Salsaclysm: Who We Are (When We Think No One’s Looking).

9 Jun

The following references are from:
Dataclysm:  Who We Are (When We Think No One's Looking)
by Christian Rudder ».

A book about big data and what it tells us about male-female attraction.

Part 1: What Brings Us Together – Chapter 1: Wooderson’s Law, Pages 34-36:
“…
That’s the data’s way of saying that until thirty, a woman prefers slightly older guys; afterward, she likes them slightly younger. Then at forty, the progression breaks free of the diagonal, going practically straight down for nine years. That is to say, a woman’s tastes appear to hit a wall. Or a man’s looks fall off a cliff, however you want to think about it. If we want to pick the point where a man’s sexual appeal has reached its limit, it’s there: forty. …

… A woman’s at her best when she’s in her very early twenties. Period. And really my plot doesn’t show that strongly enough. The four highest-rated female ages are twenty, twenty-one, twenty-two, and twenty-three for every group of guys but one … And after he hits thirty, the latter half of our age range (that is, women over thirty-five) might as well not exist. Younger is better, and youngest is best of all, and if “over the hill” means the beginning of a person’s decline, a straight woman is over the hill as soon as she’s old enough to drink. …”

Part 1: What Brings Us Together - Chapter 1: Wooderson's Law, Pages 34-36

Big data tells us what is obvious and observable on the dancefloor:
40-year-old salsa gigolos like to grindchata with 20-year-old salseras.
50-year-old salsa gigolos like to grindchata with 20-year-old salseras.
60-year-old salsa gigolos like to grindchata with 20-year-old salseras.
70-year-old salsa gigolos like to grindchata with 20-year-old salseras.
And yes, 80-year-old salsa gigolos like to grindchata with 20-year-old salseras.

Part 1: What Brings Us Together – Chapter 3: Writing on the Wall, Page 70:
“…
Sitewide, the copy-and-paste strategy underperforms from-scratch messaging by about 25 percent, but in terms of effort-in to results-out it always wins: measuring by replies received per unit effort, it’s many times more efficient to just send everyone roughly the same thing than to compose a new message each time. I’ve told people about guys copying and pasting, and the response is usually some variation of “That’s so lame.” When I tell them that boilerplate is 75 percent as effective as something original, they’re skeptical — surely almost everyone sees through the formula. But his last message is an example of a replicated text that’s impossible to see through, and, in a fraction of the time it would’ve taken him otherwise, the sender got five replies from
exactly the type of woman he was looking for. And let me tell you something. Nearly every single thing on my desk, on my person, probably in my entire home, was made in a factory alongside who knows how many copies. I just fought a crowd to pick up my lunch, which was a sandwich chosen from a wall of sandwiches. Templates work. Our social-smoking architecture-loving backpacker is just doing what people have always done: harnessing technology. In this case his innovation is using a few keyboard shortcuts to save himself some time. …”

Part 1: What Brings Us Together - Chapter 3: Writing on the Wall, Page 70

And chances are, a 20-year-old salsera is going to be a novice. So a 40-year-old salsa gigolo should learn how to dance with beginners. Or better yet, a 30-year-old salsa gigolo should spend 10 years dancing with beginners, so by the time he’s a 40-year-old salsa gigolo, he’ll have amassed the skills and experience to make a 20-year-old novice salsera happy on the dancefloor.

A 40-year-old salsa gigolo will have learned that a 20-year-old novice salsera won’t notice that the moves he leads are really basic, or that he’s used the same moves all day long, day after day, week after week, with one 20-year-old novice salsera after another. The 40-year-old salsa gigolo, who hasn’t learned, is trying to lead the 20-year-old novice salsera through all sorts of complicated crap that he thinks will impress her. Or worse, he’s showing her how to count 1-2-3, 5-6-7, as if it’s her fault he can’t lead her into a basic step. No excuses necessary, just don’t do this.

