Monthly Archives: December 2010

The Felt & The Unfelt

In the economic sphere an act, a habit, an institution, a law produces not only one effect, but a series of effects. Of these effects, the first alone is immediate; it appears simultaneously with its cause; it is seen. The other effects emerge only subsequently; they are not seen; we are fortunate if we foresee them. (What Is Seen and What Is Not Seen, Bastiat, 1850)

Lately I’ve been pondering various public policy/opinion puzzles:

  • few seem worried that regulation discourages innovation
  • most oppose randomizing policies to learn what policies work
  • white collar crime is neglected relative to blue collar crime
  • cuckoldry seems to most far less bad than even stealth rape
  • long prison terms seem to most less cruel than brief torture
  • folks fear not getting medicine far more than getting too much
  • minimum wages help folks with jobs, neglect those without
  • folks focus on professional licensing raising quality, not price

The pattern I see here is vivid images of direct visceral effects overwhelming less direct and visceral considerations. “Near” tends to displace “far” in policy. This sounds like Bastiat’s famous bias for the “seen” over the “unseen.” But while I agree that this effect contributes, I actually doubt it is the root cause.

You see, most people seem quite capable of understanding many of these indirect effects. Yet even when indirect effects are clearly explained to them, so that they clearly understand, they don’t usually change opinions on such policies.

Now one might invoke social pressure, suggesting people don’t want to look evil or uncaring in the eyes of the many others who don’t understand indirect effects. But while that explanation gets us closer, I think it is still missing a lot.

Consider that econ lab experiment subjects often show “cooperative” or “altruistic” behavior, taking actions that benefit other subjects in the same experiment. Yet this direct help comes at the indirect expense of however else that money would be spent by the researchers. I’d bet that randomly chosen and grouped subjects would mostly continue such altruism, even when clearly informed that money left over at year’s end will be randomly distributed to those who participated in experiments during the year. Even if subjects clearly understand this indirect distribute-the-surplus effect, they’d still neglect it relative to direct effects.

Similarly, when folks meet and say “its been so long, we simply must see each other more often,” they focus on the joy of meeting, and neglect the other less vivid reasons they have not been meeting. Even though they are quite aware that such reasons exist.

In these and many other cases, it seems to me that people have a habit of going out of their way to show that they have strong emotional “near” feelings, via overemphasizing such feelings in their words and actions. People also seem to take comfort in seeing others react with feeling to vivid visible effects, and criticize “cold” unfeeling folks who react less strongly. Together these suggest a simple functional story: we don’t so much emphasize the seen over the unseen, as the feeling over the unfeeling, to signal our vulnerability to such feelings. It seems our ancestors were built to rely heavily on such signals in deciding who to trust. And this show-that-you-feel tendency seems especially strong when, as in politics or charity, we don’t suffer much in the way of other personal consequences.

This theory suggests that merely informing people about indirect effects is far from enough to get more consideration of indirect effects in policy. Creating near-common knowledge about such effects might be sufficient if our fear was looking bad to those ignorant of indirect effects. But if the issue is showing that we feel, this won’t work either. Instead we’ll need to find ways to frame indirect effects so that strong emotional responses seem appropriate, to allow people to signal feelings via considering indirect effects. Easier said than done, I know.

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How Hopeless A PhD?

Imagine that you have some estimate in your mind of the odds of becoming a professor, given that you start a Ph.D. program. Now imagine you see an article titled “The disposable academic: Why doing a PhD is often a waste of time.” How much do you expect that to change your estimate? Yeah, it should lower your estimate a bit.

Now consider actually reading the article. How much on average do you expect your estimate to change then? If your belief changes are rational, you should never expect your estimates to change – they might go up, might go down, but on average stay the same. OK, but do you so expect in this case?

