'Multi-Dimensional' Trust Metrics
I think what some people here are feeling around for are 'multi-dimensional trust metrics', or even better - trust metrics built on a quantale which is a little more interesting than the positive real numbers.
An immediate advantage of multi-dimensional trust metrics is that you can rate different qualities simultaneously. For example, you can rate someone's theoretical skills, or their skills in Perl, or Python. Then, if you like, you can project these skills onto a single scale in any way that you like - for example, you may be interested in people who are good at Perl and Python so you can take PERL+PYTHON or PERL*PYTHON, or some other increasing function of the individual variables as your measure of how good this person is on the scale.
Why do we need to think about more than just multiple dimensions (which could just as easily be some with several separate metrics)? Here's an example:
In the case of a rating system (like Advogato)- the fact that I trust someone's programming skills doesn't necessarily mean that I trust them to be a good judge of the qualities/trustworthiness of others. This is relevant because the degree to which I trust the people that they trust is actually determined by how much I trust their ability to rate people. Thus the transitivity of trust in this system is not simply the 'product' of the transitivity of two (uninteracting) metrics.
For people who are really interested - you can of course do logic on quantales!
Advogato's trust metric
I don't know if anyone else has noticed, but the definition of Advogato's turst metric given doesn't result in a determined answer. In most situations there will be many different maximal flows, each of which will result in a different result of who is certified and who isn't. Ford-Fulkerson makes no claims about which flow will result and neither does the description of Advogato's metric calculation. I can't be bothered reading through the code to see what actually happens, so I'll just ask you learned people to do it for me ;)