This American Life Retracts Daisey Show

This American Life has retracted the Mike Daisey show it did a few months ago because it turns out several details — not trivial ones — were wrong. Daisey knew this, and kept the TAL producers from finding out by concealing the cellphone number of his translator. He told them it no longer worked. TAL producers didn’t ask for her email address, apparently. It is a lot like Gleickgate — Daisey/Gleick  believing it was okay to stretch the truth in pursuit of some greater good (better Foxconn working conditions/less global warming). At least, I would like to think that is why Daisey did it. I hate to think he needed the money.

The position of This American Life is more complicated than their press release reveals. A few years ago Alex Heard revealed that parts of David Sedaris stories were made up. Sedaris is one of TAL’s biggest contributors. He is also their most famous. He probably owes his success to TAL. Did TAL retract his stories? Did it even mention the new information? Uh, no. But TAL remains a great show. These are missteps.

A few weeks ago I complained about Sedaris in a comment on the New Yorker website: Why does The New Yorker publish his stuff as memoir rather than fiction? What exactly is funny about making up derogatory stuff about living people (e.g., Sedaris’s guitar teacher) and spreading the false info far and wide?

 

 

 

 

 

An Example of Predatory Medicine

I recently posted about how doctors act like predators, in the sense of having what Jane Jacobs called “guardian values” (e.g., loyalty to other doctors is more important than honesty to patients). Here is an example of medical behavior that coming from an ordinary business would be shocking:

On February 21 [2012], I had my evaluation for a kidney transplant at a university-affiliated medical center about 100 miles from where I live. The way this institution operates, it takes about 8 months to get from initial referral to evaluation and there are all kinds of diagnostic tests in between (see previous blogs for more details). Once you are an approved transplant candidate and an organ becomes available, you go to the hospital and have surgery. The average stay for a kidney transplant is about 3 days and then you are discharged to a local hotel for 5-7 days. During that time, you return to the hospital every day for blood work, monitoring of the immunosuppressive medications and patient education. Also, you must have a full-time caregiver. That can be a friend, family member, stranger off the street corner, but they must be with you at all times to ensure that you are eating, taking meds, bathing, etc. Also, driving is prohibited until about six weeks post-transplant so the caregiver is also a chauffeur and attends the educational activities as a back-up in case the patient becomes incapacitated or symptoms of rejection appear.

In short, your caregiver must be able to put their own life on hold for about two weeks with as little as two hours notice. When you think about it, that’s a pretty tall order to fill. I have a caregiver, he happens to be a member of this forum. He is a dear, dear friend and always will be if only for the fact that he is willing to undertake this role with only the merest of acquaintance. He is more than willing to put himself and his home at my disposal if necessary. I won’t call him out by name, he obviously knows of whom I speak, but I truly feel as though Karma has smiled on me since our paths have crossed.

So the evaluation finally rolls around. Caregivers must be present during the evaluation. We check in at the medical center and are shown to an exam room. We are seen by a barrage of clinicians; dietician, nephrology resident, nephrology attending (the doctor in overall charge of my medical care while at the transplant unit), and the transplant surgeon. There are physical exams (kind of interesting since my caregiver knows me pretty well, but not THAT well), an EKG and a side trip to the lab. At the lab, the phlebotomist doesn’t pay any attention to my advice about using a butterfly catheter and proceeds to draw 20 (count ’em, 20) vials of blood for type, cross match, antigen levels, etc, etc through a Vaccutainer. About halfway through, my vein collapses and she has to switch to the other arm, this time with a butterfly. After that, a chest x-ray. Back up to the 9th floor for our final meeting of the day; the social worker.

Up until this time, everything had been encouraging. I can’t say enough good things about the clinical staff, they were all wonderful, professional, warm, willing to answer questions, etc. My transplant surgeon looks like he should be on a TV medical drama, he can unzip me any time! The good vibes ended the minute we sat down with the social worker. She informed me that I would be required to have a second caregiver, a backup so to speak. WTH? People that can call a halt to their lives don’t grow on trees. Talk about hitting a brick wall. Here’s a sample of the conversation:

Social worker: What will you do if you are discharged to home and you can’t take care of yourself?
LadyDoc: Well, if I can’t take care of myself then I guess I shouldn’t be discharged, should I?
Social worker: Well, you could always go into a nursing home.
LadyDoc: Over my dead body.

