Follower networks are comprised of active and inactive followers, so all follower counts are not the same. For example, someone who raised 2,000 followers in six months should probably get a higher score than someone who raised 2,000 followers in six years, since a higher percentage of the 2nd author's followers are likely to be inactive.

In principle, I would agree with this, because it can be assumed that new followers are constantly being added to active (even older) accounts.

I have to point out an older quote from you in this context:

I'm seeing that it's probably far too easy to get a top score.

Wouldn't your new approach with a bunch of spam accounts lead to the top even more easily?

and then average the number of followers into a time-based average over the life of the account (i.e. new followers per day, new followers per week, new followers per month, etc.).

I was wondering how you want to determine the number of followers per day (i.e. for a certain period of time), etc. I probably had the same difficulties in understanding as event-horizon. However, a look at your new code revealed to me that you calculate the number over the entire account lifetime.

It would be more interesting and comparable to look at the same time period for all accounts, but this would not be possible with the existing blockchain methods (or only with more network load).
However, Steemchiller's data service could be useful here once again. Among other things, it offers a follower history that can also be filtered by time period:
https://sds0.steemworld.org/followers_api for Follow and Unfollow