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dagnabbit

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  1. Upvote
    dagnabbit reacted to nivy25 in 2020-2021 Application Thread   
    I got into UT Austin off their waitlist! Heard from them this morning (IR). I am DELIGHTED! And I will be accepting the offer  
    I have also contacted Rice to ask them to take my name off their waitlist, so hopefully it might help someone there  
  2. Upvote
    dagnabbit reacted to uncle_socks in Updated US-News Rankings   
    Modern polling companies would kill for a response rate of 32%. Like if the 32% response rate is what makes you skeptical, you better be super skeptical of basically all survey and experimental inferences within our field. 
  3. Like
    dagnabbit got a reaction from AHD in 2020-2021 Application Thread   
    A note for the waitlisted: there is often a ton of movement in the week or so before the decision deadline (April 15), as there are always folks who wait until the last minute to turn down offers. I know it's agonizing, but remember: nothing's set in stone until the deadline has passed.
  4. Upvote
    dagnabbit got a reaction from Crossed_fingers in 2020-2021 Application Thread   
    A note for the waitlisted: there is often a ton of movement in the week or so before the decision deadline (April 15), as there are always folks who wait until the last minute to turn down offers. I know it's agonizing, but remember: nothing's set in stone until the deadline has passed.
  5. Like
    dagnabbit got a reaction from Amanda W in 2020-2021 Application Thread   
    A note for the waitlisted: there is often a ton of movement in the week or so before the decision deadline (April 15), as there are always folks who wait until the last minute to turn down offers. I know it's agonizing, but remember: nothing's set in stone until the deadline has passed.
  6. Like
    dagnabbit got a reaction from poliscihopeful2021 in 2020-2021 Application Thread   
    A note for the waitlisted: there is often a ton of movement in the week or so before the decision deadline (April 15), as there are always folks who wait until the last minute to turn down offers. I know it's agonizing, but remember: nothing's set in stone until the deadline has passed.
  7. Like
    dagnabbit got a reaction from polisci21 in 2020-2021 Application Thread   
    A note for the waitlisted: there is often a ton of movement in the week or so before the decision deadline (April 15), as there are always folks who wait until the last minute to turn down offers. I know it's agonizing, but remember: nothing's set in stone until the deadline has passed.
  8. Like
    dagnabbit got a reaction from verschiedene in 2020-2021 Application Thread   
    A note for the waitlisted: there is often a ton of movement in the week or so before the decision deadline (April 15), as there are always folks who wait until the last minute to turn down offers. I know it's agonizing, but remember: nothing's set in stone until the deadline has passed.
  9. Like
    dagnabbit got a reaction from funfetti in 2020-2021 Application Thread   
    A note for the waitlisted: there is often a ton of movement in the week or so before the decision deadline (April 15), as there are always folks who wait until the last minute to turn down offers. I know it's agonizing, but remember: nothing's set in stone until the deadline has passed.
  10. Like
    dagnabbit got a reaction from spotted in 2020-2021 Application Thread   
    A note for the waitlisted: there is often a ton of movement in the week or so before the decision deadline (April 15), as there are always folks who wait until the last minute to turn down offers. I know it's agonizing, but remember: nothing's set in stone until the deadline has passed.
  11. Like
    dagnabbit reacted to icemanyeo in 2020-2021 Application Thread   
    JUST GOT A FULLY FUNDED OFFER FROM CONCORDIA!!!!!
  12. Upvote
    dagnabbit got a reaction from amyvt98 in Math Camp?   
    In my experience, math camp serves two purposes that have nothing to do with math:
    1. It allows incoming grads to transition back into "academic mode" - attending lectures, doing assignments, et cetera - before formal courses begin. This seemed to be especially useful for those in my cohort who had been out of school for a while.
    2. It's a great bonding exercise. You spend a lot of time with your cohort, grab drinks/food after the lecture, and start to build friendships. I think this is really the most important part of the whole exercise, and thus I would strongly encourage all incoming grads to attend (even if your math + programming chops are already very strong).
  13. Upvote
    dagnabbit got a reaction from IcedCovfefe in Math Camp?   
    In my experience, math camp serves two purposes that have nothing to do with math:
    1. It allows incoming grads to transition back into "academic mode" - attending lectures, doing assignments, et cetera - before formal courses begin. This seemed to be especially useful for those in my cohort who had been out of school for a while.
    2. It's a great bonding exercise. You spend a lot of time with your cohort, grab drinks/food after the lecture, and start to build friendships. I think this is really the most important part of the whole exercise, and thus I would strongly encourage all incoming grads to attend (even if your math + programming chops are already very strong).
