How Medicare for All Looks From Britain

Babies are often expensive for creatures that are so small: they need new clothes, bedding, toys once they’re a little more agile, and the time you spend caring for them isn’t spent working, so your bank balance is run down for every day you aren’t in the office.

By posting a photograph of the bill she received after the birth of her second child, Washington Post columnist Elizabeth Bruenig also underscored that in the United States, the care you and your child receive during the delivery also costs money; even though Bruenig is insured, the hospital billed her nearly $8,000. The responses were mixed: many people understandably found the idea of billing people for bringing new life into being abhorrent, but others were defensive — child-rearing was a choice, their argument went, and having children was bound to cost money, so no one should complain that some companies were profiting from the creation of future generations.

Travelling to the United States several years ago, I spent more than twice as much time searching for insurance than booking flights, accommodation, and planning a sightseeing itinerary combined. My friends sorted their insurance quickly and cheaply but finding a company who would insure me for less than the cost of the return flight was a challenge. Since insurance is essentially gambling with risk, the vast majority of companies were unwilling to take a chance on a traveller with a rare genetic condition that causes multiple tumors to grow in my spinal cord and severe, poorly controlled epilepsy. Finally, I found a reasonable quote, but spent a huge amount of time in fear of seizing in public and being rushed to hospital, racking up an enormous bill.

Mercifully, I was seizure free for a week in New York, but came down with a brutal chest infection, coughing like a medieval peasant with tuberculosis, and raided CVS for anything that might help so as to avoid having to seek medical help. The cough left me unable to sleep for longer than a couple of hours a night and made enemies of the people around me on the flight back. The pain, fever, and shortness of breath made the tail end of my holiday miserable, but the fear of an expensive medical bill affected me far more. On returning to London, I secured an appointment with the National Health Service (NHS) quickly, was diagnosed with pneumonia, and sent home with a free prescription. I didn’t pay a penny for anything.

After a recent seizure left me unconscious for several minutes, I was kept in hospital for a little over a week. I had my own room in a facility directly over the river from the House of Parliament. Doctors performed multiple tests, including full body MRIs, CT scans, tests that tracked the electrical activity of my heart and brain, and staff gave me three meals a day, many cups of coffee, and medication at regular intervals. Free Wi-Fi throughout the hospital meant that when I felt able to, I could work on my laptop and explore the hospital grounds with friends. As we sat in the well-manicured gardens outside one of the hospital cafes, an American friend marveled that the place was “like a mini-city.”

It’s often, correctly, observed that to people in the United Kingdom the National Health Service is akin to a religion. Since its creation after World War II, the mere suggestion, by any party, of a shift away from free health care provokes horror in the electorate. To British people, the US model of health care appears like a hellscape: the easiest way to go viral in the United Kingdom is to post a scan of a US hospital bill and be met with horror by British people from across the political spectrum. Bruenig’s delivery may be at the lower end of that scale, but the outlook of those Americans tweeting about how health care shouldn’t be free is as alien to UK Conservatives as they are to the Left.

The NHS has changed the psychology of an entire nation, across multiple generations: we know that no matter what happens we will receive care and pay little, if anything, for it. Nowadays there are some costs: prescriptions are charged at a flat rate of £9 per person, but a large number of people are exempt — children, pregnant people, pensioners, low earners, and people like me, with certain health conditions that require daily medication, such as epilepsy, diabetes, thyroid issues, and cancer. Shortly after the introduction of the NHS, the government opted to impose charges for spectacles, wigs, and dentures, a highly controversial move that provoked the resignation of health minister Aneurin Bevan, the father of the NHS system. It was an unpopular choice but one that has stuck. (Again, there are certain exemptions similar to those listed above, and my eyesight is so poor, I am given free eye tests, and money off the cost of my lenses.)

Even those in Britain who pay to access private health care, either through work or through their personal wealth, use the NHS: their doctors are trained in the NHS, and specialist care is often available only through the NHS for rare and complex diseases. If you need to visit the emergency room, you’ll be taken to an NHS hospital. People might complain about certain aspects of the NHS, such as waiting times, or personal treatment when they disagree with a doctor, but these are minor gripes, and few would claim that charging people would improve matters. Most problems with the NHS are caused by underfunding at the hands of governments that will happily finance wars while cutting funding for nurses. The United Kingdom spends only about $4,000 per capita on health — the lowest of any G7 country save Italy — compared to more than $10,000 in the United States.

by Dawn Foster, Jacobin |  Read more:
Image: Christopher Furlong / Getty Images
[ed. See also: Does Anyone Really ‘Love’ Their Private Health Insurance? (NY Times).]

The Smug Style in American Liberalism

There is a smug style in American liberalism. It has been growing these past decades. It is a way of conducting politics, predicated on the belief that American life is not divided by moral difference or policy divergence — not really — but by the failure of half the country to know what's good for them.

In 2016, the smug style has found expression in media and in policy, in the attitudes of liberals both visible and private, providing a foundational set of assumptions above which a great number of liberals comport their understanding of the world.

It has led an American ideology hitherto responsible for a great share of the good accomplished over the past century of our political life to a posture of reaction and disrespect: a condescending, defensive sneer toward any person or movement outside of its consensus, dressed up as a monopoly on reason.

The smug style is a psychological reaction to a profound shift in American political demography.

Beginning in the middle of the 20th century, the working class, once the core of the coalition, began abandoning the Democratic Party. In 1948, in the immediate wake of Franklin Roosevelt, 66 percent of manual laborers voted for Democrats, along with 60 percent of farmers. In 1964, it was 55 percent of working-class voters. By 1980, it was 35 percent.

