Anthropology Friday: Our Moslem Sisters pt. 3

Hausa woman, circa 1900

I desired to read a good ethnography of Middle Eastern life in the 1800s, but not happening upon one, I settled for Our Moslem Sisters: A Cry of Need from Lands of Darkness Interpreted by Those Who Heard It, edited by Annie Van Sommer and Samuel M. Zwemer. (Published in 1907.)

Sommer, Zwemer, and the book’s other contributing authors were Christian (Calvinist) missionaries, and as such, we should keep in mind that much of the book is an explicit appeal for more funding–but they are also people who were on the ground and actually lived there, spoke the language, and befriended the locals, so their observations are not without merit.

Today’s excerpts begin with “Soudan,” which I do not think is the modern nation of “Sudan,’ but the French colony of Soudan, today Mali.

Fulani woman

“Soudan”

“The form of Islam seen in the large centres of population in the Hausa States is that of a virile, aggressive force, in no sense effete or corrupted by the surrounding paganism. It has had no rival systems such as Hinduism or Buddhism to compete with, and until now has not come into conflict with Christianity. The distinctive characteristics of the African have, however, tended to increase in it sensualism and a laxity of morals, and this has stamped, to a large extent, the attitude toward women and the character of women as developed under its system….

“It is now generally acknowledged that these people—Fulanis—originally came from Asia, or at least are Semitic.

“They are the rulers of all this great empire, and have for a hundred years exercised a tyrannical rule over the Hausas and the pagan peoples whom they had succeeded in enslaving before British rule in turn overcame them. The Fulani women are many of them olive-colored; some are beautiful and all have the small features, thin lips, straight nose, and long straight hair associated with the Asiatic. The Fulani rulers, following the Eastern fashion, have large harems and keep their women very secluded.

“The late Emir of Zaria was terribly severe to all his people, and cruel to a degree with any of his wives who transgressed in any way or were suspected of unfaithfulness. In one instance in which a female slave had assisted one of his wives to escape, both being detected, the wife was immediately decapitated and the slave given the head in an open calabash and ordered by the Emir to fan the flies off it until next night!

“I have been admitted into the home of one such family, the home of one of the highest born of all the Fulani chiefs, saw two of the wives and bowed to them, but the two little girls of seven and eight years came to call on me. On the whole I was struck with the cheerful appearance of the wife and the sweetness of the two little girls, but the husband was a particularly nice man, I should think a kind husband, and I know a kind father. …

“The ease with which all Hausa women, but specially those of the middle and lower classes, can obtain divorce for almost any reason; also the frequency with which they can obtain redress for cruelty from their husbands in the native courts, gives them power and a position in the community not to be despised. A man, for instance, in order to get a girl of sixteen years in marriage will pay her parents a sum of perhaps ten or twelve pounds.

“If at any future time she desires to leave him and marry another man, she can do so by swearing before the native courts that they have quarrelled and that she no longer wishes to live with him. But if that is all she merely gets a paper of divorce and either herself or her next husband has to refund to the aggrieved former husband the sum originally paid for her. If, however, she can prove violence or injury from her husband she has not to pay him anything, but may even in some cases get damages.

“A girl is usually given the option of refusing the man whom her parents have arranged for her to marry. This is not often done, but I have known of some cases in which the girl has availed herself of the privilege, and stated that she prefers some one else, in which case the engagement is broken and the new marriage arranged at once with the man of her choice. …

“The existence of a large class of pagan slave girls, who have been caught and brought from their own homes and carried into the Hausa country to become members of the harem of some of the Hausas, also complicates and intensifies the evil; for this mixture only tends to lower the standards and make the facilities for sin tenfold easier….

“The knowledge that a wife may leave at will, that less labor can be got out of a cruelly-treated slave wife, and that little girls can leave home and find a place elsewhere, all have tended to make women’s lives freer, and to some extent less hard in the Central Soudan than in North Africa.”

