by Dan Charles

May 03, 2013 4:19 PM

It’s a captivating story: A global rice-growing revolution that started with a Jesuit priest in Madagascar, far from any recognized center of agricultural innovation. Every so often, it surfaces in the popular media — most recently in The Guardian, which earlier this year described farmers in one corner of India hauling in gigantic rice harvests without resorting to pesticides or genetic modification.

Rice farmers in Indonesia plant rice seedlings using the “system of rice intensification.”

Their secret? A “system of rice intensification,” or SRI, that the priest, Henri de Laulanié, who was French, developed 30 years ago. It’s now promoted by an international network of SRI evangelists, with a center at Cornell University. Among the secrets of SRI: transplanting rice seedlings into fields with great care, planting them far apart, and enriching the soil with compost. The result, according to SRI’s proponents, is an increase of 50 to 100 percent in yields, using 90 percent fewer seed and half as much water for irrigation.

But there’s a mystery surrounding SRI, as Christopher Barrett, an economist at Cornell University, discovered. “If this is all it’s cracked up to be, why isn’t everybody doing it?” says Barrett. And even some farmers who try it, abandon it — 15 to 40 percent of farmers, in some communities, studies show.

Barrett joined forces with Kazushi Takahashi from the Japan External Trade Organization, and took a closer look at a community of farmers in Indonesia, some of whom were using SRI. Their findings, recently released as a “working paper,” may help explain the mystery. (There’s also a Power Point presentation with photos.)

First of all, Barrett and Takahashi found that SRI did, in fact, boost the farmers’ yields of rice by an estimated 64 percent. But here’s the bad news: Even though the farmers were harvesting more rice and spending less on seeds and chemicals, their household income did not go up at all.

This apparent contradiction actually has a pretty simple explanation, Barrett says. Farming families in Indonesia — in fact, in much of the world — don’t just work on the farm. When they have time, they also find work elsewhere to earn more money.

But SRI demands more time for all that careful transplanting and soil improvement. And as a result, family members have less time for outside work, and that lost off-farm income cancels out any gain from the rice harvest. (Interestingly, although SRI reduced outside work, it did not appear to reduce the rate of school attendance among children.)

Norman Uphoff, a professor of government at Cornell who has been SRI’s most important advocate, says that what Barrett and Takahashi saw in Indonesia isn’t typical of other places. “If you go to China or India, you’ll find that farmers are saving labor with SRI, not using more labor,” he says, because farmers in those countries already are spending a lot of time in their rice fields. In addition, he says, farmers who stick with SRI soon find ways to do the work more quickly. “It’s not intrinsically labor-intensive; it’s initially labor-intensive,” he says.

Barrett agrees that his Indonesian observations don’t prove that the same thing is happening everywhere. But they do represent “a cautionary tale” about the ambiguous effects of agricultural innovation.

Agricultural scientists tend to focus on ways to make fields more productive. But according to Barrett, when it comes to improving the lives of rural people, high yields really are only one part of the picture.

通过Unraveling The Mystery Of A Rice Revolution : The Salt : NPR.

488: Harper High School, Part Two

We pick up where we left off last week in our second hour of stories from Harper High School in Chicago. We find out if a shooting in the neighborhood will derail the school’s Homecoming game and dance. We hear the origin story of one of Harper’s more prominent gangs. And we ask a group of teenage boys: where do you get your guns?

In the first hour of our Harper High School shows, Alex Kotlowitz talked to a junior named Devonte who a year earlier had accidentally shot and killed his 14-year-old brother. Devonte was forming a strong relationship with Crystal Smith, one of the social workers, and beginning to come to terms with both his grief and guilt. Alex checks back in with Devonte and finds out that his life has taken some troubling turns. (8 minutes) death • teenagers

Alex Kotlowitz

ACT FIVE: Reverse Turnaround Backflip.

Late in the semester, Principal Sanders takes a look at her budget. It doesn’t look good. She talks with Ben Calhoun about what is going to change — and who won’t be at Harper — next year. (7 minutes) education •teenagers

Ben Calhoun

ACT SIX: We Are Harper High School.

Harper High School isn’t alone. (3 minutes) crime

487: Harper High School, Part One

We spent five months at Harper High School in Chicago, where last year alone 29 current and recent students were shot. 29. We went to get a sense of what it means to live in the midst of all this gun violence, how teens and adults navigate a world of funerals and Homecoming dances. We found so many incredible and surprising stories, this show is a two-parter; Part One airs this week, Part Two is next week.