Here is the article; test yourself. Quotes below the fold. Continue reading "How Hopeless A PhD?" »

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Prison Is Cruel

Bankers who take bad risks (provided those risks are legal) simply do not end up with bad outcomes in any absolute sense. … We’re not going to bring back torture, trial by ordeal or debtors’ prisons, nor should we. (Tyler)

During Europe’s Middle Ages, debtors … were locked up … until their families paid their debt. … Some debt prisoners were released to become serfs or indentured servants (debt bondage) until they paid off their debt in labor. … While Hong kong has long imprisoned debtors, the first mainland [China] prison sentence for unpaid debts was handed down in 2008. (more)

Peonage is a system where laborers are bound in servitude until their debts are paid in full. … Such systems have existed in many places at many times throughout history. … Such a system was often used in the southern United States after the American Civil War … Debt bondage has been defined by the United Nations as a form of “modern day slavery” and is prohibited by international law. … The number of debt bondage slaves [worldwide was] 18.1 million at the end of 2006. (more)

When a debtor is tricked or trapped into working for very little or no pay, or when the value of their work is significantly greater than the original sum of money borrowed, some consider the arrangement to be a form of unfree labour or debt slavery. (more)

I like to make my students consider odd policy proposals, ones far from the status quo, but with simple supporting economic arguments. Students usually show a pretty strong status quo “bias” – they are sure our status quo is best, even if don’t know why. So I take notice when most of my students find a non-status quo proposal plausible.

Crimes can be punished via fines, stigma, prison, torture, exile, death, etc. Most of these types of punishment can be scaled, to allow for very small or very large punishments. I asked my students to design a system of punishment – a court sentences each convict to some punishment level, and you decide how to implement that level. Most students suggested some form of debt bondage/prison system – punish convicts via fines, and those who can’t pay must work to pay off the debt. And most of those opted for a competitive system, letting convicts choose to any “prison” willing to pay the fine.

Students noted that fines could depend on convict income/wealth, and that such a system wastes far fewer resources than regular prisons, while keeping convicts confined and letting them learn new skills. And it seems clear to me that no punishment system with a wide enough range of punishment levels is more “cruel” than any other, at least from the convict’s point of view. It is the level of punishment that a convict finds cruel, not the method of implementing it. A prison system is just as cruel as a torture system; it is large punishments, e.g., long prison sentences or severe torture acts, that are cruel, not prison or torture itself.

Commentary on the history of debt bondage is full of accusations of “exploitation” – saying debtor laborers were not fairly credited for their work. No doubt this did happen, but such a problem seems easily solved via competition, making sure a debtor can always to switch to any lender willing to pay their remaining debt. Yet even with such a fix, random walks of wealth in systems allowing debt bondage should accumulate a low tail of folks with the least allowed wealth. And the more wealth is inherited between generations, the thicker that low tail will be.

Clearly the existence of low wealth tails offends many.  (At least within a nation – low wealth elsewhere in the world offends much less.)  And such offense has motivated “anti-slavery” bans of debt bondage. But convicts with long prison sentences are in fact “slaves” with very low wealth levels. Somehow most folks see that as ok, while the same convicts at the same low wealth levels via debt bondage would be, horrors, “slavery,” and not ok.

But if my students are any guide, that conviction is weaker than it might seem. And since debt bondage can make a lot of sense in a future world of near-subsistence whole brain emulations, we may well see a large-scale revival of debt-bondage within a century or so.

Added 9a: Sentences could specify incapacitation or detailed monitoring for some period, with strong penalties for “prisons” that failed.  I’m somewhat skeptical about inevitable political pressures to exploit convicts – that seems a slippery slope argument, and I find such arguments weak.

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Heroes Of Heroes

What do we do when we at last come together [at Christmas]? We watch TV.  To some, this sounds awfully tragic. Shouldn’t we be gathered around the piano instead of the Wii? … All that Christmas idealism is sustained by television. Everything we know about how Christmas should appear and feel, we learned from watching Christmas happen on TV to people who don’t exist. Have a look at the pretty, pretty trees in all those living rooms and in all those diamond necklace ads and in Hallmark specials. What’s the one thing missing from these people’s homes? Correct: No TVs are on. The people we see on television at Christmastime have chosen to put their tree up in a formal living room, safely away from the television. (more)

It may be reasonable to be skeptical of stories, preferring to live a real life with real friends, problems, careers, etc. And it may be reasonable to enjoy stories, to embrace the ideals they embody, and to find life-lessons in their exaggerations. But if you approve of your habit of spending time and energy admiring story heroes and exemplars, then consistency suggests that your heroes and exemplars should also devote their own time and energy to stories, admiring their own heroes. If your heroes don’t waste much time with stories, why should you?