The white working class in particular saw even sharper declines. Despite historic advantages with both poor and middle-class white voters, by 2012 Democrats possessed only a 2-point advantage among poor white voters. Among white voters making between $30,000 and $75,000 per year, the GOP has taken a 17-point lead.

The consequence was a shift in liberalism's intellectual center of gravity. A movement once fleshed out in union halls and little magazines shifted into universities and major press, from the center of the country to its cities and elite enclaves. Minority voters remained, but bereft of the material and social capital required to dominate elite decision-making, they were largely excluded from an agenda driven by the new Democratic core: the educated, the coastal, and the professional.

It is not that these forces captured the party so much as it fell to them. When the laborer left, they remained.

The origins of this shift are overdetermined. Richard Nixon bears a large part of the blame, but so does Bill Clinton. The Southern Strategy, yes, but the destruction of labor unions, too. I have my own sympathies, but I do not propose to adjudicate that question here.

Suffice it to say, by the 1990s the better part of the working class wanted nothing to do with the word liberal. What remained of the American progressive elite was left to puzzle: What happened to our coalition?

Why did they abandon us?

What's the matter with Kansas?

The smug style arose to answer these questions. It provided an answer so simple and so emotionally satisfying that its success was perhaps inevitable: the theory that conservatism, and particularly the kind embraced by those out there in the country, was not a political ideology at all.

The trouble is that stupid hicks don't know what's good for them. They're getting conned by right-wingers and tent revivalists until they believe all the lies that've made them so wrong. They don't know any better. That's why they're voting against their own self-interest.

As anybody who has gone through a particularly nasty breakup knows, disdain cultivated in the aftermath of a divide quickly exceeds the original grievance. You lose somebody. You blame them. Soon, the blame is reason enough to keep them at a distance, the excuse to drive them even further away.

Finding comfort in the notion that their former allies were disdainful, hapless rubes, smug liberals created a culture animated by that contempt. The result is a self-fulfilling prophecy.

Financial incentive compounded this tendency — there is money, after all, in reassuring the bitter. Over 20 years, an industry arose to cater to the smug style. It began in humor, and culminated for a time in The Daily Show, a program that more than any other thing advanced the idea that liberal orthodoxy was a kind of educated savvy and that its opponents were, before anything else, stupid. The smug liberal found relief in ridiculing them.

The internet only made it worse. (...)

Of course, there is a smug style in every political movement: elitism among every ideology believing itself in possession of the solutions to society's ills. But few movements have let the smug tendency so corrupt them, or make so tenuous its case against its enemies.

"Conservatives are always at a bit of a disadvantage in the theater of mass democracy," the conservative editorialist Kevin Williamson wrote in National Review last October, "because people en masse aren't very bright or sophisticated, and they're vulnerable to cheap, hysterical emotional appeals."

The smug style thinks Williamson is wrong, of course, but not in principle. It's only that he's confused about who the hordes of stupid, hysterical people are voting for. The smug style reads Williamson and says, "No! You!"

Elites, real elites, might recognize one another by their superior knowledge. The smug recognize one another by their mutual knowing.

Knowing, for example, that the Founding Fathers were all secular deists. Knowing that you're actually, like, 30 times more likely to shoot yourself than an intruder. Knowing that those fools out in Kansas are voting against their own self-interest and that the trouble is Kansas doesn't know any better. Knowing all the jokes that signal this knowledge.

The studies, about Daily Show viewers and better-sized amygdalae, are knowing. It is the smug style's first premise: a politics defined by a command of the Correct Facts and signaled by an allegiance to the Correct Culture. A politics that is just the politics of smart people in command of Good Facts. A politics that insists it has no ideology at all, only facts. No moral convictions, only charts, the kind that keep them from "imposing their morals" like the bad guys do.

Knowing is the shibboleth into the smug style's culture, a cultural that celebrates hip commitments and valorizes hip taste, that loves nothing more than hate-reading anyone who doesn't get them. A culture that has come to replace politics itself.

The knowing know that police reform, that abortion rights, that labor unions are important, but go no further: What is important, after all, is to signal that you know these things. What is important is to launch links and mockery at those who don't. The Good Facts are enough: Anybody who fails to capitulate to them is part of the Problem, is terminally uncool. No persuasion, only retweets. Eye roll, crying emoji, forward to John Oliver for sick burns.

by Emmett Rensin, Vox | Read more:
Image: Brittany Holloway-Brown

How Long Before The Salmon Are Gone?

How Long Before These Salmon Are Gone? ‘Maybe 20 Years’ (NY Times)

Image: Leon Werdinger, via Alamy

The Deep-Pocket Push to Preserve Surprise Medical Billing

As proposals to ban surprise medical bills move through Congress and state legislatures with rare bipartisan support, physician groups have emerged as the loudest opponents.

Often led by doctors with the veneer of noble concern for patients, physician-staffing firms—third-party companies that employ doctors and assign them out to health care facilities—have opposed efforts to limit the practice known as balance billing. They claim such bans would rob doctors of their leverage in negotiating, drive down their payments and push them out of insurance networks.

Opponents have been waging well-financed campaigns. Slick TV ads and congressional lobbyists seek to stop legislation that had widespread support from voters. Nearly 40% of patients said they were “very worried” about surprise medical bills, which generally arise when an insured individual inadvertently receives care from an out-of-network provider.

