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Economics before romance: How marriage differs in poor countries

Economic concerns can take much of the sentimentality and romance out of marriage, says Judith Bruce, the senior associate and policy analyst at the Population Council.

Judith Bruce: When I decided to do this work—obviously I’m a female and I was an adolescent once—I began to think about the shape of females’ lives and I became very interested in knowing more about the most excluded girls in the most excluded and poorest communities.

Obviously all women face some difference in their experience (regardless of where they are) as what men experience, but it was much more dramatic when I went to the poorer places and saw how desperately dependent females in sub-Saharan Africa, the Middle East (where I lived and worked for a long time), Central America, Asia—how much more tied explicitly their futures were to the process that was called “marriage” and child-bearing.

I was also struck that the words that were used to describe the experience gave a very false impression. These were not sentimental marriages—though many of them succeeded mind you—they were made as an economic calculation of families. Girls accepted from an early age that without agreeing to their family’s wishes they would not have a place in society; there were cautionary tales of the girls who didn’t marry or who didn’t bear children, stories of little girls thrown in the fire, “young brides,” as they’re called, thrown into the fire because they didn’t produce a child—really dramatic consequences.

At the same time wherever you went you saw the women and girls working, but nobody called it “work,” they said they’re “helping their partners.” When we started looking into the data we saw that female income was rededicated to others at a rate of ten to 20 times that of male income.

So if a woman makes a dollar that dollar is ten times more powerful than a dollar in a man’s hands.

So the language—not only were the conditions under which they were forced into marriage represented as something sentimental and normative, but also the tremendous economic contribution they made and indeed their dominance in providing for older and younger dependents was consistently named something else.

I was once in India with a very well known expert in agricultural development, which is very, very male dominated and at that time a really technologically-focused field, and he turned to me and said, “I see! Women can be farmers too!” The assumption was that “farmer” meant male.

And language is like that all the way through.

So when a woman is doing it, “Oh she’s helping her children, she’s not earning.” Women themselves, girls themselves will describe what they do in minimizing and denigrating terms: “Oh I just help out.” There’s even an issue of their feeling like they have higher status if a man is supporting them, which is rare enough. So one African country I was working in, I remember they were having trouble with the census because women would claim that their husbands were supporting them (because it was seen as a status that he was supporting them rather than the reverse). Females themselves saw being dependent on a male as a goal, because the society would not acknowledge the extremely diverse and heavy burdens that females carry economically from a very young age.

I think one of the really important differences between male and female experience is that—pretty much everywhere, especially in the developing world but I think pretty much everywhere—sexual and marital markets and labor markets for females are completely connected and aligned. To put it kind of bluntly, who you have sex with, inside or outside of marriage, determines in many cases whether you’re socially included in your economic prospects, and not because you’re necessarily being supported by that person, but because they are gatekeepers to an economy.

A male who does not marry or have children is not necessarily destitute, but in most societies if you ask the question: “Can this girl, let’s say I have a 12-year-old girl in front of me, if you said ‘Well you don’t marry and you don’t have children,’” then in effect that’s like a death sentence, because there’s no social structure she can fit in, she’s stigmatized, and she doesn’t have an economic base either.

So marriage is, above all in most places (with other sentimental value it may have), an economic arrangement by which women’s time, by which—girls, more often, a girl’s time, labor, and fertility is ceded, it’s an emolument, it’s basically an essential economic exchange.

Now it’s all dressed up and it’s called marriage, and it’s interesting right now in the current time, the word “marriage” has been made sacred again in people’s minds because there are excluded groups, you know, the idea of gay marriage; what people think marriage means in terms of sharing and caring and partnership does not apply in many things called marriages around the world; it is a construct for controlling young females.

Child marriage is an example of an economic bargain.

I hate to just use the word “marriage” there because it kind of sanitizes the concept, but imagine: promising a girl in marriage at a young age is basically ceding her control over her spatial movements, her body, her bodily functions, her privacy, physical integrity.

Female genital mutilation, for example, persists not because it’s just some idea but because a girl is seen as non-marriageable if she’s not circumcised or mutilated in the societies that practice that. So in order for that girl to have a social place, through which is attached some economic rights or some economic access—certainly a lot of economic responsibility—she MUST be married.

People used to look at women’s status as a series of individual traits: for example, are you educated? Are you living away from the family? Are you contributing economically? And Susan Greenhall did a wonderful article years ago looking at the “East Asia tigers” and she pointed out these were the countries that were identified as the first, really, emerging market economies.

And she pointed out something very important: she said the families decide that they will educate the girl to the level at which she can join a free trade zone job, and she will be sent off to work and earn.

Now she lives away from home, she’s been educated to some uncommonly high level or she’s received some education and she sending money home.

And she’s not a free person, she’s actually being used to support, let’s say, the higher education of her brother.

