding a Tenure Track job within five years of completion. This is not to say that placement does not vary, just that rank is not as big of a factor in whether or not you will get a job as some say.
 
APSA’s studies of placement backs me up on this one:
http://www.apsanet.org/RESOURCES/Data-on-the-Profession
 
Some years the schools in the NRC’s 20-40 and 40-60 range actually have better initial placement rates than those in the 1-20 range.
 
Where rank makes a difference, this study as well as the Oprisko data shows, is the types of institutions one gets placed at. If you absolutely need to get a job at an R1 PhD granting institution or this whole endeavor is not worth it for you, you might be best sticking to top 20 programs (but still do your homework on their placement). Otherwise, if you are fine ending up at an R3, non selective liberal arts college or a directional school, you have a lot more options.
 
So how do you determine a schools placement if this data is not readily available to you? Look on the department’s placement page. You can divide the number of total placements (TT, TT+nonTT, R1 jobs, jobs you would want to take, however you want to break it down) over a set period of time (5-7 years is advisable) and either divide it by the total number of grad students currently in the program (data which you can also usually find on the departments website) or by the planned incoming cohort multiplied by the number of years you are counting placements for (again, 5-7 is advisable). Just make sure you keep your process consistent. There will be some inevitable noise, but this should do enough to let you know what programs look good and which you should stay away from.  You may find that some 'top’ programs do a bad job of placing people, whereas some 'midteirs’ do an excellent job. If you focus on R1 placements, you will likely find that the rankings are excellent predictors.
 
Conclusion
So that just about wraps it up. I hope this advice has been useful. Best of luck to all of you.

 

It's like a Russian troll farm, only with advanced knowledge in formal theory and in how to structure a grammatically correct insult. In the past few weeks I became convinced it's a rather awful representation of Political Scientists, because it gives you the suspicion that in your own cohort you might be surrounded by people with huge fragile egos, who have zero respect for other people, especially if they don't go to CHYMPS and are women, who are so atomized, they think that spousal hires are fundamentally wrong (I'm not saying that this is indeed the case, just that that particular website gives you such a toxic aftertaste). One can go on, but you get the idea. I hope that you open another thread for this one, because I don't want to contaminate this thread, which was a great support to other people, and to me personally, because of the sense of respect and camaraderie that it afforded. In other words, a total opposite of poliscirumors.

Many programs send a first wave of acceptances and then wait to see if the admits reject before sending formal waitlist/rejection or potentially more acceptance notifications. 
Keep your head up and don't listen to everyone on the Internet -- programs do stagger notifications. 

I understand the percieved lack of opinions, but hold your head up, you got into a good program- no matter what the top-20 or bust crowd says.

I got into Maryland
Holy shit I thought I was going to strike out. I'm so freaking happy right now. I actually don't have to go back to Japan now to do PhD work.

The GRE is such a scam

Thank you guys for the words of encouragement! I was offered a position in a fully funded M.A. program with a paid research assistantship, so I may just have to take that instead and hope to get into a better Ph.D. program afterwards. Still, I'd much prefer to go straight into a Ph.D. program at Notre Dame, UNC, or Georgetown.