For more than 35 years, riders on the New York City subways and buses during their daily commute were graced with posters of beaming young women. While the women featured in each poster — all New Yorkers — were billed as “average girls,” they were also beauty queens in the nation’s first integrated beauty contest: Miss Subways, selected each month starting in 1941 by the public and professionally photographed by the country’s leading modeling agency.Photographer Fiona Gardner, captivated by old Miss Subways posters she’d seen, worked with journalist Amy Zimmer to track down 40 of the more than 200 former pageant winners. They’ve juxtaposed images of those women today with their Miss Subways photographs in their book, Meet Miss Subways. Several former winners featured in the book also shared their stories with the audio documentary project Radio Diaries.”When you looked at Miss Subways, you were looking at a star, no question about it,” Peggy Byrne, a 1952 Miss Subways, told Radio Diaries’ Samara Freemark. And when riders gazed at the Miss Subways posters, they were often seeing something more, something unusual: a group of young women far more diverse than other beauty queens at that point in American history.”Somewhere along the line it occurred to me I had never seen a clearly ethnic name on that poster,” says former Miss Subways Enid Berkowitz Schwarzbaum. “My name was distinctively Jewish, and that might have been part of the reason I might have said let’s give it a shot. Let’s see what happens.”Enid, of course, did go on to take the Miss Subways title in July 1946, when her poster proclaimed that the Hunter College student was “plugging for [a] B.A., but would settle for an M.R.S.” — code for a college-educated woman in the market for a husband.Two years later, Thelma Porter became the first black Miss Subways, more than three decades before Vanessa Williams became the first black Miss America in 1983. Latino and Asian Miss Subways all joined their white Miss Subways counterparts before the pageant ended in 1976.The Radio Diaries story, airing on All Things Considered, was produced by Samara Freemark, with help from Joe Richman and Ben Shapiro, and edited by Deborah George.

通过‘Miss Subways’: A Trip Back In Time To New York’s Melting Pot : The Picture Show : NPR.

by NPR Staff     December 16, 2012 2:53 PM  All Things Considered

采访录音

Alex Clare isn’t the first Orthodox Jew to have a recording career, but he may be the first to be dumped by one major company and rescued by another in the space of a few months. The British singer-songwriter released his debut album, The Lateness of the Hour, on Island Records last summer. But the label soon discovered how serious Clare was about his faith — especially when it came to the sabbath and high holy days, on which Orthodox Jews are forbidden to perform.

“When I signed to Island — you know, obviously a shomer Shabbos Jewish person — I don’t think they quite realized what that means,” Clare says. “I got offered a tour at Pesach, at Passover, and couldn’t perform.”

The offer Clare turned down was a slot opening for Adele. About four months later, he was dropped from Island’s roster, having failed to generate significant album sales or radio play. As Clare was figuring out his next move, he received a call from Microsoft, which was interested in using his song “Too Close” in a commercial. It was a deal that would make the song a hit and restart his career.

Speaking with NPR’s Guy Raz, Alex Clare discusses that surprising turn of events, as well as his beginnings in both music and religion.

Interview Highlights

On getting dropped from his label

“If you’re a musician, you’re a musician; you don’t ever get that out of your bones. You’re always going to want to play and sing and write music. But I knew I had to definitely have a rethink about how I was going to approach writing, and certainly how I was going to approach performing. The funny thing is, as I was dropped, I was just starting to sell out tours. … We were building this really nice buzz; it was just taking quite a while. And then I got the rug pulled out from underneath me, as it was.”

On becoming Orthodox in his early 20s

“My parents are like religious atheists. They’re not even slightly observant in any capacity. My parents are kind of into existentialism, actually. … For me, [religion] really came about much later in life. I could never call myself an atheist; my parents could, quite happily. I always felt like there was a little bit more out there, and was always into observing the world from a slightly more spiritual, as opposed to scientific, perspective. Gradually, boxes began to get ticked. I decided to start learning to read Hebrew and really try and understand it.”

On discovering his voice

“The sort of epiphany, for want of a better word, was probably around [age] 18. I was playing in a group in London; I was playing drums for them. I always sang, and I always played a little bit of guitar, but my main instrument was drums and that’s what I was focused on. I was singing backing vocals one day, and the singer of the band kind of turned around and said, ‘You know what? You should probably just sing. Because you’re drowning everybody else out.’”

通过Upended By Label Drama, Alex Clare Lands On His Feet : NPR.

By Ben Wieder

courtesy of Tan Jun

Online matchmaking is getting better at telling us whom we ought to like—and that’s not good.