So make up your mind. If you think it good for your family to spend holidays together watching inspirational stories, well then the families in those stories should also think it good to spend holidays together being inspired by other stories.  And if you can’t really admire heroes who much time watching TV, well if your want to admire yourself maybe you shouldn’t spend much time watching TV either.

Here’s a related post by Katja.

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Mapping Academia

Even though individuals display strong correlations between their verbal/writing and quantitive GRE scores, Razib Khan observes that the average GRE scores by intended major show little correlation. Khan also notes:

Philosophers are the smartest humanists, physicists the smartest scientists, economists the smartest social scientists.

I wonder: why do these also happen to be three of my four favorite academic areas (the other being computer science)? Could some areas be better suited to high IQ folks?  If so, am I attracted to those because I think I’m smart? This conflicts with my impression that I like these subjects because they seem objectively more interesting, but that could just be my rationalization.

44 months ago I posted on an interesting “map of science,” and digging deeper today I find that in ’09 the folks who made that map merged twenty different maps of science/academia into this 2D consensus map:

mapofscimapofsciindex

It seems that academic fields naturally form something like a circle, with no fields being especially central. Especially interesting to me, the fields I prefer are all clustered together on one side; my history was to move from E to P to H to CS to an M-style SS.  These topic areas seem to roughly have higher GRE scores, to involve more general and abstract reasoning, and to discuss “far” things further in space, time, social distance, and hypothetically. Apparently academia is divided by near vs. far topics, with math and IQ more important for the far topics, even though math and other formal analysis invokes a near mental mode. The axis orthogonal to near vs far seems to be living vs. dead. Why does academia distribute itself as a circle in this two-dimensional space?

Added 9p: The MapOfScience website, where I got that ’07 graph I liked, now only offers this one:

mapofscicut

If you don’t look carefully you won’t notice that the right and left sides actually connect.  Apparently the idea that social science is closely related computer science offends folks there, just as it seems to offend 3 of the 4 comments here so far. More hating on econ?

Many point out that this SS-CS connection seems one of the weakest links in the consensus ring, but that is in part due to the fact that the databases used to generate these maps usually only include data on “sciences”, from which the humanities and many social sciences are purposely excluded.  There has long been a campaign to marginalize these areas from the main body of academia.

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Fertility Looks Bad

Bryan Caplan complains about evo psych folk who say we didn’t inherit “an overwhelming, conscious desire to have children”, and about my suggestion that “It is hard to tell grand hero stories” about high fertility”:

How secure are the premises that people don’t crave children, and can’t frame parenting as a noble quest?  Even nowadays, these claims seem exaggerated. … An ultra-Darwinian yearning to have vast numbers of descendents – and grand hero stories about this yearning – seem like common memes throughout history. [See] these Biblical quotes: …

Genesis 22:17: That in blessing I will bless thee, and in multiplying I will multiply thy seed as the stars of the heaven.

Yes, people do try to tell parenting hero stories. But this was lots easier among Biblical herders. Herder men who grew their herd well could afford to take many wives, while impressive herder women could attract successful herder men, who could afford to feed many children. Women who grew their herd well could also support more kids. For the folks of Genesis, having more kids was in fact a strong positive signal about your qualities; having many kids looked good.

Not so much today. Imagine you had a child who seemed extremely talented in some area, such as music, writing, analysis, or sport. Imagine that he or she was young, say early twenties, and was considering having her first child. Compared to a kid of ordinary talent, would you encourage them more or less to wait before having a baby?

Now imagine you had a child who seemed of unusually low ability. Loving and caring, with a good stable spouse, they would probably never be much more than the janitor, driver, receptionist, etc. of their current position.  While they would never get much respect on the job, their kids would probably love and respect them. Compared to a kid of ordinary ability, would you encourage them more or less to start a family?

Seems to me that in our modern world, the obvious answer is: more. The more talented your kid is, the more you’d encourage them to put off having kids. Which creates a signaling effect: having kids earlier tells other folks that you see yourself as being less talented. This effect encourages delayed fertility, which tends toward reduced fertility.

