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buckinghamubadger

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  1. Maybe I should have posted this closer to now, rather than back in March. Good luck to all.
  2. 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.
  3. My apologies. That is the standard offer though if you do get admitted. ND has been known to stagger acceptances in the past. It's tough to say what's going on this year though. My letter said that they admitted less than 10 percent, but it also came before the first wave, so I have no idea what's going on there. Wish I could help more.
  4. I got into Notre Dame with full funding and a guaranteed 6th year post-doc
  5. 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.
  6. 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.
  7. My cycle, aside from waitlists, ended today with my tenth and final decision. Seeing as things are beginning to wind down, I thought this would be a good time to post the annual 'profile and lessons learned' thread. I found the previous installment of this thread useful, and others in the past have claimed that it aided them tremendously in the process. So if your cycle is over, please consider posting your profile and results (with as much detail as you feel comfortable) along with advice The template, from previous years, is as follows: PROFILE: Type of Undergrad Institution: Major(s)/Minor(s): Undergrad GPA: Type of Grad: Grad GPA: GRE: Any Special Courses: Letters of Recommendation: Research Experience: Teaching Experience: Subfield/Research Interests: Other: RESULTS: Acceptances($$ or no $$): Waitlists: Rejections: Pending: Going to: LESSONS LEARNED: SOP:
  8. They stagger them. I've had my ND offer since like Feb. 2
  9. Can anyone who got into SC tell me what their funding package looked like?
  10. Waitlisted at USC too. Looks like I'm almost certainly going to Notre Dame, but maybe the waitlists might change that. And thus, the non-waitlist portion of my cycle ends: Accepted: Notre Dame, UC Irvine, Colorado, Missouri Waitlisted: USC, WashU-STL, Brandeis Rejected: Michigan, Princeton, Univ of Washington
  11. They sent out a waive around the first. In the past I believe they have staggered acceptances so I think you still have a shot.
  12. Do you think it's time to start the 'lessons learned' thread yet?
  13. I've gotten nine of my ten decisions, granted two of them were waitlistings. Am I just finishing up early?
  14. 1. PM me if you had any advise on the exact model, I was thinking of using a logistic regression, but you may be able to suggest something better. I am not yet sure how to code waitlists (the dependent variable may have to be trichotomous) 2. Obviously no measure is perfect. For research experience I was thinking of using two separate variables and either running them as separate in the same model or combining them based on which performs better. Number of papers that were either presented at conferences, published in an academic journal or published as a thesis (under grad or grad) would qualify as major research projects, while the number of RAships, independent study or graduate courses taken as an undergrad would constitute minor research experience. For fit I was thinking of asking for both the number of professors one thinks they could work with in the dept and a self reported 1 to 3 scale and again, seeing which performs better. 3. Obviously the model can't be perfect. Things like dept quotas and theoretical orientations are things that I cannot control for, thus we have to presume some uncertainty, where maybe with perfect information we would have a better idea of how things work. Hope this helps clarify. If you want to help, PM me.
  15. Would anyone be interested in helping me build a regression model to help calculate the probability of admission at any given program for political scientists? I tried to make estimates for myself using GRE scores/ranges, a program fit estimate, personal connections/whether or not I received recruitment contacting from the program and the quality of the application I sent off. I believe now after being waitlisted at Brandeis and partly (though less so) because I was waitlisted at WashU, that one factor I failed to control for was program size. My research experience was also a constant for myself, so that would be something I would be interested in looking at. Obviously GPA and undergrad institution rank would be important factors to look at. Anyways, if I'm going to do so, it will require data. That's where some of you come in. I am capable of coding the regression in R, but may also need someone to translate this into a workable model in HTML. Otherwise, I could just post the regression model here somewhere and allow people to calculate their own odds of admissions if they are interested. This is part of my ongoing project to provide more information to people who are at the beginning of this process (I plan on posting useful data for new applicants in March). PM me if you are interested in providing me with data and I will send you back a survey once I write it.
  16. Waitlisted at Brandeis. Somewhat surprised because they sent me recruitment emails, but also not that surprising given that their website says they accept two to five applicants every year. Accepted: Notre Dame, Missouri, Colorado, UC Irvine Waitlisted: Brandeis, WashU-STL Rejected: Michigan, Princeton, Univ. Of Washington Pending: USC
  17. https://www.bankrate.com/calculators/savings/moving-cost-of-living-calculator.aspx This site can help you estimate cost of living adjustments.
  18. Likely next week: Stanford Columbia MIT Pitt Rochester Minnesota USC Chicago Vanderbilt Brown Possible but not exceedingly likely: Yale Cornell UC Riverside
  19. It seems to me that the Following NRC S-Rank top 40 programs have yet to announce anything: Stanford Harvard Columbia Yale MIT Pitt Rochester Cornell Minnesota USC UC Riverside UChicago Vaderbuilt Brown
  20. Two things: I'm really surprised that I am the only person who has heard from Notre Dame on here. I mean I heard unusually early for them, but still I would think someone would have heard something by now. Also I'm currently only waiting on two decisions: USC and Brandeis. I'm surprised Brandeis doesn't get more love and have no idea why it is ranked in the 80s in the US News rankings. They have nine TT placements over the past five years, which is remarkable considering that the program currently has only ten doctoral students.
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