Aziz Ansari sarcastically jokes about those who marry their high school sweethearts: "I don't think I’m going to run into anyone interesting in my 20s or 30s. I’m just going to lock this shit down now.”
I have to imagine that reasoning occurs more often with those from smaller towns than those from the big city.
If you lock it down at 30, what are the odds that you won't find a single person who is more interesting in your remaining 5+ decades of life (good health be with you)?
I think I would respond to this viewpoint with a CS analogy. You can do a comparison based sort, in which you really don't have an absolute sense of the final sorted position of any object just by looking at it, or you might know extra information about the objects being sorted (e.g., they're integers), in which case you can do something like a counting sort.
With finding your spouse, I don't think a naive comparison-based sort is necessary. You should have a feeling for how solid the match is just on the basis of the match alone. You can estimate the value of that match without necessarily having to compare it to all other possible matches one-by-one.
Of course, experience and wisdom in life are tremendously helpful in this regard. But at some point you're going to just have to make the call yourself.
This dataset appears to be the same one used for the "where you grow up affects how much money you make" article and seems to directly speak to what a few commenters here noticed about that one: it was looking at household income, so less likely to marry -> more likely to be two datapoints making less money in two separate households than one datapoint making a higher combined total.
"Here, better or worse is measured by the household incomes of children in early adulthood. This makes New York look worse than it would if individual incomes were used, because it, along with Northern California, has some of the lowest marriage rates in the country. Manhattan is actually better than most of the country at raising the individual incomes of poor girls. Marriage rates, too, are strongly affected by where children grow up."
But that seems to essentially invalidate broad swaths of the original article, instead of merely being mentioned in the last paragraph in regard to just two areas...
There are still probably some interesting outliers, but it looks like they're not the ones discussed in the original. For instance, I noticed that LA county, one of the listed lower-income-causing ones in the original article, is indeed 4 percentage points less likely to marry. But then I saw that it's neighbor, Ventura County, is both 3 percentage points less likely to marry by 26 and has households making 7 percent more at age 26. That's potentially interesting. Doubtless there are others that are more likely to marry and also lower income...
Could this really just be a map of the racial distribution of America? According to [1], 16% of white Americans aren't married by the time they hit 25, whereas 33% of black Americans aren't married by that same age.
I originally picked up on this because I looked at a county whose population is dominated by a very poor, drug ridden city populated almost entirely by black Americans, and was surprised to see that that county may count as a "liberal" area.
You make a good point, but as a side note, this was rather confusing:
> 16% of white Americans aren't married by the time they hit 25, whereas 33% of black Americans aren't married by that same age.
That seemed way too low considering the median age of first marriage in the US is now approaching 30. The stat you quote is actually 16% of (non-Hispanic) white Americans and 33% of black Americans who are 25 or older are not married.
Does the article you cite support your claim? It states that 16% of whites over the age of 25 have not married, which is quite different than "16% of white Americas aren't married by the time they hit 25."
I feel like this article, mostly the small town section, is in need of some statistics. The "small town effect" should be looked at very critically because lower populations equal a lower sample size, lower sample size means the data is more prone to extremes.
Any attempt to correct for a non-heterosexual population? I'd imagine anyone who doesn't fit in to red-state society would flee to a city and, at least until recently, not get married.
[+] [-] IvyMike|11 years ago|reply
I have to imagine that reasoning occurs more often with those from smaller towns than those from the big city.
[+] [-] nilkn|11 years ago|reply
I think I would respond to this viewpoint with a CS analogy. You can do a comparison based sort, in which you really don't have an absolute sense of the final sorted position of any object just by looking at it, or you might know extra information about the objects being sorted (e.g., they're integers), in which case you can do something like a counting sort.
With finding your spouse, I don't think a naive comparison-based sort is necessary. You should have a feeling for how solid the match is just on the basis of the match alone. You can estimate the value of that match without necessarily having to compare it to all other possible matches one-by-one.
Of course, experience and wisdom in life are tremendously helpful in this regard. But at some point you're going to just have to make the call yourself.
[+] [-] unknown|11 years ago|reply
[deleted]
[+] [-] majormajor|11 years ago|reply
This is even noted in the other article: http://www.nytimes.com/interactive/2015/05/03/upshot/the-bes...
"Here, better or worse is measured by the household incomes of children in early adulthood. This makes New York look worse than it would if individual incomes were used, because it, along with Northern California, has some of the lowest marriage rates in the country. Manhattan is actually better than most of the country at raising the individual incomes of poor girls. Marriage rates, too, are strongly affected by where children grow up."
But that seems to essentially invalidate broad swaths of the original article, instead of merely being mentioned in the last paragraph in regard to just two areas...
There are still probably some interesting outliers, but it looks like they're not the ones discussed in the original. For instance, I noticed that LA county, one of the listed lower-income-causing ones in the original article, is indeed 4 percentage points less likely to marry. But then I saw that it's neighbor, Ventura County, is both 3 percentage points less likely to marry by 26 and has households making 7 percent more at age 26. That's potentially interesting. Doubtless there are others that are more likely to marry and also lower income...
[+] [-] oh_sigh|11 years ago|reply
I originally picked up on this because I looked at a county whose population is dominated by a very poor, drug ridden city populated almost entirely by black Americans, and was surprised to see that that county may count as a "liberal" area.
[1] http://www.npr.org/sections/codeswitch/2014/09/26/351736134/...
[+] [-] magicalist|11 years ago|reply
> 16% of white Americans aren't married by the time they hit 25, whereas 33% of black Americans aren't married by that same age.
That seemed way too low considering the median age of first marriage in the US is now approaching 30. The stat you quote is actually 16% of (non-Hispanic) white Americans and 33% of black Americans who are 25 or older are not married.
[+] [-] mediaman|11 years ago|reply
[+] [-] tyrel|11 years ago|reply
[+] [-] Red_|11 years ago|reply
Wonder why?
[+] [-] pgonda|11 years ago|reply
[+] [-] drblast|11 years ago|reply
[+] [-] omgitstom|11 years ago|reply