Alas, as I’ve suggested before (1 2 3 4), in the modern world trying to making parenting seem heroic runs into a signaling problem that having more kids earlier tends to make you look bad.

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Artists As Foragers

William Easterly in yesterday’s Post:

For so many of my generation, growing up in the 1960s and 1970s, Lennon was a hero, not just for his music but for his fearless activism against the Vietnam War. … The closest counterpart to Lennon now is U2’s Bono, … championing … the battle against global poverty. But there is a fundamental difference between Lennon’s activism and Bono’s. … Lennon was a rebel. Bono is not. Lennon’s protests against the war in Vietnam so threatened the U.S. government that he was hounded by the FBI, police and immigration authorities. … Bono, by contrast, … does not challenge power but rather embraces it; he is more likely to appear in photo ops with international political leaders – or to travel through Africa with a Treasury secretary. … There is something inherently noble about the celebrity dissident, but there is something slightly ridiculous about the celebrity wonk. (more)

If you thought artists had special insight into politics, policy, or their underlying morality, and so sought political info from them, you would not presume to know the info they had to convey in particular cases. You would wait to hear from them if they thought any particular power should be supported or criticized. Instead Easterly here is disappointed that today’s artist celebrities criticize today’s policies, not its powers, because he thinks artists should always criticize power. Artists are so much not info sources to Easterly as allies he wants to rely on to support his anti-power political side. Why?

Artists are iconic foragers, seen as promiscuous, leisurely, non-materialistic, non-domineering, well-traveled, etc. In our great political conflicts between forager and farmer styles, we expect artists to take the forager side. So Easterly complains that the politics of celebrities like Bono doesn’t seem sufficiently forager-like. The great divide continues.

More Easterly quotes: Continue reading "Artists As Foragers" »

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Gambling Save Science?

The latest New Yorker:

All sorts of well-established, multiply confirmed findings have started to look increasingly uncertain. … This phenomenon … is occurring across a wide range of fields, from psychology to ecology. … The most likely explanation for the decline is … regression to the mean. … Biologist Michael Jennions argues that the decline effect is largely a product of publication bias. Biologist Richard Palmer suspects that an equally significant issue is the selective reporting of results. … The disturbing implication … is that a lot of extraordinary scientific data is nothing but noise. (more)

Academics are trustees of one of our greatest resources – the accumulated abstract knowledge of our ancestors. Academics appear to spend most of their time trying to add to that knowledge, and such effort is mostly empirical – seeking new interesting data. Alas, for the purpose of intellectual progress, most of that effort is wasted. And one of the main wastes is academics being too gullible about their and allies’ findings, and too skeptical about rivals’ findings.

Academics can easily coordinate to be skeptical of the findings of non-academics and low-prestige academics. Beyond that, each academic has an incentive to be gullible about his own findings, and his colleagues, journals, institutions, etc. share in that incentive as they gain status by association with him. The main contrary incentive is a fear that others will at some point dislike a findings’ conclusions, methods, or conflicts with other findings.

Academics in an area can often coordinate to declare their conclusions reasonable, methods sound, and conflicts minimal. If they do this, the main anti-guillibility incentives are outsiders’ current or future complaints. And if an academic area is prestigious and unified enough, it can resist and retaliate against complaints from academics in other fields, the way medicine now easily resists complaints from economics. Conflicts with future evidence can be dismissed by saying they did their best using the standards of the time.

It is not clear that these problems hurt academics’ overall reputation, or that academics care much to coordinate to protect it. But if academics wanted to limit the gullibility of academics in other fields, their main tool would be simple clear social norms, like those now encouraging public written archives, randomized trials, controlled experiments, math-expressed theories, and statistically-significant estimates.

Such norms remain insufficient, as great inefficiency remains. How can we do better? The article above concludes by suggesting:

We like to pretend that our experiments define the truth for us. But … when the experiments are done, we still have to choose what to believe.

True, but of little use. The article’s only other suggestion:

Schooler says “Every researcher should have to spell out, in advance, how many subjects they’re going to use, and what exactly they’re testing, and what constitutes a sufficient level of proof.”