Image credit: Frank Chimero

The air in Santa Cruz was warm and still as I sat among perfect roses in the backyard of the bride’s parents. At the key moment of this nontraditional Jewish wedding, the friend presiding over the ceremony took a moment to explain the Hebrew word kadosh. It’s translated as “holy,” or “the holy one,” but it also connotes the act of setting apart or elevating one thing above all other things of a type. Marriage is holy because each partner says, “You are the one person I choose out of all the people in the world.”

If only you could Google your way to The One. The search engine, in its own profane way, is a kadosh generator. Its primary goal is to find the perfect Web page for you out of all the Web pages in the world, to elevate it to No. 1.

The Santa Cruz couple had met in a time-honored way—through a friend—but the number of such encounters is decreasing. One reputable estimate suggests that 74 percent of singles looking for a mate now turn to dating sites like eHarmony, Match.com, and OkCupid, which use algorithms to pair people up based on answers to sets of questions.

But even e-yentas find prognosticating love difficult. Date-mining software needs lots of tuning to create good matches, so the services track everything would-be lovebirds do. Their romantic-data trails become grist for matchmaking improvements.

OkCupid, which according to The Boston Globe aspires to be the Google of online dating, has been particularly aggressive about tracking users. The company’s goal is to stimulate “three-ways”—a double entendre that, to someone at OkCupid, means a person sent a note, received a reply, and fired off a follow-up.

“Imagine if you had a video camera at every bar in the country,” Sam Yagan, a co-founder of OkCupid, told me. “You’d have all these data that reveal things about society and predict them. This isn’t a survey. It isn’t a lab experiment. These are millions of people going about their lives. We just happen to be able to track and quantify everything about it.”

The company can quantify things you could guess but might rather not prove. For instance, all races of women respond better to white men than they should based on the men’s looks. Black women, as a group, are the least likely to have their missives returned, but they are the most likely to respond to messages.

I asked Yagan whether OkCupid might try tailoring its algorithm to surface more statistically successful racial combinations. Such a measure wasn’t out of the question, he said. “Imagine we did a lot of research, and we found that there were certain demographic or psychographic attributes that were predictors of three-ways. Hispanic men and Indian women, say,” Yagan suggested. “If we thought that drove success, we could tweak it so those matches showed up more often. Not because of a social mission, but because if it’s working, there needs to be more of it.”

Imagine the reverse, though, in the past or future. What if the dating sites had existed in the 1950s? How would they have dealt with interracial matches? Given the female response to white men in 2010, should white men show up more often? “We could do some really screwed-up things,” Yagan admits. Imagine war broke out with China, causing Chinese users’ ratings to plummet: would dating Web sites start reducing the number of Chinese people showing up in other groups’ searches?

Algorithms are made to restrict the amount of information the user sees—that’s their raison d’être. By drawing on data about the world we live in, they end up reinforcing whatever societal values happen to be dominant, without our even noticing. They are normativity made into code—albeit a code that we barely understand, even as it shapes our lives.

We’re not going to stop using algorithms. They’re too useful. But we need to be more aware of the algorithmic perversity that’s creeping into our lives. The short-term fit of a dating match or a Web page doesn’t measure the long-term value it may hold. Statistically likely does not mean correct, or just, or fair. Google-generated kadosh is meretricious, offering a desiccated kind of choice. It’s when people deviate from what we predict they’ll do that they prove they are individuals, set apart from all others of the human type.

This article available online at:

http://www.theatlantic.com/magazine/archive/2010/12/take-the-data-out-of-dating/8299/

通过Take the Data Out of Dating – Magazine – The Atlantic.

Quid’s algorithm mapping software allows users to visualize the proliferation of ideas on the Internet. This representation of articles written about the Occupy Wall Street movement uses colors to group ideas together and lines to show a connection between articles.

Enlarge Courtesy of Quid

Quid’s algorithm mapping software allows users to visualize the proliferation of ideas on the Internet. This representation of articles written about the Occupy Wall Street movement uses colors to group ideas together and lines to show a connection between articles.

My favorite movie, Days of Heaven, is at the top of my recommendations list on Netflix. But I’ve never actually watched it on Netflix, so how did they know I like it?

“Every time a Netflix member streams a title from us, we learn a little bit more about what’s interesting to them,” says John Ciancutti, vice president of engineering at Netflix. Netflix has algorithms that mix customer information with other algorithms that group shows together. So if I enjoy Mad Men, it guesses that I might like other dramas with complicated male leads, like Breaking Bad — and it’s right.