But as lobbyists purporting to represent doctors and hospitals fight the proposals, it has become increasingly clear that the force behind the multimillion-dollar crusade is not only medical professionals, but also investors in private equity and venture capital firms.

In the past eight years, in such fields as emergency medicine and anesthesia, investors have bought and now operate many large physician-staffing companies. And key to their highly profitable business strategy is to not participate in insurance networks, allowing them to send surprise bills and charge patients a price they set—with few limitations.

“We’ve started to realize it’s not us versus the hospitals or the doctors, it’s us versus the hedge funds,” said James Gelfand, senior vice president of health policy at ERIC, a group that represents large employers. (...)

To understand the power and size of private equity in the U.S. health care system, one must first understand physician-staffing firms.

Increasingly, hospitals have turned to third-party companies to fill their facilities with doctors. Among driving factors: physician shortages, a bigger insured population because of the Affordable Care Act and an aging population, according to research from the investment firm Harris Williams & Co.

In some areas, doctors have few options but to contract with a staffing service, which hires them out and helps with the billing and other administrative headaches that occupy much of a doctor’s time. Staffing companies often have profit-sharing agreements with hospitals, so some of the money from billing patients is passed back to the hospitals.

The two largest staffing firms, EmCare and TeamHealth, together make up about 30% of the physician-staffing market.

That’s where private equity comes in. A private equity firm buys companies and passes on the profits they squeeze out of them to the firm’s investors. Private equity deals in health care have doubled in the past 10 years. TeamHealth is owned by Blackstone, a private equity firm. Envision and EmCare are owned by KKR, another private equity firm.

With affiliates in every state, these privately owned, profit-driven companies staff emergency rooms, own dialysis facilities and operate physician practices. Research from 2017 shows that when EmCare entered a market, out-of-network billing rates went up between 81 and 90 percentage points. When TeamHealth began working with a hospital, its rates increased by 33 percentage points.

by Rachel Bluth and Emmarie Huetteman, Kaiser Health News via Daily Beast |  Read more:

Image: Shutterstock

[ed. Hedge funds. Again. They're an economic virus. See also: Kaiser healthcare workers plan for nation's largest strike since 1997 (Salon)]

Kabul Relieves Traffic Congestion By Creating Car Bomb Lane

KABUL, Afghanistan — Residents of Kabul are enjoying shorter commute times on the Kandahar–Kabul Highway thanks to the recent completion of a designated car bomb toll lane, sources report.

“For over 18 years motorists had to endure expressways choked with vehicle-borne improvised explosive devices (VBIEDs), resulting in driver frustration, spilled coffee, and premature detonations due to excessive delays,” said Minster of Transportation and Civil Aviation Muhammad Hamid Tahmasi.

“Now,” continued Tahamsi, “with the patent-pending FastBlast® app, drivers can prepay their tolls and rest assured that they will reach their destination on-time and on-target.”

In addition to helping jihadists deliver their payloads in record time, the $2 billion project funded by the US Army Corps of Engineers is a surprising new stream of revenue for both the Afghan government and local businesses in the postwar draw down.

“We are definitely seeing a lot of new foreign investment in the fertilizer and ball bearing industries,” said Minister of Commerce and Industries Anwar ul-Haq Ahady. “Plus, we are providing generous electric car bomb incentives to help aspiring domestic terrorists ‘go green.'”

by Jack S. McQuack, DuffleBlog | Read more:
Image: MichelleWalz CC2.0 license

Overtourism

A rising tide: ‘overtourism’ and the curse of the cruise ships (The Guardian)

Image: Sean Smith

Huang Yongyu, Lotus
via:

The Zollar

The 100 trillion dollar bank note that is nearly worthless (CNN)

Image: uncredited

[ed. The things you learn every day! For example, I knew Zimbabwe suffers from hyper-inflation, but didn't know that it's currency - even in trillion dollar denominations - was still insufficient. So they invented - the Zollar!]

The 100 Best

The 100 best films of the 21st century (The Guardian)

Image: uncredited

[ed. See also: The 100 best albums of the 21st century (The Guardian).]

Ken Burns’s ‘Country Music’ Traces the Genre’s Victories, and Reveals Its Blind Spots

Tell a lie long enough and it begins to smell like the truth. Tell it even longer and it becomes part of history.

Throughout “Country Music,” the new omnibus genre documentary from Ken Burns and Dayton Duncan, there are moments of tension between the stories Nashville likes to tell about itself — some true, some less so — and the way things actually were.

And while from a distance, this doggedly thorough eight-part, 16-hour series — which begins Sunday on PBS — hews to the genre’s party line, viewed up close it reveals the ruptures laid out in plain sight.

Anxiety about race has been a country music constant for decades, right up through this year’s Lil Nas X kerfuffle. In positioning country music as, essentially, the music of the white rural working class, Nashville streamlined — make that steamrollered — the genre’s roots, and the ways it has always been engaged in wide-ranging cultural dialogue.

But right at the beginning of “Country Music” is an acknowledgment that slave songs formed part of early country’s raw material. And then a reminder that the banjo has its roots in West African stringed gourd instruments. The series covers how A.P. Carter, a founder of the Carter Family, traveled with Lesley Riddle, a black man, to find and write down songs throughout Appalachia. And it explores how Hank Williams’s mentor was Rufus Payne, a black blues musician.