Alas this still allows much publication bias, and one just cannot anticipate all reasonable ways to learn from data before it is collected. Arnold Kling suggests:

An imperfect but workable fix would be to standardize on a lower significance level. I think that for most ordinary research, the significance level ought to be set at .001.

I agree this would reduce excess gullibility, though at the expense of increasing excess skepticism. My proposal naturally involves prediction markets:

When possible, a paper whose main contribution is “interesting” empirical estimates should give a description of a much better (i.e., larger later) study that, if funded, would offer more accurate estimates. There should be funding to cover a small (say 0.001) chance of actually doing that better study, and to subsidize a conditional betting markets on its results, open to a large referee community with access to the paper for a min period (say a week).  A paper should not gain prestigious publication mainly on the basis of “interesting” estimates if current market estimates of better estimates do not support those estimates.

Theory papers containing proofs might similarly offer bets on whether errors will be found in them, and might also offer conditional bets on if more interesting and general results could be proven, if sufficient resources were put to the task.

More quotes from that New Yorker article: Continue reading "Gambling Save Science?" »

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Compare Refuge, Resort

Wednesday I gave a brief talk (audio, slides) at the annual meeting of the Society for Risk Analysis. It seems many risk analysts are like futurists in disliking numerical/probability estimates, preferring to qualitatively discuss “scenarios.” They note one can’t think of all possible relevant events, and point to past numerical estimates that now seem way off.

My talk was on a concrete way to get numerical estimates on extreme risks: refuge futures. I’ve given the subject a bit more thought since I talked on it a few years ago; here is my current concept.

Create a set of underground refuges against disaster, some near major transport access points. For example, a $2 Million shelter can hold 36 people with air, water, food, power for 4 years, at less than $14K per person-year. Near each refuge create a matching resort, which supports a comparably utilitarian lifestyle, but does not protect much against disaster. For example, imagine a cheap hotel near an airport, with a refuge dug below it.

Create and sell transferable tickets representing the right of qualified amateurs to stay in those refuges or resorts on particular future dates. Refuges maintain a multi-year supply of food and power, and are staffed by experts who decide when a disaster justifies sealing it. Qualified folks can use their tickets for a date by showing up at the matching resort; they’ll then be escorted to its matching refuge. Those who are in a refuge when it is sealed remain there until its experts decide to unseal it.

The price of a ticket to a particular refuge on a particular date should vary with the estimated chance of a serious disaster near that date and location. But that price should also vary with other factors, such as interest rates, general wealth levels, the local economy, the total supply of related refuge slots, the risk a ticket holder might fail to arrive in time to use a ticket, and the risk that refuge administrators might not honor valid tickets. How can we disentangle these effects?

Regarding variations in interest rates, general wealth, and local growth, such factors could be roughly corrected for via comparing refuge and resort ticket prices. That is, subsidize a market maker who trades of refuge for resort tickets in some ratio. (Ticket fractions could be a random chance of getting a ticket.) The number of resort tickets required to buy a single refuge ticket could be our key disaster indicator.

While an estimate of how disaster risks vary across space and time would be interesting, it would be far more useful to know how disaster risks vary with events, especially relevant decisions. For example, imagine policy-makers were considering a new geo-engineering program. We could then create conditional tickets, such as tickets to a refuge valid on a date only if this new program was begun by some specified prior date. This would allow folks to trade conditional refuge tickets for conditional resort tickets.

The number of conditional resort tickets required to buy a conditional refuge ticket would be a disaster indicator for that condition. If the disaster indicator was lower given the adoption of a geo-engineering policy than given not adopting it, this would suggest that the geo-engineering policy reduces the chance of serious disaster. The possibility of obtaining such valuable policy info would be a major reason to created this whole refuge-resort ticket system.

Regarding the risk of failing to show up to use a refuge ticket, for each slot available we could sell several tickets at different priority levels. If not all first priority tickets holders showed up, the refuge could randomly allocate slots among those who showed up with second priority tickets. If any slots remained, they’d continue with third priority tickets, etc. We could focus on the total price of all refuge priority level tickets for a date, as that should vary less with variations in the chance folks can’t show up to use tickets.

