1821123

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.

Of course; but you're misunderstanding. Don't be flippant about offers that you might actually accept, and don't disparage programs that you may very well have to endure for the next 5-7 years of your life. Grad school is a very trying experience, and you'd be wise not to make enemies before ever arriving on campus. Prospective students should be very, very careful about how they portray themselves and their perceived "skills" publicly. tl;dr: Do expect to be asked by faculty where else you were admitted, just don't be an idiot on public internet forums (because they see that too).

The most important thing anyone using this website should learn is that this a public forum which is widely read by both current graduate students and faculty. It is not hard to identify users on this website, particularly when they indicate the programs they're considering, areas of interest, etc. You never know who's reading this website, so be wary about what you post. Oversharing makes for many an awkward recruitment weekend, even if you've already been admitted.

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.