It goes on and on, tracing an inconvenient history for a genre that has generally been inhospitable to black performers, regardless of the successes of Charley Pride, Darius Rucker or DeFord Bailey, the first black performer on the Grand Ole Opry. Over and again, “Country Music” lays bare what is too often overlooked: that country music never evolved in isolation.

Each episode of this documentary tackles a different time period, from the first Fiddlin’ John Carson recordings in the 1920s up through the pop ascent of Garth Brooks in the 1990s. Burns has used this multi-episode approach on other American institutions and turning-point historical events: “The Civil War,” “The Vietnam War” and “Jazz.” These are subjects that merit rigor and also patience — hence the films’ length. But country music, especially, demands an approach that blends reverence and skepticism, because so often its story is one in which those in control try to squelch counternarratives while never breaking a warm smile.

“Country Music” rolls its eyes at the tension between the genre imagining itself as an unvarnished platform for America’s rural storytelling and being an extremely marketable racket where people from all parts of the country, from all class levels, do a bit of cosplay.

Minnie Pearl, from “Hee Haw,” came from a wealthy family and lived in a stately home next to the governor’s mansion. Nudie Cohn, the tailor whose vividly embroidered suits became country superstar must-haves in the 1960s and beyond, was born Nuta Kotlyarenko in Kiev, and worked out of a shop in Hollywood. The number of life insurance advertisements sprinkled throughout the photos in the early episodes serve as a reminder of just how contingent the spread of country music was on its sponsors. One salesman recalled determining which homes were tuning in to the Grand Ole Opry on the weekend, and then going to try to sell them insurance on Monday morning.

The only constant in this film is Nashville’s repeated efforts to fend off new ideas like a body rejecting an organ transplant. Merle Haggard, Willie Nelson, Charlie Pride, Hank Williams Jr. — they’re all genre icons who first met resistance because of their desire to make music different from the norm of their day, then ended up establishing new norms.

by Jon Caramanica, NY Times | Read more:
Image: Les Leverett Collections

The Distinctly American Ethos of the Grifter

The Distinctly American Ethos of the Grifter (NY Times)

Image: Stan Douglas, “Two Friends, 1975”

Unknown, Astronomical Photos, 1863
via:

What Happened to Urban Dictionary?

On January 24, 2017, a user by the name of d0ughb0y uploaded a definition to Urban Dictionary, the popular online lexicon that relies on crowdsourced definitions. Under Donald Trump—who, four days prior, was sworn in as the 45th president of the United States, prompting multiple Women's Marches a day later—he wrote: "The man who got more obese women out to walk on his first day in office than Michelle Obama did in eight years." Since being uploaded, it has received 25,716 upvotes and is considered the top definition for Donald Trump. It is followed by descriptions that include: "He doesn't like China because they actually have a great wall"; "A Cheeto… a legit Cheeto"; and "What all hispanics refer to as 'el diablo.'" In total, there are 582 definitions for Donald Trump—some are hilarious, others are so packed with bias you wonder if the president himself actually wrote them, yet none of them are completely accurate.

The site, now in its 20th year, is a digital repository that contains more than 8 million definitions and famously houses all manner of slang and cultural expressions. Founded by Aaron Peckham in 1999—then a computer science major at Cal Poly—Urban Dictionary became notorious for allowing what sanctioned linguistic gatekeepers, such as the Oxford English Dictionary and Merriam-Webster, would not: a plurality of voice. In interviews, Peckham has said the site began as a joke, as a way to mock Dictionary.com, but it eventually ballooned into a thriving corpus.

Today, it averages around 65 million visitors a month, according to data from SimilarWeb, with almost 100 percent of its traffic originating via organic search. You can find definitions for just about anything or anyone: from popular phrases like Hot Girl Summer ("a term used to define girls being unapologetically themselves, having fun, loving yourself, and doing YOU") and In my bag ("the act of being in your own world; focused; being in the zone; on your grind") to musicians like Pete Wentz ("an emo legend. his eyeliner could literally kill a man"); even my name, Jason, has an insane 337 definitions (my favorite one, which I can attest is 1,000 percent true: "the absolute greatest person alive").

In the beginning, Peckham's project was intended as a corrective. He wanted, in part, to help map the vastness of the human lexicon, in all its slippery, subjective glory (a message on the homepage of the site reads: "Urban Dictionary Is Written By You"). Back then, the most exciting, and sometimes most culture-defining, slang was being coined constantly, in real time. What was needed was an official archive for those evolving styles of communication. "A printed dictionary, which is updated rarely," Peckham said in 2014, "tells you what thoughts are OK to have, what words are OK to say." That sort of one-sided authority did not sit well with him. So he developed a version that ascribed to a less exclusionary tone: local and popular slang, or what linguist Gretchen McCulloch might refer to as "public, informal, unselfconscious language" now had a proper home.

In time, however, the site began to espouse the worst of the internet—Urban Dictionary became something much uglier than perhaps what Peckham set out to create. It transformed into a harbor for hate speech. By allowing anyone to post definitions (users can up or down vote their favorite ones) Peckham opened the door for the most insidious among us. Racism, homophobia, xenophobia, and sexism currently serve as the basis for some of the most popular definitions on the site. One of the site's definitions for sexism details it as "a way of life like welfare for black people. now stop bitching and get back to the kitchen." Under Lady Gaga, one top entry describes her as the embodiment of "a very bad joke played on all of us by Tim Burton." For LeBron James, it reads: "To bail out on your team when times get tough." (...)

