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2017-2018 Application Cycle


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Got very bad news from the University of Florida today. I didn't even want to go there that much, but they aren't even top 50 and I didn't get in, so I don't see how there is any way for me to get into the final schools that I am waiting for: UNC, Notre Dame, and Georgetown. 

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39 minutes ago, Haeralis said:

Got very bad news from the University of Florida today. I didn't even want to go there that much, but they aren't even top 50 and I didn't get in, so I don't see how there is any way for me to get into the final schools that I am waiting for: UNC, Notre Dame, and Georgetown. 

Really, don't read into it. You still have a shot. 

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46 minutes ago, Haeralis said:

Got very bad news from the University of Florida today. I didn't even want to go there that much, but they aren't even top 50 and I didn't get in, so I don't see how there is any way for me to get into the final schools that I am waiting for: UNC, Notre Dame, and Georgetown. 

I was waitlisted by George Washington but accepted to several much higher ranked programs. Never lose hope.

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1 hour ago, sbs2018 said:

Really, don't read into it. You still have a shot. 

 

1 hour ago, Asaid said:

I was waitlisted by George Washington but accepted to several much higher ranked programs. Never lose hope.

 

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. 

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1 hour ago, cedfik said:

No news at all from Chicago or Columbia...

 

Same boat here. If Columbia had sent out their full set of admissions then I suspect there would be more results posts.

I also suspect Chicago may be trickling out. Perhaps some subfields met and finalized this morning and the others will get together this week. Or not—but I'd like to sleep soundly tonight so I'm going with that prediction. 

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7 hours ago, buckinghamubadger said:

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.

Interesting idea -- I have a few questions about how this would work: 

1.  What's your dependent variable? If it's a dichotomous outcome (acceptance/rejection), you'd need something more sophisticated than run-of-the-mill regression -- particularly if you're interested in calculating predicted probabilities.

2. How do you operationalize your independent variables? This would be particularly consequential in the case of things such as "fit" or "research experience," which an applicant may be unable to judge objectively.

3. There are likely many latent (i.e. unobserved) confounders that influence a given school's admissions decisions; for example, subfield quotas, applicants' adherence to the dominant theoretical orientations within a subfield, faculty availability, etc. How would your model account for these factors?

Again, very interesting idea -- however, you should be sure that your model is accurate before soliciting others' information online. 

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10 minutes ago, 1821123 said:

Interesting idea -- I have a few questions about how this would work: 

1.  What's your dependent variable? If it's a dichotomous outcome (acceptance/rejection), you'd need something more sophisticated than run-of-the-mill regression -- particularly if you're interested in calculating predicted probabilities.

2. How do you operationalize your independent variables? This would be particularly consequential in the case of things such as "fit" or "research experience," which an applicant may be unable to judge objectively.

3. There are likely many latent (i.e. unobserved) confounders that influence a given school's admissions decisions; for example, subfield quotas, applicants' adherence to the dominant theoretical orientations within a subfield, faculty availability, etc. How would your model account for these factors?

Again, very interesting idea -- however, you should be sure that your model is accurate before soliciting others' information online. 

Very legitimate questions. But just build it. Otherwise it would never come to life.

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25 minutes ago, 1821123 said:

Interesting idea -- I have a few questions about how this would work: 

1.  What's your dependent variable? If it's a dichotomous outcome (acceptance/rejection), you'd need something more sophisticated than run-of-the-mill regression -- particularly if you're interested in calculating predicted probabilities.

2. How do you operationalize your independent variables? This would be particularly consequential in the case of things such as "fit" or "research experience," which an applicant may be unable to judge objectively.

3. There are likely many latent (i.e. unobserved) confounders that influence a given school's admissions decisions; for example, subfield quotas, applicants' adherence to the dominant theoretical orientations within a subfield, faculty availability, etc. How would your model account for these factors?

Again, very interesting idea -- however, you should be sure that your model is accurate before soliciting others' information online. 

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.

Edited by buckinghamubadger
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3 minutes ago, Wiesbaden said:

I sent an email to the department and they say

 

Our applications are currently under review and you should expect to receive notification in about a week. 

 

What a generic one

when did you send that?

Thanks!

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I feel like Im just waiting for the resounding NO. 

I couldnt afford to apply to all the schools I wanted to so I settled on Pitt because my graduate advisor went there and recommended it. But my quant score is so low and my french grades have hampered my gpa Im probably no where near good enough.

There should be anti depressants for these waiting periods. Its like waiting for whats your worth ??

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8 minutes ago, katieb93 said:

I feel like Im just waiting for the resounding NO. 

I couldnt afford to apply to all the schools I wanted to so I settled on Pitt because my graduate advisor went there and recommended it. But my quant score is so low and my french grades have hampered my gpa Im probably no where near good enough.

There should be anti depressants for these waiting periods. Its like waiting for whats your worth ??

Similar boat, could really afford even the ones I did apply to (still paying those bills off). Going to put some money aside for next cycle as well as the absurd cost for testing. 160/153/4.5 was a weak score but I just couldn't afford the ridiculous cost to take the test another time or two. Expecting the worst, hoping for the best.

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5 hours ago, buckinghamubadger said:

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.

http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.703.1946&rep=rep1&type=pdf

If the link is broken, do a google scholar search for "What Do We Learn from Graduate Admissions Committees?: A Multiple-Rater, Latent Variable Model, with Incomplete Discrete and Continuous Indicators". There may be more recent work in PS, the journal that focuses specifically political sci education and the discipline as a whole.

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