Arabia:

“The same men who themselves indulge in the grossest form of immorality become very angry and cruel if there is a breath of scandal against their women. In Bahrein, a young pearl-diver heard a rumor that his sister was not a pure woman; he returned immediately from the divings and stabbed her in a most diabolical way without even inquiring as to the truth of the matter. She died in great agony from her injuries, and the brother was acquitted by a Moslem judge …

“It is a common thing for us to be asked to prescribe poison for a rival wife who has been added to the household and for the time being is the favorite. Through jealousy some of these supplanted wives plunge into a life of sin. I do not know anything more pathetic than to have to listen to a poor soul pleading for a love-philter or potion to bring back the so-called love of a perfidious husband. Women, whether rich or poor, naturally prefer to be the only wife. … Some divorced women return to the house of their parents, while the homeless ones are most miserable and find escape from misery only in death. …

“A man may have a new wife every few months if he so desires, and in some parts of Arabia this is a common state of affairs among the rich chiefs. The result of all this looseness of morals is indescribable. Unnatural vice abounds, and so do contagious diseases which are the inheritance of poor little children.

“There is a very large per cent. of infant mortality partly on this account, and partly on account of gross ignorance in the treatment of the diseases of childhood. …

However

“Lady Ann Blunt, who has travelled among the Bedouins, says, ‘In more than one sheikh’s tent it is the women’s half of it in which the politics of the tribe are settled.'”

Yemen

“Called one day to see a Somali woman I missed the whip usually seen in a Somali’s house, and jokingly asked how her husband managed to keep her in order without a whip. She, taking her husband and me by the hand, said, “You are my father and this is my husband. Love unites us, and where love is there is no need for whips.”

“I was so pleased with her speech that I offered her husband, who was out of work, a subordinate place in our dispensary. Yet less than a month later I heard that he had divorced his wife and turned her out of doors….

“The following case will, I think, illustrate the usual attitude of the Arabs in the Yemen towards womankind:

“A man whose wife had been in labor two days came asking for medicine to make her well. My reply was that it was necessary to see the woman before I could give such a drug as he wished. “Well,” said he, “she will die before I allow you or any other man to see her,” and two days after I heard of her death.”

Lebanon:

“In Beirut, among the better classes girls are not married as young as they used to be, though occasionally you hear of instances, as in the case of a woman who had eight daughters and married two of them, twins, at the age of eight. She gained nothing by this cruel act as they were soon divorced and sent home.

“One reason for child-marriages among Mohammedans in Syria is the conscription which demands for the army every young man of eighteen. The one who cannot afford to escape conscription by paid substitutes or money may be exempt if he has a wife dependent upon him. When he is sixteen or seventeen his family send off to some distant town for a young girl who is a destitute orphan, and this child is married to the youth,—she may be ten years old, or nine, or even eight, and cases are known where a girl of seven has been married to a boy of sixteen. …

“Sad stories are told of those who are put out to service, especially when they go to Turkish families. It is not very common, fortunately, for there is always the fear that the men in the family, regarding them as lawful prey, will ill-treat them. Girls disgraced in this way have a terrible fate.

“A friend came to us one day, weeping because of a dreadful thing which had just come to her knowledge, too late, alas! for any help to be given. The daughter of a neighbor, a poor man, had been sent out to service, and the worst befell her. She was sent home in disgrace,—her father was obliged to receive her, but he would not recognize her or have anything to do with her till one day he ordered her to go out into the garden and dig in a spot he indicated. Each day he came to see what she had accomplished, till at last there was a hole deep enough for her to stand in, her full height. Her father then called his brothers, they brought lime, poured it over her, and then buried the child alive in the hole she herself had dug. She was only twelve years old! …

“I must not omit to say that in the smaller Mohammedan settlements where there is much intermarrying in families, there is almost no divorce, for even if a man wishes it, he must be very courageous to brave the united wrath of the whole circle of female relatives or of his enraged uncle or cousin, who resents bitterly having his daughter sent back to her home. …

Druze woman wearing a tantour, 1870s, Lebanon

“Among the Druzes, divorce is even more common than it is among the true Mohammedans, and the state of morals is very low. The Druzes are an interesting, even fascinating people. They live on the Lebanons and inland on the Druze mountains of the Hauran, and are a warlike independent race, of fine physique, and most polished, courteous manners. Some of their women are very beautiful and their peculiar costumes are most becoming and picturesque. … As was said before, they are classed with the Mohammedans although they have their own prophet, Hakim, and they take pride in having their own secret religion, which is little more than a brotherhood for political purposes.”