Early on, the beauty of the site was its deep insistence on showing how slang is socialized based on a range of factors: community, school, work. How we casually convey meaning is a direct reflection of our geography, our networks, our worldviews. At its best, Urban Dictionary crystallized that proficiency. Slang is often understood as a less serious form of literacy, as deficient or lacking. Urban Dictionary said otherwise. It let the cultivators of the most forward-looking expressions of language speak for themselves. It believed in the splendor of slang that was deemed unceremonious and paltry.

In her new book, Because Internet: Understanding the New Rules of Language, McCulloch puts forward a question: "But what kind of net can you use to capture living language?" She tells the story of German dialectologist Georg Wenker, who mailed postal surveys to teachers and asked them to translate sentences. French linguist Jules Gilliéron later innovated on Wenker's method: He sent a trained worker into the field to oversee the surveys. This practice was known as dialect mapping. The hope was to identify the rich, varied characteristics of a given language: be it speech patterns, specific terminology, or the lifespan of shared vocabulary. For a time, field studies went on like this. Similar to Wikipedia and Genius, Urban Dictionary inverted that approach through crowdsourcing: the people came to it.

"In the early years of Urban Dictionary we tried to keep certain words out," Peckham once said. "But it was impossible—authors would re-upload definitions, or upload definitions with alternate spellings. Today, I don't think it's the right thing to try to remove offensive words." (Peckham didn't respond to emails seeking comment for this story.) One regular defense he lobbed at critics was that the site, and its cornucopia of definitions, was not meant to be taken at face value. Its goodness and its nastiness, instead, were a snapshot of a collective outlook. If anything, Peckham said, Urban Dictionary tapped into the pulse of our thinking.

But if the radiant array of terminology uploaded to the site was initially meant to function as a possibility of human speech, it is now mostly a repository of vile language. In its current form, Urban Dictionary is a cauldron of explanatory excess and raw prejudice. "The problem for Peckham's bottom line is that derogatory content—not the organic evolution of language in the internet era—may be the site's primary appeal," Clio Chang wrote in The New Republic in 2017, as the site was taking on its present identity.

by Jason Parham, Wired |  Read more:

Image: Elena Lacey/Getty

Homeless

The word is that John Bolton is not going quietly after President Trump’s ostentatious slam-dunking of him on Twitter. Maybe he won’t. But there’s a part of this equation I doubt we’ll see discussed much in the press coverage of this story. Bolton isn’t really a foreign policy guy and hasn’t been for more than a decade. Yes, he still discusses foreign policy and for the last year or so he had what is basically the top foreign policy job in the U.S. government. But since the end of the Bush years Bolton has really been a public politics guy and a consummate player in the GOP buck-raking industrial complex.

Bolton had a $500,000 a year gig with Fox News. But he also had a slew of PACs and fundraising entities dedicated to sounding the alarm about bad acting regimes and sending money into John Bolton’s pocket. He became one of the GOP’s many professional yakkers and scaremongers who make big dollars raising money off the folks who watch Fox News.

Just for kicks, here’s some of the fundraising emails I pulled up in my inbox, each with links to give money by this or that deadline.

Just one sample of the sort of stuff you’d find in those emails:

But here’s the thing. Donald Trump owns the Republican party. Just ask Justin Amash and Mark Sanford and Bob Corker and a number of others. Trump is the first, second and third rail of Republican politics. You can’t be anti-Trump and be anywhere in the GOP/Fox News funding system, let alone in elected office. If you want to stay in, you have to do what Sen. Ben Sasse did and give Trump full custody of your dignity with maybe the hope of occasional visitation rights.

I have no doubt that Bolton wants to roast Trump alive. Partly it’s just payback for canning and humiliating him. But Bolton must also be horrified by what Trump appears to want to do in Afghanistan, Iran, North Korea and various other places. But if Bolton goes full Trump critic, it’s very hard to see how he’s ever going to make the massive paydays he was before Trump picked him.

Not that that’s the end of the world. I’m sure he’s a wealthy man and he could find other ways to make money. But that’s a Fox News world. And if he goes anti-Trump, that world will be closed to John Bolton. And that big money is going to be really hard to forego.

by Josh Marshall, TPM |  Read more:

Images: TPM
[ed. See also: Trump Finally Fired John Bolton, but Does It Really Matter? (New Yorker).]

Seeing What the Fighting Is All About on Alaska’s Coastal Plain

Seeing What the Fighting Is All About on Alaska’s Coastal Plain (NY Times)

Image: Christopher Miller

Mud Maker: The Man Behind MLB’s Essential Secret Sauce

Jim Bintliff’s collection of lies is small and sharply curated, each one loose enough to be plausible and mundane enough to limit interest in verifying it. They work like this: Bintliff will be out on the banks of a tributary of the Delaware River, in his personal uniform of denim cutoffs and disintegrating sneakers, using a shovel to harvest buckets of mud. Someone will come along and ask what he’s doing. Bintliff sizes up the questioner, usually a boater or swimmer or fisherman, then picks from his collection. I’ve been sent by the Environmental Protection Agency, and I’m surveying the soil. Or: I’m helping the Port Authority, looking into pollution. Or, if it’s a group of young folks who look like they’ve only come out on the water for a good time: I take this mud, and I put it on my pot plants. They grow like trees.

This always does the trick. It prevents anyone from exploring what he’s actually doing, which is what he’s done for decades, what his father did before him, and his grandfather before him: Bintliff is collecting the mud that is used to treat every single regulation major league baseball, roughly 240,000 per season.

