Some social choice models assume that precise interpersonal comparisons of utility (either ordinal or cardinal) are possible, allowing a rich theory of distributive justice. Other models assume that absolutely no interpersonal comparisons are possible, or even meaningful; hence all...

We develop a model of social choice over lotteries, where people's psychological characteristics are mutable, their preferences may be incomplete, and approximate interpersonal comparisons of well-being are possible. Formally, we suppose individual preferences are described by a...

We propose a mathematical model of `approximate' interpersonal comparisons of well-being, in terms of an incomplete preorder over a space of `psychophysical states'. We argue that this model is consistent with people's intuitions about interpersonal comparisons, intertemporal preferences, and...

We develop a model of preference aggregation where people's psychological characteristics are mutable (hence, potential objects of individual or social choice), their preferences may be incomplete, and approximate interpersonal comparisons of well-being are possible. Formally, we consider...

Suppose it is possible to make approximate interpersonal comparisons of welfare gains and losses. Thus, if w, x, y, and z are personal psychophysical states (each encoding all ethically relevant information about the physical and mental state of a person), then it sometimes possible to say,...

This paper analyses the implications of classical liberal and libertarian approaches for distributive justice in the context of social welfare orderings. An axiom capturing a liberal non-interfering view of society, named the Weak Harm Principle, is studied, whose roots can be traced back to...

Opportunities in society are commonly interpreted as `chances of success'. Within this interpretation, should opportunities be equalised? We show that a liberal principle of justice and a limited principle of social rationality imply that opportunity profiles should be evaluated by means of a...