Part 2: What Pulls Us Apart – Chapter 6: The Confounding Factor, Page 107:
“…
These matrices show two negative trends, and two positive. Blacks are again unappreciated by non-black users, but Asian men have joined them in the red. On the positive side, women clearly prefer men of their own race — they’re more “race-loyal” than men — but they also express a clear, secondary, preference for white men. …”

Part 2: What Pulls Us Apart - Chapter 6: The Confounding Factor, Page 107

If you blindfold a salsa gigolo and ask him to lick the ear of an Angolan salsera, a Korean salsera, and an Irish salsera, he’d still choose to grindchata with the 20-year-old salsera.

Part 2: What Pulls Us Apart – Chapter 7: The Beauty Myth in Apotheosis, Pages 120-121:
“…
Success and beauty are correlated for both sexes, but you can see that the slope of the red line is always steeper. On Facebook, every percentile of attractiveness gives a man two new friends. It gives a woman three. On Shiftgig, the curves aren’t even comparable in this way. The female curve is exponential and the male is linear. Moreover, they hold whether the
hiring manager, the person doing the interviewing, is a man or a woman. In either case, the male candidates’ curves are a flat line — a man’s looks have no effect on his prospects — and the female graphs are exponential. So these women are treated as if they’re on OK-Cupid, even though they’re applying for a job. Male HR reps weigh the female applicants’ beauty as they would in a romantic setting — which is either depressing or very, very exciting, depending on whether you’re a lawyer with a litigation practice. And female employers view it through the same (seemingly sexualized) lens, despite there (typically) being no romantic intent.

It is hardly fresh intellectual ground that beauty matters, and that it matters more for women. For example, a foundational paper of social psychology is called “What Is Beautiful Is Good.” It was the first in a now long line of research to establish that good-looking people are seen as more intelligent, more competent, and more trustworthy than the rest of us. More attractive people get better jobs. They are also acquitted more often in court, and failing that, they get lighter sentences. As Robert Sapolsky notes in the Wall Street Journal, two Duke neuropsychologists are working on why: “The medial orbitofrontal cortex of the brain is involved in rating both the beauty of a face and the goodness of a behavior, and the level of activity in that region during one of those tasks predicts the level during the other. In other words, the brain … assumes that cheekbones tell you something about minds and hearts.” On a neurological level, the brain registers that ping of sexual attraction — Ooh, she’s hot — and everything else seems to be splash damage.

To my second point, that beauty affects women in particular, Naomi Wolf’s bestseller The Beauty Myth showed that better than I ever could. In short, my raw findings here are not new. What is new is our ability to test ideas, established ones, famous ones even, against the atomized actions of millions. That granularity gives strength and nuance to previous work and even suggests ways to build on it.

The paper “What Is Beautiful” was based on a research sample of only 60 subjects — barely adequate to prove the effect, let alone its many facets.* But now we can go from “What Is Beautiful Is Good” to asking “How Good?” and in what contexts. In sex, beauty is very good. In friendship, it’s only somewhat good, and when you’re looking for a job, the effect really depends on your gender. As for Wolf’s seminal work, we can confirm the truth behind her broad observation that “today’s woman has become her ‘beauty'” — three robust research sets agree that the correlation is strong. And, better, we can extend some of her most cogent arguments about beauty being a means of social control. Think about how the Shiftgig data changes our understanding of women’s perceived workplace performance. They are evidently being sought out (and exponentially so) for a trait that has nothing to do with their ability to do a job well. Meanwhile, men have no such selection imposed. It is therefore simple probability that women’s failure rate, as a whole, will be higher. And, crucially, the criteria are to blame, not the people. Imagine if men, no matter the job, were hired for their physical strength. You would, by design, end up with strong men facing challenges that strength has nothing to do with. In the same way, to hire women based on their looks is to (statistically) guarantee poor performance. It’s either that or you limit their opportunities. Thus Ms. Wolf: “The beauty myth is always actually prescribing behavior and not appearance.” She was speaking primarily in a sexual context, but here, we see how it plays out, with mathematical equivalence, in the workplace. …”

Part 2: What Pulls Us Apart - Chapter 7: The Beauty Myth in Apotheosis, Pages 120-121

However, it is a very rare 20-year-old salsera, who can give a seasoned salsa gigolo his salsa fix. She has to be pretty, too.

Technology – 2
Salsa Gigolo – 4

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