  14. Like
    dagnabbit got a reaction from Pancho Villa in Political Science Interview Content   
    n of 1 here, but the interview that I had a couple years ago was somewhere in between casual and formal. Most questions were just further probings on my interests, works that had inspired my (proposed) research agenda, and so on. I'd recommend that you be as honest as possible when answering questions about your interests, and prepare a few good questions for the interviewer about the program. They certainly won't be testing your knowledge of their program, beyond maybe asking you if you're still interested in working with the faculty that you ID-ed in your SOP. Cheat sheet is probably unnecessary - focus on communicating your interest in the program and having a pleasant conversation.
  15. Upvote
    dagnabbit reacted to buckinghamubadger in Guide to Applying to PhD Programs in Political Science   
    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.

     
  16. Upvote
    dagnabbit got a reaction from MrsPhD in Duke or NYU? Needs decision advice!   
    I agree with @MrsPhD - I have only heard of a few cases in which a student was asked to leave a poli sci phd program because they failed comps. It seems that there are two more common types of attrition:
    1. Those who leave within the first couple of years to pursue other opportunities / follow their partner / etc
    2. Those who never manage to finish their dissertations.
    The first type is almost entirely idiosyncratic, and should not be of concern to you when choosing a program. The second type is usually not program dependent, but it could be indicative of issues w/r/t advising. If you haven't already, I would strongly recommend that you speak with some of your potential advisors' current students; this can help you identify warning signs about the faculty member (unresponsive/hard to work with/might be leaving/etc) and give you a sense of their respective advising philosophies.
  17. Upvote
    dagnabbit got a reaction from tigerlilies in What skills were most useful when beginning your PhD program?   
    A great way to find these is to look at  methods ABDs' websites; many of these people have taught the "math camp/refresher/etc" and TA-ed for the stats sequence, and often have links to the course materials. For example, here's Harvard's most recent math "prefresher."
    David Seigel at Duke also has some really great videos on math for social scientists.
  18. Upvote
    dagnabbit got a reaction from megabee in What skills were most useful when beginning your PhD program?   
    A great way to find these is to look at  methods ABDs' websites; many of these people have taught the "math camp/refresher/etc" and TA-ed for the stats sequence, and often have links to the course materials. For example, here's Harvard's most recent math "prefresher."
    David Seigel at Duke also has some really great videos on math for social scientists.
  19. Like
    dagnabbit got a reaction from izmir in 2017-2018 Application Cycle   
    My honest advice: don't worry about subfield rankings. Here are the more important things (in my opinion) to consider when weighing programs (in order from most to least important)
    1. Placement. Do graduates in your subfield consistently get TT jobs? Do your potential advisor's students get jobs? This is extremely important information; especially so for theorists, who face an even tougher job market than the rest of us.
    2. Advisors. Is there a faculty member who could chair your dissertation committee? Do you have reason to believe that person might leave or retire soon? Do they seem like somebody who you could get along with? They will play a big role in your experience in graduate school (much bigger than I thought before I started), so it's important to at least have an idea about this before committing to a program.
    3. After you visit each department, reflect on this question: could I spend 5 to 7 years here, with these people? Don't discount the importance of things like department culture, cohort/grad student relations, and even geographic location. Grad school is hard, and if you don't have supportive colleagues, or you're unhappy living in x location, it could be downright unpleasant. My advice here is to treat the visiting weekend like a first date: you'll never get the whole picture right away, but you'll certainly know if it's never going to work out. Trust your gut on this.
  20. Like
    dagnabbit got a reaction from Gik in 2017-2018 Application Cycle   
    My honest advice: don't worry about subfield rankings. Here are the more important things (in my opinion) to consider when weighing programs (in order from most to least important)
    1. Placement. Do graduates in your subfield consistently get TT jobs? Do your potential advisor's students get jobs? This is extremely important information; especially so for theorists, who face an even tougher job market than the rest of us.
    2. Advisors. Is there a faculty member who could chair your dissertation committee? Do you have reason to believe that person might leave or retire soon? Do they seem like somebody who you could get along with? They will play a big role in your experience in graduate school (much bigger than I thought before I started), so it's important to at least have an idea about this before committing to a program.
    3. After you visit each department, reflect on this question: could I spend 5 to 7 years here, with these people? Don't discount the importance of things like department culture, cohort/grad student relations, and even geographic location. Grad school is hard, and if you don't have supportive colleagues, or you're unhappy living in x location, it could be downright unpleasant. My advice here is to treat the visiting weekend like a first date: you'll never get the whole picture right away, but you'll certainly know if it's never going to work out. Trust your gut on this.
  21. Like
    dagnabbit got a reaction from possibleirphd in 2017-2018 Application Cycle   
    My honest advice: don't worry about subfield rankings. Here are the more important things (in my opinion) to consider when weighing programs (in order from most to least important)
    1. Placement. Do graduates in your subfield consistently get TT jobs? Do your potential advisor's students get jobs? This is extremely important information; especially so for theorists, who face an even tougher job market than the rest of us.