If the Industrial Revolution was about extending the power of human muscle with inventions like the car, then the computer revolution is about extending the power of the human mind — and algorithms are the key to its success. These formulas find search results, pick the top story on the news feed of your Facebook page, and determine things like your credit score and trades on Wall Street.

Every day Netflix has dozens of engineers improving its algorithms. A huge whiteboard in the hallway of Netflix headquarters displays numbers in a grid, part of a contest to see who can come up with the best algorithms.

“Just in the last couple of months, we’ve run tests where we’ve improved overall streaming hours for members with a new algorithm that’s just a little bit better at making recommendations, which means it’s so powerful as far as delighting members that they are more likely to stay with the service versus not,” Ciancutti says.

Political Potential

For Netflix, it’s about keeping customers. But algorithms tailored to figure out individual tastes and interests are also being applied to the political arena. When Mitt Romney is on local TV in Ohio, it’s no surprise that he’d talk about local interests, like manufacturing jobs. But it would be even better if he could target his message directly to people who lost those jobs.

In this coming election, that’s exactly what Democrats and Republicans will be able to do.

“There’s been this explosion of data available over the last decade, frankly, at the individual level from voter files, from consumer sources, from other sources,” says Tom Bonier, co-founder of Clarity Campaign Labs, a company that uses algorithms to help Democrats target voters. “You can send one piece of mail about choice to one household, and to their neighbors you can send a piece of mail about the environment.”

In other words, there are more computers hoarding more data about us than ever before.

Algorithm As Crystal Ball

Sean Gourley is co-founder and CTO of Quid, a company that gets hired by governments and business to create algorithms. He says, “From an algorithms perspective, this is a great time to be alive. Algorithms are just frolicking in the mountains of data that they can play with.”

Gourley uses algorithms to predict insurgencies in Iraq and Afghanistan and help banks map developing markets for new technologies. As an experiment for NPR, he maps the development of the Occupy Wall Street movement. He uses algorithms to sort through about 40,000 blogs and articles written since the movement began and group similar ideas together.

“You can’t read all this as a human or even necessarily get what’s going on, so you start to apply algorithms to help kind of cluster, sort, put topics around them and ultimately visualize [it],” he says. What Gourley’s algorithm helps visualize is how ideas from the initial Occupy Wall Street rallies in New York spread to other groups and other parts of the country.

Gurley points to a computer screen. It’s filled with dots that are grouped into color clusters and connected by thin lines. One cluster represents politicians talking about taxing the wealthy. It’s far from the cluster that represents protesters.

Quid’s algorithm mapping software shows where discussion of higher taxes is taking place. Yellow dots represent articles that focus on taxation, while the teal dots show articles that don’t.

Enlarge Courtesy of Quid

Quid’s algorithm mapping software shows where discussion of higher taxes is taking place. Yellow dots represent articles that focus on taxation, while the teal dots show articles that don’t.

“When the politicians talk about Occupy Wall Street, they’re not really talking in Occupy Wall Street,” Gourley says. “They’re not talking within the cluster — they’re talking separately. And so when they talk about taxes and they talk about inequality it’s not really resonating [in the Occupy Wall Street cluster], or at least the language is quite different.”

Occupy Wall Street protesters meditate while a sign bearing their Twitter hashtag hangs from a railing in Zuccotti Park in October. Some activists accused Twitter of censorship because #OccupyWallStreet wasn’t appearing on trending lists.

Technology

Gourley clicks on another smallish cluster that represents “Bank Transfer Day,” an activist initiative that calls for people to move their accounts out of larger banks and into credit unions — you can see that people aren’t saying much about it anymore. A more recent cluster represents the issue of the courts using Twitter feeds as evidence in cases against protesters, and yet another tracks the conversation around Occupy Oakland, which is dominated by talk of police violence.

Proceed With Caution

Gourley imagines that information like this might be useful to politicians, police and political activists.

“We can start to think about where it’s come from,” he says. “We can start to think about how it’s evolved and we can start to think about where we want it to go and if we want to change the direction.”

But Gourley has concerns about other possible uses of algorithms. Netflix is just trying to keep its customers watching movies, which isn’t so bad, but he wonders what would happen if Google Maps knew that you were looking for a new car. Maybe when you looked up directions to a party, it would suggest a route that passes right past a dealership.

“[Has] it got your interest at heart or has it got making money from ads at heart?” Gourley says.

What worries him most is that we humans haven’t yet evolved to be as wary of algorithms as we are of used car salesmen.

通过Algorithms: The Ever-Growing, All-Knowing Way Of The Future : All Tech Considered : NPR.