  Likelihoodists will endorse (2.1e) because the relationships described in its antecedent depend only on inverse probabilities. Proponents of both the "probability" and "odds" interpretations of total evidence will accept (2.1e) because satisfaction of its antecedent ensures that conditioning on E increases H's probability and its odds strictly more than those of H*.  Indeed, the weak likelihood principle must be an integral part of any account of evidential relevance that deserves the title "Bayesian".  To deny it is to misunderstand the central message of Bayes' Theorem for questions of evidence: namely, that hypotheses are confirmed by data they predict.  As we shall see in the next section, this "minimal" form of Bayesianism figures importantly into subjectivist models of learning from experience.