I’m not sure how best to correct for variations in the local supply of refuge or resort slots. I’m also not sure how best to aggregate trades and prices across diverse resort-refuge pairs.

Added 10p: Regarding the risk that refuge administrators might not honor valid tickets, to get useful prices we only need a substantial chance that tickets will be honored. In order to distort our disaster indicator policy advice, ticket speculators need to expect that the chance of valid tickets not being honored is substantially correlated with chosen disaster policy.  What policies could plausibly create such an expected correlation?

Added 12Dec: I should add that as futures markets in concrete physical services, refuge and resort futures and their derivatives would seem to avoid anti-gambling laws.

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Ban Mirror Cells

Imagine a mirror reversed cell, made of mirror-reversed molecules. If it gained energy via photosynthesis, or via special adaptations that enable it to eat ordinary life, the fact that it was immune to ordinary predators and disease would give it a huge advantage; it could take over much of the biosphere. Sounds like a good reason not to make mirror cells right? Unfortunately, there are now big efforts to develop mirror cells, because they’d be a handy biotech tool for pumping out lucrative mirror proteins. Yes this is a real gain, and yes there are ways to try to stop mirror cells from getting loose and destroying the biosphere. But really, the gains here seem easily outweighed by the risks. This is a pretty clear case justifying strong global regulation or bans. Alas, I can find no movement in this direction. Details:

A life-form … based on mirror-image versions of earthly proteins and DNA. … If it worked, those new cells … might also open up new avenues of discovery in materials science, fuel synthesis, and pharmaceutical research. On the down side, though, mirror life wouldn’t have any predators or diseases to limit its reproduction. …

A catastrophe was under way across the Charles River at Genzyme, one of the largest biotech companies in the world. … A virus that disrupts cell reproduction infected one of the bioreactors. The entire plant had to be shut down. … When Church talks about mirror life’s quirky advantages, invulnerability to this kind of mishap is high on his list. “Viruses can’t touch a mirror cell,” … This makes mirror life a potential workhorse for biotech. … Church has been hacking the ribosome. … His plan is to make one that reads regular RNA transcripts of genes but can string together wrong-handed amino acids to form mirror proteins. … Church and his team have cracked the first step. … Last year his team got a synthetic ribosome to self-assemble and produce luciferase, the protein that makes fireflies glow. And he has a library of mutant ribosomes that have the right kind of sockets—they’ll accept mirror amino acids. This is where the money comes in. Some of the most valuable drugs are actually tiny proteins that include wrong-handed amino acids—like the immunosuppressant cyclosporine. To manufacture it, pharmaceutical companies have to rely on an inefficient and expensive fungus. A hacked ribosome modified to handle both normal and mirror amino acids could crank out the stuff on an industrial scale. …

Church thinks even bigger. A manufacturing ribosome would be great, but a fully domesticated mirror cell—able to synthesize more-complicated stuff—would change everything. … vats of virus-proof mirror cells could pump out biofuel, lay down nano-size organic circuitry, and even extrude organic cement foundations for skyscrapers. …

Of course, mirror life could also kill us all. … Just as viruses from our side of the mirror can’t infect it, mirror pathogens can’t infect us. … They might be poisonous, though. … To a mirror cell, … there’s just not enough nutrition for them in the wild. … On the other hand, if mirror cells somehow evolved—or were engineered—to consume normal fats, sugars, and proteins, we might have a problem. … Mirror cells would slowly convert edible matter into more of themselves. … If mirror cells acquired the ability to photosynthesize, we’d be screwed. … All it would take would be a droplet of mirror cyanobacteria squirted into the ocean. Cyanobacteria are at the base of the ocean’s food pyramid, converting sunlight and carbon dioxide into more of themselves … That would wipe out the global ocean ecology. …

“I would be the first to say that we shouldn’t make a photosynthetic mirror cell,” Church says. “But I’m reluctant to have a moratorium on something that doesn’t exist yet.” He says he’d build safeguards into his mirror cells so they’d perish without constant care. And the advances in synthetic biology required to transform those first delicate mirror cells into anything that could survive in the wild are even more remote.

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