I am afraid I don't understand either of your questions. I work with the karma distribution only in the quotes domain. It doesn't have to be determined, I collected all the data myself. The list is sorted by p-value.

We have the total list of quotes, with scores and posters. We know that Kutta scored 90 points from 7 quotes. Our null hypothesis is that he randomly selected 7 quotes from the total set of 1138 quotes. The p-value is the probability that he could achieve at least 90 points by this process. If his actual method yields better scores then random drawing, then the p-value will be low.

I have very low opinion of classical frequentist statistics, but it seemed to be very suitable for this task. I am sure that there is already a name for this method I reinvented. Of course, the null hypothesis is ridiculous, so we shouldn't assign much meaning to these numbers. It is just one of the many ways we can solve this ranking task.