EvX: The book makes no mention of the Yazidis, but these days they post on Twitter about how matters stand between them and their neighbors, the Islamic State:

I was pregnant and taken as sex slave with my five years daughter by SuNn! Neighbors. After ISIS killed my husband and almost all members of our family I decided to suicide, I took poison but didn’t die, I lost my unborn baby. I was sold many times.

 

Advertisements

Sacrifice Everything Memes

I woke up this morning with the realization that I needed to make a meme about Nongqawuse. (Context.)

These were the result:

In 1997, 39 members of the Heaven’s Gate cult committed suicide in order to reach a UFO they believed was accompanying comet Hale-Bopp.

In 1978, 918 followers of cult leader Jim Jones committed suicide by drinking poisoned Kool-Aid–the origin of the phrase, “Don’t drink the Kool-Aid.”

 

Mathematician Ted Kaczynski, unable to find a publisher for his manifesto, Industrial Society And Its Future, turned to mailing bombs to professors.

 

 

82 Branch Davidians, led by David Koresh, died when their compound burned down during a raid by the ATF. It appears that the Branch Davidians set the fire themselves.

 

The Thugs were an Indian cult that ritually strangled and murdered travelers.

 

Timothy McVeigh killed 168 people in 1995 when he bombed the Alfred P. Murrah Federal Building in Oklahoma City, in what he claimed was revenge for ATF’s siege against the Branch Davidians.

Hong Xiuquan claimed to be Jesus’ little brother and lead the Taiping Rebellion, which resulted in the deaths of 20-30 million people.

Lee Harvey Oswald

Nongqawuse was a Xhosa prophet who convinced her people that if they sacrificed all of their cattle, the British would be “swept into the sea.” The Xhosa sacrificed their cattle, the British did not get swept into the sea, and mass famine resulted.

 

Charles Manson was a cult leader whose followers carried out 9 murders in the 70s.

 

Elliot Rodger

 

By request:

 

Moloch

 

Every month of the Aztec year had a specific form of human sacrifice devoted to different deities.

 

Nike is giving terrible advice. Anyone who encourages you to sacrifice everything is probably a charlatan and actually wants you to sacrifice everything for them.

Believe in something sensible, true, and not likely to result in mass death.

Book Club Announcement: How to Create a Mind

Next Book Club pick: How to Create a Mind: The Secret of Human Thought Revealed, by Ray Kurzweil. (This time we will be taking a different approach, and the discussion will be much shorter.)

From the Amazon blurb:

Ray Kurzweil is arguably today’s most influential—and often controversial—futurist. In How to Create a Mind, Kurzweil presents a provocative exploration of the most important project in human-machine civilization—reverse engineering the brain to understand precisely how it works and using that knowledge to create even more intelligent machines.

Discussion starts September 24th.

A Little Review of Big Data Books

I recently finished three books on “big data”– Big Data: A Revolution That Will Transform How We Live, Work, and Think, by Viktor Mayer-Schönberger and Kenneth Cukier; Everybody Lies: Big Data, New Data, and What the Internet can tell us about who we Really Are, by Seth Stephens-Davidowitz; and Big Data At Work: Dispelling the Myths, Uncovering the opportunities, by Thomas H. Davenport.

None of these books was a whiz-bang thriller, but I enjoyed them.

Big Data was a very sensible introduction. What exactly is “big data”? It’s not just bigger data sets (though it is also that.) It’s the opportunity to get all the data.

