Well, you want some negative selection: Choose dating partners from among the set who are unlikely to steal your money, assault you, or otherwise ruin your life.
This is especially true for women, for whom the risk of being raped is considerably higher and obviously worth negative selecting against.
That carries the assumption that the qualities you’re positively selecting for don’t have a strong negative correlation with the ones you’re trying to select against. I don’t think it’s hard to lay out a few basic “are” qualities that imply “are not” for “violent, thief, etc.”
If A means not B, then selecting for A is the same thing as selecting against B.
If A means “with probability 90% not B”, then if B is a serious problem, it is worth checking both A and not B. Maybe even checking not B first, to avoid halo effect from A.
In my experience, some people treat dating as a negative selection process with thousand requirements that no one passes, because thousand criteria are simply too much. (Assuming independent results, even with probability 99% of passing each test, less than one person in 20 000 passes all thousand criteria. In real life, the criteria are often positively correlated, but on the other hand the probability is way less than 99%.) And those people usually defend it by taking each criterium out of the context and saying: “What’s wrong about wanting my boyfriend/girlfriend to be interested in opera/programming?” Well, nothing wrong per se, but if you have thousand criteria like this, good luck finding a person who fulfills them all (and is also interested in you).
The solution is to separate those criteria into two groups: “must have” and “nice to have”. (And if nine hundred of the thousand criteria are in the first group, you are doing it wrong.) First, filter people by the “must have” criteria. What remains is your dating pool. Some of those will be never interested in you, but you will find that out by trying. Now use the “nice to have” criteria for a utility function, and go seduce someone with a high utility. (And as a parallel process, try to increase your market value.) At the end, you may find someone who has all “must have” and some of the “nice to have” traits; and you may be happy with them.
If A means not B, then selecting for A is only the same thing as selecting against B IF A doesn’t also mean other things, besides not B.
In the dating example, a (straight) woman might employ positive selection to choose men who are particularly decent people. This would also have the effect of weeding out thieves and rapists (assuming that the woman in question can assess a man’s decency with sufficient accuracy), but the quality of “being a decent person” doesn’t only mean one isn’t a thief and a rapist; it’s more wide-ranging than that.
Well, you want some negative selection: Choose dating partners from among the set who are unlikely to steal your money, assault you, or otherwise ruin your life.
This is especially true for women, for whom the risk of being raped is considerably higher and obviously worth negative selecting against.
That carries the assumption that the qualities you’re positively selecting for don’t have a strong negative correlation with the ones you’re trying to select against. I don’t think it’s hard to lay out a few basic “are” qualities that imply “are not” for “violent, thief, etc.”
If A means not B, then selecting for A is the same thing as selecting against B.
If A means “with probability 90% not B”, then if B is a serious problem, it is worth checking both A and not B. Maybe even checking not B first, to avoid halo effect from A.
In my experience, some people treat dating as a negative selection process with thousand requirements that no one passes, because thousand criteria are simply too much. (Assuming independent results, even with probability 99% of passing each test, less than one person in 20 000 passes all thousand criteria. In real life, the criteria are often positively correlated, but on the other hand the probability is way less than 99%.) And those people usually defend it by taking each criterium out of the context and saying: “What’s wrong about wanting my boyfriend/girlfriend to be interested in opera/programming?” Well, nothing wrong per se, but if you have thousand criteria like this, good luck finding a person who fulfills them all (and is also interested in you).
The solution is to separate those criteria into two groups: “must have” and “nice to have”. (And if nine hundred of the thousand criteria are in the first group, you are doing it wrong.) First, filter people by the “must have” criteria. What remains is your dating pool. Some of those will be never interested in you, but you will find that out by trying. Now use the “nice to have” criteria for a utility function, and go seduce someone with a high utility. (And as a parallel process, try to increase your market value.) At the end, you may find someone who has all “must have” and some of the “nice to have” traits; and you may be happy with them.
If A means not B, then selecting for A is only the same thing as selecting against B IF A doesn’t also mean other things, besides not B.
In the dating example, a (straight) woman might employ positive selection to choose men who are particularly decent people. This would also have the effect of weeding out thieves and rapists (assuming that the woman in question can assess a man’s decency with sufficient accuracy), but the quality of “being a decent person” doesn’t only mean one isn’t a thief and a rapist; it’s more wide-ranging than that.