I agree that some cardinal information needs to enter in the model to generate compromise. The question is whether we can map all theories onto the same utility scale or whether each agent gets their own scale. If we put everything on the same scale, it looks like we’re doing meta-utilitarianism. If each agent gets their own scale, compromise still makes sense without meta-value judgments.
Two outcomes is too degenerate if agents get their own scales, so suppose A, B, and C were options, theory 1 has ordinal preferences B > C > A, and theory 2 has preferences A > C > B. Depending on how much of a compromise C is for each agent, the outcome could vary between
choosing C (say if C is 99% as good as the ideal for each agent),
a 50⁄50 lottery over A and B (if C is only 1% better than the worst for each), or
some other lottery (for instance, 1 thinks C achieves 90% of B and 2 thinks C achieves 40% of A. Then, a lottery with weight 2/3rds on C and 1/3rd on A gives them each 60% of the gain between their best and worst)
I agree that some cardinal information needs to enter in the model to generate compromise. The question is whether we can map all theories onto the same utility scale or whether each agent gets their own scale. If we put everything on the same scale, it looks like we’re doing meta-utilitarianism. If each agent gets their own scale, compromise still makes sense without meta-value judgments.
Two outcomes is too degenerate if agents get their own scales, so suppose A, B, and C were options, theory 1 has ordinal preferences B > C > A, and theory 2 has preferences A > C > B. Depending on how much of a compromise C is for each agent, the outcome could vary between
choosing C (say if C is 99% as good as the ideal for each agent),
a 50⁄50 lottery over A and B (if C is only 1% better than the worst for each), or
some other lottery (for instance, 1 thinks C achieves 90% of B and 2 thinks C achieves 40% of A. Then, a lottery with weight 2/3rds on C and 1/3rd on A gives them each 60% of the gain between their best and worst)