Until now, the authors point out, we have lived in a data poor world. We have had to carefully design our surveys to avoid sampling bias because we just can’t sample that many people. There’s a whole bunch of math done over in statistics to calculate how certain we can be about a particular result, or whether it could just be the result of random chance biasing our samples. I could poll 10,000 people about their jobs, and that might be a pretty good sample, but if everyone I polled happens to live within walking distance of my house, is this a very representative sample of everyone in the country? Now think about all of those studies on the mechanics of sleep done on whatever college students or homeless guys a scientist could convince to sleep in a lab for a week. How representative are they?

Today, though, we suddenly live in a data rich world. An exponentially data rich world. A world in which we no longer need to correct for bias in our sample, because we don’t have to sample. We can just get… all the data. You can go to Google and find out how many people searched for “rabbit” on Tuesday, or how many people misspelled “rabbit” in various ways.

Data is being used in new and interesting (and sometimes creepy) ways. Many things that previously weren’t even considered data are now being quantitized–like one researcher quantitizing people’s backsides to determine whether a car is being driven by its owner, or a stranger.

One application I find promising is using people’s searches for various disease symptoms to identify people who may have various diseases before they seek out a doctor. Catching cancer patients earlier could save millions of lives.

I don’t have the book in front of me anymore, so I am just going by memory, but it made a good companion to Auerswald’s The Code Economy, since the modern economy runs so much on data.

Everybody Lies was a much more lighthearted, annecdotal approach to the subject, discussing lots of different studies. Davidowitz was inspired by Freakonomics, and he wants to use Big Data to uncover hidden truths of human behavior.

The book discusses, for example, people’s pornographic searches, (as per the title, people routinely lie about how much porn they look at on the internet,) and whether people’s pornographic preferences can be used to determine what percent of people in each state are gay. It turns out that we can get a break down of porn queries by state and variety, allowing a rough estimate of the gay and straight population of each state–and it appears that what people are willing to tell pollsters about their sexuality doesn’t match what they search for online. In more conservative states, people are less likely to admit to pollsters that they are gay, but plenty of supposedly “straight” people are searching for gay porn–about the same number of people as actually admit to being gay in more liberal states.

Stephens-Davidowitz uses similar data to determine that people have been lying to pollsters (or perhaps themselves) about whom they plan to vote for. For example, Donald Trump got anomalously high votes in some areas, and Obama got anomalously low votes, compared to what people in those areas told pollsters. However, both of these areas correlated highly with areas of the country where people made a lot of racist Google searches.

Most of the studies discussed are amusing, like the discovery of the racehorse American Pharaoh. Others are quite important, like a study that found that child abuse was probably actually going up at a time when official reports said it wasn’t–the reports probably weren’t showing abuse due to a decrease in funding for investigating abuse.

At times the author steps beyond the studies and offers interpretations of why the results are the way they are that I think go beyond what the data tells, like his conclusion that parents are biased against their daughters because they are more concerned with girls being fat than with boys, or because they are more likely to Google “is my son a genius?” than “is my daughter a genius?”

I can think of a variety of alternative explanations. eg, society itself is crueler to overweight women than to overweight men, so it is reasonable, in turn, for parents to worry more about a daughter who will face cruelty than a boy who will not. Girls are more likely to be in gifted programs than boys, but perhaps this means that giftedness in girls is simply less exceptional than giftedness in boys, who are more unusual. Or perhaps male giftedness is different from female giftedness in some way that makes parents need more information on the topic.

Now, here’s an interesting study. Google can track how many people make Islamophobic searches at any particular time. Compared against Obama’s speech that tried to calm outrage after the San Bernardino attack, this data reveals that the speech was massively unsuccessful. Islamophobic searches doubled during and after the speech. Negative searches about Syrian refugees rose 60%, while searches asking how to help dropped 35%.

In fact, just about every negative search we cold think to test regarding Muslims shot up during and after Obama’s speech, and just about every positive search we could think to test declined. …

Instead of calming the angry mob, as everybody thought he was doing, the internet data tells us that Obama actually inflamed it.