Mud is a family business; it has been for more than half a century. For decades, baseball’s official rule book has required that every ball be rubbed before being used in a game. Bintliff’s mud is the only substance allowed. Originally marketed as “magic,” it’s just a little thicker than chocolate pudding—a tiny dab is enough to remove the factory gloss from a new ball without mucking up the seams or getting the cover too filthy. Equipment managers rub it on before every game, allowing pitchers to get a dependable grip. The mud is found only along a short stretch of that tributary of the Delaware, with the precise location kept secret from everyone, including MLB.

The business is small and fundamentally unglamorous. Bintliff harvests the mud himself, using only a shovel and a few buckets, as he has for his entire adult life. The 62-year-old has recently begun bringing a trusted assistant to help him carry the load, but other than that, the process is the same as it has always been. After he collects the mud, he hauls it back to his yard in southern New Jersey, where it sits until he’s ready to pack it up in his garage and ship it out to teams. His wife, Joanne, takes orders and does invoicing. That’s it. There’s no one and nothing else to the operation. It’s increasingly out of place in a hyper-controlled, ultra-competitive, high-tech league, where every detail is calibrated for peak efficiency.

So it shouldn’t be surprising that MLB has recently tried to eliminate Bintliff, teaming with Rawlings to develop a ball that doesn’t need to be enhanced by mud. But baseball is realizing that it isn’t so easy to replace him, and, in fact, it might not be possible at all.

by Emma Baccellieri, Sports Illustrated |  Read more:

Image: LEBRECHTMEDIA

Face Recognition, Bad People and Bad Data

• We worry about face recognition just as we worried about databases - we worry what happens if they contain bad data and we worry what bad people might do with them

• It’s easy to point at China, but there are large grey areas where we don't yet have a clear consensus of what ‘bad’ would actually mean, and how far we worry because this is different rather than just because it’s just new and unfamiliar

• Like much of machine learning, face recognition is quickly becoming a commodity tech that many people can and will use to build all sorts of things. ‘AI Ethics’ boards can go a certain way but can’t be a complete solution, and regulation (which will take many forms) will go further. But Chinese companies have their own ethics boards and are already exporting their products.

Way back in the 1970s and early 1980s, the tech industry created a transformative new technology that gave governments and corporations an unprecedented ability to track, analyse and understand all of us. Relational databases meant that for the first time things that had always been theoretically possible on a small scale became practically possible on a massive scale. People worried about this, a lot, and wrote books about it, a lot.

Specifically, we worried about two kinds of problem:

• We worried that these databases would contain bad data or bad assumptions, and in particular that they might inadvertently and unconsciously encode the existing prejudices and biases of our societies and fix them into machinery. We worried people would screw up.

• And, we worried about people deliberately building and using these systems to do bad things

That is, we worried what would happen if these systems didn’t work and we worried what would happen if they did work.

We’re now having much the same conversation about AI in general (or more properly machine learning) and especially about face recognition, which has only become practical because of machine learning. And, we’re worrying about the same things - we worry what happens if it doesn’t work and we worry what happens if it does work. We’re also, I think, trying to work out how much of this is a new problem, and how much of it we’re worried about, and why we’re worried.

First, ‘when people screw up’.

When good people use bad data

People make mistakes with databases. We’ve probably all heard some variant of the old joke that the tax office has misspelled your name and it’s easier to change your name than to get the mistake fixed. There’s also the not-at-all-a-joke problem that you have the same name as a wanted criminal and the police keep stopping you, or indeed that you have the same name as a suspected terrorist and find yourself on a no-fly list or worse. Meanwhile, this spring a security researcher claimed that he’d registered ‘NULL’ as his custom licence place and now gets hundreds of random misdirected parking tickets.

These kinds of stories capture three distinct issues:

• The system might have bad data (the name is misspelled)…

• Or have a bug or bad assumption in how it processes data (it can’t handle ‘Null’ as a name, or ‘Scunthorpe’ triggers an obscenity filter)

• And, the system is being used by people who don’t have the training, processes, institutional structure or individual empowerment to recognise such a mistake and react appropriately.

Of course, all bureaucratic processes are subject to this set of problems, going back a few thousand years before anyone made the first punch card. Databases gave us a new way to express it on a different scale, and so now does machine learning. But ML brings different kinds of ways to screw up, and these are inherent in how it works.

So: imagine you want a software system that can recognise photos of cats. The old way to do this would be to build logical steps - you’d make something that could detect edges, something that could detect pointed ears, an eye detector, a leg counter and so on… and you’d end up with several hundred steps all bolted together and it would never quite work. Really, this was like trying to make a mechanical horse - perfectly possible in theory, but in practice the complexity was too great. There’s a whole class of computer science problems like this - thing that are easy for us to do but hard or impossible for us to explain how we do. Machine learning changes these from logic problems to statistics problems. Instead of writing down how you recognise a photo of X, you take a hundred thousand examples of X and a hundred thousand examples of not-X and use a statistical engine to generate (‘train’) a model that can tell the difference to a given degree of certainty. Then you give it a photo and it tells you whether it matched X or not-X and by what degree. Instead of telling the computer the rules, the computer works out the rules based on the data and the answers (‘this is X, that is not-X) that you give it. (...)

This works fantastically well for a whole class of problem, including face recognition, but it introduces two areas for error.

First, what exactly is in the training data - in your examples of X and Not-X? Are you sure? What ELSE is in those example sets?

