These imply a course of action which starts with elimination. If building an online dating profile? Your goal is not to attract as many suitable people as possible. Your goal is to -reject- as many unsuitable people as possible; this is the entry point for people looking for you, and there are far, far more unsuitable people than suitable people.
So, I agree with the premises behind this prediction, but:
I know someone who scraped okCupid for information which he used to eliminate women he wouldn’t want to date from the pool. I read an article about someone else who scraped okCupid for information which he used to appear as acceptable as possible to women, and then would go on dates to find out if they were acceptable to him. The second person was considerably more effective, both at figuring out what actually led to a good date and getting good dates.
Consider this like prices. If you are having too many dates, your prices are too low, and you should raise them (i.e. exclude more people / look less presentable and more authentic). If you are having too few dates, your prices are too high, and you should lower them (i.e. appear more presentable so you don’t get excluded as much).
I think of it more as a Type 1 versus Type 2 error tradeoff; there’s a point at which you are excluding too many people, true, but I’d treat it less a function of raw dates, and more a function of the number of obviously unacceptable dates you have. You can relax exclusion criteria if you’re not getting enough dates, but if in relaxing it, the number of unacceptable people rises without a commensurate rise in acceptable people, you went too far.
(The criteria will differ wildly according to the population you’re searching. The style of profile I had living in the Northeast was -much- more exclusionary than the style of profile I used in the Midwest or South, both because the pool of potential people was much larger, and the percentage of them I would consider dating was much smaller.)
I think of it more as a Type 1 versus Type 2 error tradeoff
I agree that this is a big issue. My point there is more that you need to look at that curve, figure out your tangent line, figure out your value tangent line, and then move so that the two are identical, and this requires both advice on what to do if you are going on too many dates and advice on what to do if you are going on too few dates.
The secondary issue is that presenting as exclusionary typically is discussed in terms of relative turn-offs; if it turns off 5% of the people you would want to date and 50% of the people you wouldn’t want to date, your pool’s average has increased. (Ideally, someone decreases the turn-off chance in people you’d like to date and increases it in people you wouldn’t like to date, but I think people are overly sanguine about what strategies have that effect.)
I think of it more as a Type 1 versus Type 2 error tradeoff
I realized earlier this morning that I had forgotten my main point, and so the sibling comment only hints at it instead of making it explicit: many people talk about plans with the assumption that all of them are on the possibilities frontier, and so the relevant thing is moving along the possibilities frontier until they’re at the right tradeoff.
But being optimal is surprising—one should assume that there is lots of room for growth, and should try to get more of everything (i.e. move perpendicular to the perceived frontier) until it’s clear that they are actually on the frontier. (In the stats case, getting more data means both less Type 1 and Type 2 error.)
So, I agree with the premises behind this prediction, but:
I know someone who scraped okCupid for information which he used to eliminate women he wouldn’t want to date from the pool. I read an article about someone else who scraped okCupid for information which he used to appear as acceptable as possible to women, and then would go on dates to find out if they were acceptable to him. The second person was considerably more effective, both at figuring out what actually led to a good date and getting good dates.
Consider this like prices. If you are having too many dates, your prices are too low, and you should raise them (i.e. exclude more people / look less presentable and more authentic). If you are having too few dates, your prices are too high, and you should lower them (i.e. appear more presentable so you don’t get excluded as much).
I think of it more as a Type 1 versus Type 2 error tradeoff; there’s a point at which you are excluding too many people, true, but I’d treat it less a function of raw dates, and more a function of the number of obviously unacceptable dates you have. You can relax exclusion criteria if you’re not getting enough dates, but if in relaxing it, the number of unacceptable people rises without a commensurate rise in acceptable people, you went too far.
(The criteria will differ wildly according to the population you’re searching. The style of profile I had living in the Northeast was -much- more exclusionary than the style of profile I used in the Midwest or South, both because the pool of potential people was much larger, and the percentage of them I would consider dating was much smaller.)
I agree that this is a big issue. My point there is more that you need to look at that curve, figure out your tangent line, figure out your value tangent line, and then move so that the two are identical, and this requires both advice on what to do if you are going on too many dates and advice on what to do if you are going on too few dates.
The secondary issue is that presenting as exclusionary typically is discussed in terms of relative turn-offs; if it turns off 5% of the people you would want to date and 50% of the people you wouldn’t want to date, your pool’s average has increased. (Ideally, someone decreases the turn-off chance in people you’d like to date and increases it in people you wouldn’t like to date, but I think people are overly sanguine about what strategies have that effect.)
:-D
I realized earlier this morning that I had forgotten my main point, and so the sibling comment only hints at it instead of making it explicit: many people talk about plans with the assumption that all of them are on the possibilities frontier, and so the relevant thing is moving along the possibilities frontier until they’re at the right tradeoff.
But being optimal is surprising—one should assume that there is lots of room for growth, and should try to get more of everything (i.e. move perpendicular to the perceived frontier) until it’s clear that they are actually on the frontier. (In the stats case, getting more data means both less Type 1 and Type 2 error.)