However, Obama later gave another speech, on the same topic. This one was much more successful. As the author put it, this time, Obama spent little time insisting on the value of tolerance, which seems to have just made people less tolerant. Instead, “he focused overwhelmingly on provoking people’s curiosity and changing their perceptions of Muslim Americans.”

People tend to react positively toward people or things they regard as interesting, and invoking curiosity is a good way to get people interested.

The author points out that “big data” is most likely to be useful in fields where the current data is poor. In the case of American Pharaoh, for examples, people just plain weren’t getting a lot of data on racehorses before buying and selling them. It was a field based on people who “knew” horses and their pedigrees, not on people who x-rayed horses to see how big their hearts and lungs were. By contrast, hedge funds investing in the stock market are already up to their necks in data, trying to maximize every last penny. Horse racing was ripe for someone to become successful by unearthing previously unused data and making good predictions; the stock market is not.

And for those keeping track of how many people make it to the end of the book, I did. I even read the endnotes, because I do that.

Big Data At Work was very different. Rather than entertain us with the success of Google Flu or academic studies of human nature, BDAW discusses how to implement “big data” (the author admits it is a silly term) strategies at work. This is a good book if you own, run, or manage a business that could utilize data in some way. UPS, for example, uses driving data to minimize package delivery routes; even a small saving per package by optimizing routes leads to a large saving for the company as a whole, since they deliver so many packages.

The author points out that “big data” often isn’t big so much as unstructured. Photographs, call logs, Facebook posts, and Google searches may all be “data,” but you will need some way to quantitize these before you can make much use of them. For example, companies may want to gather customer feedback reports, feed them into a program that recognizes positive or negative language, and then quantitizes how many people called to report that they liked Product X vs how many called to report that they disliked it.

I think an area ripe for this kind of quantitization is medical data, which currently languishes in doctors’ files, much of it on paper, protected by patient privacy laws. But people post a good deal of information about their medical conditions online, seeking help from other people who’ve dealt with the same diseases. Currently, there are a lot of diseases (take depression) where treatment is very hit-or-miss, and doctors basically have to try a bunch of drugs in a row until they find one that works. A program that could trawl through forum posts and assemble data on patients and medical treatments that worked or failed could help doctors refine treatment for various difficult conditions–“Oh, you look like the kind of patient who would respond well to melatonin,” or “Oh, you have the characteristics that make you a good candidate for Prozac.”

The author points out that most companies will not be able to keep the massive quantities of data they are amassing. A hospital, for example, collects a great deal of data about patient’s heart rates and blood oxygen levels every day. While it might be interesting to look back at 10 years worth of patient heart rate data, hospitals can’t really afford to invest in databanks to store all of this information. Rather, what companies need is real-time or continuous data processing that analyzes current data and makes predictions/recommendations for what the company (or doctor) should do now.

For example, one of the books (I believe it was “Big Data”) discussed a study of premature babies which found, counter-intuitively, that they were most likely to have emergencies soon after a lull in which they had seemed to be doing rather well–stable heart rate, good breathing, etc. Knowing this, a hospital could have a computer monitoring all of its premature babies and automatically updating their status (“stable” “improving” “critical” “likely to have a big problem in six hours”) and notifying doctors of potential problems.

The book goes into a fair amount of detail about how to implement “big data solutions” at your office (you may have to hire someone who knows how to code and may even have to tolerate their idiosyncrasies,) which platforms are useful for data, the fact that “big data” is not all that different from standard analytics that most companies already run, etc. Once you’ve got the data pumping, actual humans may not need to be involved with it very often–for example you may have a system that automatically updates drives’ routes with traffic reports, or sprinklers that automatically turn on when the ground gets too dry.

It is easy to see how “big data” will become yet another facet of the algorithmization of work.

Overall, Big Data at Work is a good book, especially if you run a company, but not as amusing if you are just a lay reader. If you want something fun, read the first two.