3 ms·
That is indeed a good way to gain insight into consequences, but still you will have to make ambiguous decisions when formulating the measure of good healthcare
by mbrock 8y ago
That is indeed a good way to gain insight into consequences, but still you will have to make ambiguous decisions when formulating the measure of good healthcare—e.g., do you consider equality for rich and poor?—and when judging tradeoffs like those involved in budgeting tax revenue, etc.
- bloak 8y agoI agree that this is the main point: What are you trying to achieve? If your aim is to increase average happiness, what do you consider to be a good measure of happiness? And what kind of average are you using? Most "ideology" relates to this kind of arbitrary preference, I think. But there are also other problems with evidence: How well do you trust the authors and institutions that produce or report the evidence? And if the evidence is probabilistic, as most evidence is, outside mathematics, what are your prior probabilities (in a Bayesian sense)? In the case of international comparisons of health care, and other situations in which there is no repeatable experiment, there's also the problem of whether A caused B or whether A and B are both consequences of something else, perhaps something that the authors had considered and dismissed with some non-numerical justification, or perhaps something that wasn't even considered.