> But this paper was critical to getting me accepted to a Ph.D. program. Why do I think that? Well I was rejected by every Ph.D. program I applied to before this publication (but that's another story), a story about people and opportunity.<p>This is an interesting note. We're talking about a student from one of the top CS schools (UIUC) and applying to another top school (UW). If you think about this a bit carefully, the paper being published did not change who he was or his capabilities, it was simply a difference in measured (distinct from measurable) signal.<p>It's incredible how many extremely noisy signals we use in academia but act as if we use a clear meritocracy. The review process is extremely noisy itself, with computer science in particular being generally more noisy given its preference of conferences over journals. I'm glad Jeff mentions people and opportunities, and it reminds me of the old saying about there being no self made man. But I think this is a very clear example of a instance where we need to think harder and more carefully. Counterfactually, it is almost certain that had that paper been rejected, but all else stays the same (i.e. getting into UW), his success story would also not change. Signals are definitely hard to measure and certainly schools are getting a lot of applicants, so I don't blame anyone for doing this, but I think it is incredibly important to remember these counterfactuals. To remember that metrics are guides and not causal variables themselves. Because there's a great irony in that metrics destroy meritocracies.