Various ways of judging bias and approaches to eliminating it

This posting accidentally got sent when I was partway through writing
it. I have no idea which keys on the keyboard somehow sent the
message.

I'm sending it again. This time I'll make sure that it only gets sent
when it's completed. I'll do that by not filling in the "To:" field
until I've finished the posting.

So, starting from the beginning:

When I say "interval" without qualifying it, I'm referring to the
interval between two integers, for the value of q, the quotient of
dividing states' populations by some common divisor.

Divisor methods, expected s/q:

Divisor methods can eliminate bias by making equal, for all of the
intervals, the expected s/q for a state somewhere in a particular
interval.

That can be done for different assumptions about the
probability-density distribution for states, over the range of q..

As I've said before, Bias-Free (BF) is unbiased if that distribution
is assumed to be uniform.

Weighted Bias-Free (WBF) is unbiased if that distribution is
accurately approximated by an approximating function that is used with
WBF.  The definition of WBF doesn't specify any particular
approximating function.