Critical preference tells us to choose ONE fittest theory and _use_ it as knowledge. Bayesian tells us to choose as MANY of the fittest theories as possible, and _use_ them as knowledge.
In this way, Critical Preference is clearly the special case of Bayesian theory where N = 1. (In Bayesian theory, N is the number of fittest theories that are chosen to be used as knowledge.)
Here’s a simple illustration:
Epistemology is the Fitness trainER, and theories are his trainEEs. The trainER has a responsibility to put his trainEEs through gruelling tests to train their fitness. Along the way, many of the old trainEEs drop out, but there are also many new trainEEs joining the fitness programme.
The Fitness trainER continually assesses all his trainEEs, and judges some to be presently fitter than others. But with continual testing, the fitness of trainEEs varies, so that future assessments of fitness could differ from present assessments of fitness.
From time to time, different Fitness trainERs pit their trainEEs against each other in fights to determine which trainER has the fittest trainEEs.
Historically, trainERs have always sent their ONE fittest trainEE to represent them in the fights. One day, a new trainER comes along, and decides to send his 5 best trainEEs into the fighting ring. The new trainER beats all the other trainERs hands down, but the older trainERs can’t quite figure out why the new trainER keeps winning …