My favourite example of what can go wrong here comes from a project for recognising cancer in photos of skin. The obvious problem is that you might not have an appropriate distribution of samples of skin in different tones. But another problem that can arise is that dermatologists tend to put rulers in the photo of cancer, for scale - so if all the examples of ‘cancer’ have a ruler and all the examples of ‘not-cancer’ do not, that might be a lot more statistically prominent than those small blemishes. You inadvertently built a ruler-recogniser instead of a cancer-recogniser.

The structural thing to understand here is that the system has no understanding of what it’s looking at - it has no concept of skin or cancer or colour or gender or people or even images. It doesn’t know what these things are any more than a washing machine knows what clothes are. It’s just doing a statistical comparison of data sets. So, again - what is your data set? How is it selected? What might be in it that you don’t notice - even if you’re looking? How might different human groups be represented in misleading ways? And what might be in your data that has nothing to do with people and no predictive value, yet affects the result? Are all your ‘healthy’ photos taken under incandescent light and all your ‘unhealthy’ pictures taken under LED light? You might not be able to tell, but the computer will be using that as a signal.

Second, a subtler point - what does ‘match’ mean? The computers and databases that we’re all familiar with generally give ‘yes/no’ answers. Is this licence plate reported stolen? Is this credit card valid? Does it have available balance? Is this flight booking confirmed? How many orders are there for this customer number? But machine learning doesn’t give yes/no answers. It gives ‘maybe’, ‘maybe not’ and ‘probably’ answers. It gives probabilities. So, if your user interface presents a ‘probably’ as a ‘yes’, this can create problems.

You can see both of these issues coming together in a couple of recent publicity stunts: train a face recognition system on mugshots of criminals (and only criminals), and then take a photo of an honest and decent person (normally a politician) and ask if there are any matches, taking care to use a fairly low confidence level, and the system says YES! - and this politician is ‘matched’ against a bank robber.

To a computer scientist, this can look like sabotage - you deliberately use a skewed data set, deliberately set the accuracy too low for the use case and then (mis)represent a probabilistic result as YES WE HAVE A MATCH. You could have run the same exercise with photos of kittens instead of criminals, or indeed photos of cabbages - if you tell the computer ‘find the closest match for this photo of a face amongst these photos of cabbages’, it will say ‘well, this cabbage is the closest.’ You’ve set the system up to fail - like driving a car into a wall and then saying ‘Look! It crashed!’ as though you’ve proved something.

But of course, you have proved something - you’ve proved that cars can be crashed. And these kinds of exercises have value because people hear ‘artificial intelligence’ and think that it’s, well, intelligence - that it’s ‘AI’ and ‘maths’ and a computer and ‘maths can’t be biased’. The maths can’t be biased but the data can be. There’s a lot of value to demonstrating that actually, this technology can be screwed up, just as databases can be screwed up, and they will be. People will build face recognition systems in exactly this way and not understand why they won’t produce reliable results, and then sell those products to small police departments and say ‘it’s AI - it can never be wrong’.

These issues are fundamental to machine learning, and it’s important to repeat that they have nothing specifically to do with data about people. You could build a system that recognises imminent failure in gas turbines and not realise that your sample data has biased it against telemetry from Siemens sensors. Equally, machine learning is hugely powerful - it really can recognise things that computers could never recognise before, with a huge range of extremely valuable uses cases. But, just as we had to understand that databases are very useful but can be ‘wrong’, we also have to understand how this works, both to try to avoid screwing up and to make sure that people understand that the computer could still be wrong. Machine learning is much better at doing certain things than people, just as a dog is much better at finding drugs than people, but we wouldn’t convict someone on a dog’s evidence. And dogs are much more intelligent than any machine learning.

by Benedict Evans |  Read more:

Image: uncredited

Child Support vs. Deadbeat States

In most states in America, child support doesn’t actually go to children. Particularly when they are being raised in low-income families.

Confused? You’re not alone. Many people have no clue how the child support and public assistance systems operate.

The first thing to know: If you are a custodial parent (a majority of whom are mothers) and apply for public assistance (most commonly Temporary Assistance for Needy Families, or TANF), you are required by federal law to file a child support order.

“There is no choice for either parent,” says Jhumpa Bhattacharya, vice president for programs and strategy at the Insight Center for Community Economic Development. “For the custodial parent, you lose your much-needed benefits if you don’t comply. For the noncustodial parent, an order is set sometimes without your knowledge, and often not based on your actual economic situation, or an understanding of how you may be contributing in nonfinancial ways.” “What if you provide child care?” she asks. “Buy diapers or clothing regularly? Those things don’t count.”

In fact, despite the “deadbeat dad” stereotype often pinned on whole categories of nonwhite men by racist politicians, the Centers for Disease Control and Prevention report that black fathers actually spend more time feeding, dressing, playing with and reading to their children — whether they live under the same roof or apart — than fathers of other races.

But there’s more: When applying for public assistance, the custodial parent is required to give up the right to receive the child support payments. They go directly to the state, which, depending on its policies, either keeps it all or passes through a percentage of it. What happens next varies from state to state. Let’s say that the father actually sends the state his child support payment (the Office of Child Support Enforcement in the federal Department of Health and Human Services says only 66 percent of support due in the 2018 fiscal year was collected). In more than half of the states, all of that money essentially disappears, at least as far as poor families are concerned; it’s absorbed into the system, seen as “payback” for the welfare system that is supporting the child.