    2. Advisors. Is there a faculty member who could chair your dissertation committee? Do you have reason to believe that person might leave or retire soon? Do they seem like somebody who you could get along with? They will play a big role in your experience in graduate school (much bigger than I thought before I started), so it's important to at least have an idea about this before committing to a program.
    3. After you visit each department, reflect on this question: could I spend 5 to 7 years here, with these people? Don't discount the importance of things like department culture, cohort/grad student relations, and even geographic location. Grad school is hard, and if you don't have supportive colleagues, or you're unhappy living in x location, it could be downright unpleasant. My advice here is to treat the visiting weekend like a first date: you'll never get the whole picture right away, but you'll certainly know if it's never going to work out. Trust your gut on this.
  22. Like
    dagnabbit got a reaction from TheWalkingGrad in 2017-2018 Application Cycle   
    My honest advice: don't worry about subfield rankings. Here are the more important things (in my opinion) to consider when weighing programs (in order from most to least important)
    1. Placement. Do graduates in your subfield consistently get TT jobs? Do your potential advisor's students get jobs? This is extremely important information; especially so for theorists, who face an even tougher job market than the rest of us.
    2. Advisors. Is there a faculty member who could chair your dissertation committee? Do you have reason to believe that person might leave or retire soon? Do they seem like somebody who you could get along with? They will play a big role in your experience in graduate school (much bigger than I thought before I started), so it's important to at least have an idea about this before committing to a program.
    3. After you visit each department, reflect on this question: could I spend 5 to 7 years here, with these people? Don't discount the importance of things like department culture, cohort/grad student relations, and even geographic location. Grad school is hard, and if you don't have supportive colleagues, or you're unhappy living in x location, it could be downright unpleasant. My advice here is to treat the visiting weekend like a first date: you'll never get the whole picture right away, but you'll certainly know if it's never going to work out. Trust your gut on this.
  23. Upvote
    dagnabbit got a reaction from arctic_ice in 2017-2018 Application Cycle   
    My honest advice: don't worry about subfield rankings. Here are the more important things (in my opinion) to consider when weighing programs (in order from most to least important)
    1. Placement. Do graduates in your subfield consistently get TT jobs? Do your potential advisor's students get jobs? This is extremely important information; especially so for theorists, who face an even tougher job market than the rest of us.
    2. Advisors. Is there a faculty member who could chair your dissertation committee? Do you have reason to believe that person might leave or retire soon? Do they seem like somebody who you could get along with? They will play a big role in your experience in graduate school (much bigger than I thought before I started), so it's important to at least have an idea about this before committing to a program.
    3. After you visit each department, reflect on this question: could I spend 5 to 7 years here, with these people? Don't discount the importance of things like department culture, cohort/grad student relations, and even geographic location. Grad school is hard, and if you don't have supportive colleagues, or you're unhappy living in x location, it could be downright unpleasant. My advice here is to treat the visiting weekend like a first date: you'll never get the whole picture right away, but you'll certainly know if it's never going to work out. Trust your gut on this.
  24. Upvote
    dagnabbit got a reaction from Anthony2016 in What skills were most useful when beginning your PhD program?   
    Lots of excellent advice here - I don't really have an original contribution to make, but I'll add my experience to the pile.
    1. Basic knowledge of LaTeX (particularly math and BibTeX) is something you can pick up over the summer, and it proved to be really helpful for me when I started my program. Of course you can pick it up as you go, and many (most?) do, but a lot of my cohort-mates found it frustrating to have to struggle with LaTeX under the pressure of problem set deadlines.
    2. If you have little to no familiarity with any statistical software/programming language, it would be beneficial to gain basic proficiency. The Coursera tutorial recommended above would be a great option for R, and I am also a big advocate of DataCamp's short courses. I had some prior knowledge of R before I started, and what was helpful wasn't so much my limited knowledge of how to conduct statistical analysis (the department wants to teach you this anyway) as much as simply being comfortable with programming terms and concepts.
    3. If you don't already use a reference/citation manager (Mendeley, Zotero, etc), I would strongly recommend that you pick one now and learn how it works. Not only is it essential for keeping all of your readings organized, they also auto-update BibTeX files for each of your class/project folders. I wish I had started using Mendeley from the beginning of the first semester instead of picking it up halfway through and having to work backwards.
  25. Upvote
    dagnabbit got a reaction from audre.bored in 2017-2018 Application Cycle   
    That should happen once you receive the formal admission letter from the graduate school, which might not happen until a while after informal acceptance. Congratulations, by the way! If any UT admits have questions about the program, feel free to shoot me a message.
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