Unless you analyze what the CHOICE is of the female and then contrast it with a choice of the male—I always go back and I say, “All right. In this society, in this setting, could a young female decide that she wanted neither to be sexually active—or to have children or to be married—and still have a social place and economic possibilities?” And the answer is often “No.”

In the United States today it’s increasingly “Yes, you can do that.” Obviously there’s still conditions, so it’s a kind of a process standard. For males whether they’re married or not doesn’t determine who they might vote for, it doesn’t determine pretty much who they live with, it doesn’t determine how they make their money; if they are married their partner doesn’t control whether they can earn or not.

The same isn’t true with females: often marriage means that the man is—by law even, not just by practice—controls her earnings, can decide whether she can have a passport. She needs permission to do almost anything: drive, et cetera.

So it’s a very, very different experience. It’s not simply “that men and women are different,” it’s that there are dramatically different structures of control over females and their sexuality/fertility are tied to their economic survival.

Financial concerns can take much of the sentimentality and romance out of marriage, says Judith Bruce, the senior associate and policy analyst at the Population Council. In poorer countries especially, marriage becomes more of an arrangement by which women’s time, labor, and fertility are ceded as an essential economic exchange.

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Predicting PTSD symptoms becomes possible with a new test

An algorithm may allow doctors to assess PTSD candidates for early intervention after traumatic ER visits.

Image source: camillo jimenez/Unsplash
Technology & Innovation
  • 10-15% of people visiting emergency rooms eventually develop symptoms of long-lasting PTSD.
  • Early treatment is available but there's been no way to tell who needs it.
  • Using clinical data already being collected, machine learning can identify who's at risk.

The psychological scars a traumatic experience can leave behind may have a more profound effect on a person than the original traumatic experience. Long after an acute emergency is resolved, victims of post-traumatic stress disorder (PTSD) continue to suffer its consequences.

In the U.S. some 30 million patients are annually treated in emergency departments (EDs) for a range of traumatic injuries. Add to that urgent admissions to the ED with the onset of COVID-19 symptoms. Health experts predict that some 10 percent to 15 percent of these people will develop long-lasting PTSD within a year of the initial incident. While there are interventions that can help individuals avoid PTSD, there's been no reliable way to identify those most likely to need it.

That may now have changed. A multi-disciplinary team of researchers has developed a method for predicting who is most likely to develop PTSD after a traumatic emergency-room experience. Their study is published in the journal Nature Medicine.

70 data points and machine learning

nurse wrapping patient's arm

Image source: Creators Collective/Unsplash

Study lead author Katharina Schultebraucks of Columbia University's Department Vagelos College of Physicians and Surgeons says:

"For many trauma patients, the ED visit is often their sole contact with the health care system. The time immediately after a traumatic injury is a critical window for identifying people at risk for PTSD and arranging appropriate follow-up treatment. The earlier we can treat those at risk, the better the likely outcomes."

The new PTSD test uses machine learning and 70 clinical data points plus a clinical stress-level assessment to develop a PTSD score for an individual that identifies their risk of acquiring the condition.

Among the 70 data points are stress hormone levels, inflammatory signals, high blood pressure, and an anxiety-level assessment. Says Schultebraucks, "We selected measures that are routinely collected in the ED and logged in the electronic medical record, plus answers to a few short questions about the psychological stress response. The idea was to create a tool that would be universally available and would add little burden to ED personnel."

Researchers used data from adult trauma survivors in Atlanta, Georgia (377 individuals) and New York City (221 individuals) to test their system.

Of this cohort, 90 percent of those predicted to be at high risk developed long-lasting PTSD symptoms within a year of the initial traumatic event — just 5 percent of people who never developed PTSD symptoms had been erroneously identified as being at risk.

On the other side of the coin, 29 percent of individuals were 'false negatives," tagged by the algorithm as not being at risk of PTSD, but then developing symptoms.

Going forward

person leaning their head on another's shoulder

Image source: Külli Kittus/Unsplash

Schultebraucks looks forward to more testing as the researchers continue to refine their algorithm and to instill confidence in the approach among ED clinicians: "Because previous models for predicting PTSD risk have not been validated in independent samples like our model, they haven't been adopted in clinical practice." She expects that, "Testing and validation of our model in larger samples will be necessary for the algorithm to be ready-to-use in the general population."

"Currently only 7% of level-1 trauma centers routinely screen for PTSD," notes Schultebraucks. "We hope that the algorithm will provide ED clinicians with a rapid, automatic readout that they could use for discharge planning and the prevention of PTSD." She envisions the algorithm being implemented in the future as a feature of electronic medical records.

The researchers also plan to test their algorithm at predicting PTSD in people whose traumatic experiences come in the form of health events such as heart attacks and strokes, as opposed to visits to the emergency department.

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