johansantana21 wrote:So this means without URM/IP/Great WE, you would have to be significantly better than median?

First, always think of finding a “good” job as a probability, never a certainty. All you can do, and should do, is maximize your probability. Some things you can change, others you can’t.

Think of it in terms of multipliers and attempts. The most important multiplier – for most people at a given school – will be their GPA. So you’d come up with a multiplier for class rank and then apply it to your number of OCI screeners. So, everything else neutral, if you’re top 33% exactly, we’ll say that your chance of getting an offer from any particular screeners is 1/8, or 7/8 that you don’t get it (I’m making these numbers up, guessing from experience of c/o 2011 OCI). If you get 15 screeners, the probability that you won’t get any offer from OCI is 13%. If you got 30 screeners, that drops to 2%! If you’re top ten percent, your chance of any particular screener might be 1/3. With even 15 screeners, the likelihood would drop down close to zero. Conversely, if you’re bottom 1/3 it might be 1/70, giving you a 81% chance of no offer with 15 screeners and a 65% chance of no offer if you get 30 screeners.

This number however, then needs to be adjusted for wildcards. These include IP, WE, URM, nepotism, but also networking and smart bidding and mass mailing, how well you interview, etc. Not for statistical reasons, but I’d break it down into and narrative and other traits. People like to say interview well, but what does that mean? You’re outgoing and charismatic, or that you researched your firms well and you can speak confidently and intelligently to your interests in that firm and practice area? This is why I say narrative – it’s everything that determines how well you do in an interview, and I actually think WE goes into this. So it’s how well you can pitch yourself and then other things you bring to the table, IP, URM, nepotism. So now take your OCI probability of not getting a job and raise to your own personal multiplier. Figure that the absolute average t-14 person is a 1. If your father is GC of a fortune 500 and you can bring a big book of business with you, raise your probability of not getting a job perhaps to the 5th power. Maybe an IP background squares or cubes it. If you panic in interviews, your number might be a .3. Maybe you’re IP, but panic in interviews – perhaps these cancel each other out and you’re back to your 1, i.e., the base OCI percentage.

Take the bottom third and top third candidates above. If the bottom third had and IP back ground (saying this is a 3 multiplier) his chance of not getting a job with 15 screeners becomes 53% -- [(69/70) ^15] ^3. Or 25% --- [(69/70) ^30] ^3 --- with 30 screeners. Conversely, if the top third interviews poorly, but not abysmally, we’ll say his multiplier is .5. He now has a 36% chance --- [(7/8) ^15] ^.5 --- of leaving OCI with no offer with 15 screeners or a 14% chance with 30 screeners --- [(7/8) ^30] ^.5.

You could then do the same for mass mailings, other events, etc. For mass mailings with median grades, however, the chance of any given mailing resulting in an offer might be 1/500, but you can also do 300 of them. Thus, without taking into account your wildcard factors, your probability of not getting an offer from mass mailings would be 55%.

This, from what I’ve seen and logic tells me, is sort of the process of getting an NLJ250 job. It’s not really all that useful for actual calculation as you have no idea what your wildcard exponent would be – is IP 1.5 or 3? - never mind the much less tangible stuff. Also, who knows what the base likelihood of an offer for a given GPA for any particular screener or mass mailing would be. The numbers I used were somewhat arbitrary to come up with what I saw as results from my class, and people on TLS, doing OCI and mass mailings. It does, however, show the importance of a number of factors and their relationships. Perhaps none stronger than taking zillions of attempts, be they screeners or mass mailings, when you don’t have the best odds to begin with. But it also shows that, while not likely, there is a non-negligible probability of any particular person not getting a job even if they are top third if they bid poorly and don’t do a good job mass mailing and almost a certainty that someone who falls into this category will not. On the other hand, if that same person were IP, then the probability likely becomes negligible (though considering that there might be 100 people in this category, there might still be one unlucky person).

Obviously it’s not nearly this mathematical. The take-away is that you can affect your odds and you can affect your attempts, but you can never entirely eliminate luck, be you top ten percent or bottom ten. If your odds suck, you better make a hell of a lot of attempts. If your odds are good, you can probably take it easy, but until you either have an offer in your hand or don’t you won’t know which side of the coin came up.

In closing, graduating unemployed sucks and Carthage must be destroyed.