In other states, a state child support payment, usually around $50 and amounting to a small portion of what a parent paid in, is passed on to the child and his or her family. The rest, again, is absorbed by the state. Only two states — Colorado and Minnesota — pass the full amount of the support through to the custodial parent and child.

Another twist: In some states, that $50 is counted as income, and can push the custodial parent, usually a mother struggling to make ends meet, out of the range of eligibility for TANF entirely. (In other states, the “pass-through” money, as it’s known, is not counted as income.)

To look up your state, see here.

Now what happens if the noncustodial parent can’t pay?

A domino effect of penalties — again, varying from state to state — is set into motion. If the noncustodial parent, usually a father, is employed, his paycheck can be garnished. If he has a driver’s license, it can be taken away. Debt accrues. His credit score plummets. In many states, he is charged interest on the debt; in California, for example, that rate is 10 percent.

For many noncustodial parents, these penalties are economically cataclysmic. Many can’t get to work because of transportation barriers. Others have trouble securing housing because of low credit scores and end up homeless. Some work off the books in hopes of supporting themselves and their children directly, rather than seeing money go to the state. Keep in mind that many are already challenged by the stigma of having a criminal record or having been incarcerated.

The impacts are also emotional. Studies show that when fathers owe child support they have significantly less contact with their children, and when they do interact with them, they are less effective parents. Debt also leads to decreased mental and physical health and worsens family relationships.

“I have seen so many fathers cycle in and out of depression and anxiety as they battle systemic oppression and try to maintain relationships with their kids,” Charles Daniels, a therapist and the founder of a Boston-based nonprofit called Fathers’ UpLift, has written. His organization operated the country’s first mental health and substance abuse treatment facility specifically for absentee fathers and families.

Another cruel reality of the system: Even if the custodial parent manages to get off welfare, the noncustodial parent continues to get bills from the state. In fact, national data indicates that a majority of “payback” payments come from parents whose families no longer receive public assistance.

by Coutney E. Martin, NY Times |  Read more:
Image: Kameleon007/iStock, via Getty Images Plus

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'Suit Wedgie' Robs Anchorage High School Swimmer of a Victory and Sparks Controversy

A young lady from Anchorage, Alaska’s Dimond High School was disqualified at a high school swimming & diving dual meet between Dimond and Chugiak on Friday September 6th for a wardrobe violation while wearing a suit sized to fit snug for racing by the manufacturer and issued to her in accordance with uniform regulations by her team. It is the same suit being worn by each participant yet no other athletes in the program were disqualified. This comes after more than a year of tension regarding the fit of suits worn by athletes at youth swim meets in the state of Alaska. If the suit was issued by her team in accordance with national standards and she was wearing it as directed without prohibited modifications then why was she disqualified?

Above you see the modesty standards that guided the official’s decision on Friday night as well as several examples of popular brand name suits worn by other girls all over the state. Look at the cut of those suits. They’re not in compliance even before they get on the body of a swimmer. Some of these brands are currently being used as team suits. If lots of girls are wearing them, and they’re cut in a way that is “immodest”, why has only one swimmer been disqualified?

This young lady and her sisters are being targeted not for the way they wear their suits but for the way those suits fit their curvier, fuller figured bodies. The issue has come so far unraveled that parents in opposition of these girls and their swimwear have been heard saying that for the sake of their sons, the mother of these young ladies should cover up her daughters. Talk about thrusting modern women back into an era in which men were never held accountable for their behavior! Special legislation has been put forth regarding swimming costumes in this state as well and it is one official’s interpretation of national rules in which they come across as misguided by their spiritual beliefs regarding modesty and morality which have no place on the pool deck at a secular sporting event. While it will polarize Alaska Swimming to an unprecedented degree, it is crucial that this community rise up to protect these girls. They are being targeted not because they are wearing their suits to be scandalous, thus inspiring immorality among other young people, but rather because their ample hips, tiny waists, full chests, and dark complexions look different than their willowy, thin, and mostly pallid teammates. Some will argue this has nothing to do with race, but when the same officials targeting these girls have been heard saying that so-and-so white girl also shows too much skin but has never been disqualified for a similar violation the racial facet of this issue cannot be ignored. (...)

It gets much worse than last night’s injustice for the young lady whose victory was stolen from her when she discovered that a suit her high school team told her she could wear resulted in her disqualification. This same girl was the subject of one rogue team parent’s photography project last season in which they took graphic photos of her backside in her swimsuit without her knowledge or consent and circulated the images via email as evidence that her attire is immoral. She is a minor and that parent should be arrested for possession and distribution of child pornography. Her younger sister, one of the fastest athletes in the history of Alaska swimming, has told her family and friends she feels as though she’s being told by the community that her specific body is not appropriate for competitive swimming. It is the most heartbreaking thing to hear from a young person who is fit and healthy and who is just trying to ensure a brighter future for herself through this sport. We need to fight for these girls so that perverted adults can no longer single them out or judge them. Every organization associated with competitive youth swimming in the state of Alaska and the whole of the United States needs to protect them so they can get their focus back on swimming fast which is all they’ve ever wanted to do.

by Lauren Langford, Medium |  Read more:

Image: uncredited

[ed. I'm in Anchorage, AK this week (former hometown for 40 yrs.), and apparently not much has changed, particularly a strain of conservative meaness/wackiness that afflicts the body politic in general. See also: ‘Suit wedgie’ robs Anchorage high school swimmer of a victory and sparks a controversy (Anchorage Daily News). And in other news, She who won't be named is still a hot topic (TMP v. SLP, Craig Medred).]