And there you have it, the standoff. I have looked through every single printed word and email that I have ever gotten from this institution (and I keep very good records) and there is NOT A SINGLE WORD about having a second caregiver. The only family I have in the area is my daughter and she has two little boys under the age of five at home, so I can hardly ask her. My circle of friends is painfully small, many are disabled and not up to the challenge and the others have lives of their own.

The social worker called me a few days later to see if I had changed my mind and it suddenly began to sound like a sales pitch. She was touting all the advantages of this particular institution but I just don’t see it. I am now turning my attention to medical centers where the inpatient stay is closer to 5-7 days and then the patient is discharge directly to home, none of this stay-in-a-hotel stuff. I can’t think of too many places where germs and nastiness run more rampant than a hotel. I am so frustrated, I feel as though the last 7 months of my life have been an utter waste of time. Furthermore, the evaluation day was wasted; if we had met with her first we could have simply gotten up and walked out and said “Thank you for playing, please try again”.

In case you needed any convincing that customers for health care differ from customers for other services. (The difference: they are more desperate.) Think of this example if you are sure that government-run health care must be worse than the current system. You can learn what happened next at the link.

Coconut Oil Cures Foot Fungus

About ten years ago my doctor pointed to a thin white line on my foot: That’s fungus, he said. Huh. He prescribed an  antifungal medicine, previously available only by prescription, that had recently become over-the-counter (OTC). I tried several OTC remedies from my drugstore. None worked. According to the directions, they were to be applied twice per day. My doctor said the reason for the failure was that I hadn’t precisely followed the directions. This reminded me of a doctor who said that fat people know what to do about being fat (eat less) and simply fail to do it. Continue reading “Coconut Oil Cures Foot Fungus”

Public Speaking Advice From My Students

In the Frontiers of Psychology class I teach at Tsinghua (Monday 3:20-4:55, Teaching Building 6, Room A113, visitors welcome) , the students will give several presentations each class period. So I decided to assemble a list of advice. I came up with Items 1-3, the students came up with the rest.

  1. Give a presentation that you would like to hear. Don’t worry about following a formula.
  2. Make your points by telling stories. Don’t just say “X is true”. Tell a story that will make your listeners think that X is true.
  3. Stay within the allotted time (e.g., 5 minutes). In real life — presentations at scientific conferences, for example — most presentations are too long. Listeners rarely like this. They think the speaker is selfish. If one person speaks too long, this usually means that other speakers will have less time to speak.
  4. Don’t read your talk.
  5. Use simple, spoken English. Don’t speak fast
  6. Smile and use body language to connect with the audience.
  7. Pause before the most important points.
  8. Ask questions to attract attention.
  9. Show the big structure of your talk.
  10. When telling a story, don’t go far from the point of the story (e.g., with unnecessary details)

To me, the most interesting item is #8 (ask questions). For example, instead of saying “Let us begin” I can say “Shall we begin?” Which is certainly an improvement over coughing, which is what one student said was the usual way officials began talks.

For example, which phrasing works better?

Why does question-asking work? I asked my students.

I asked my students why question-asking works.

The first way (“Why does”) grabs my attention more than the second (“I asked”). I did ask my students why it works. One said that when you hear a question you automatically try to answer it.  I cannot do better than that. I suppose we notice questions much like we notice loud noises.

Percentile Feedback and Productivity

Warning: This post, written for the Quantified Self blog, has more repetition than usual of material in earlier posts.

In January, after talking with Matthew Cornell, I decided to measure my work habits. I typically work for a while (10-100 minutes), take a break (10-100 minutes), resume work, take another break, and so on. The breaks had many functions: lunch, dinner, walk, exercise, nap. I wanted to do experiments related to quasi-reinforcement.

I wrote R programs to record when I worked.  They provided simple feedback, including how much I had worked that day (e.g., “121 minutes worked so far”) and how long the current bout of work had lasted (e.g., “20 minutes of email” — meaning the current bout of work, which was answering email , had so far lasted 20 minutes).

I collected data for two months before I wrote programs to graph the data. The first display I made (example above) showed efficiency (time spent working/time available to work) as a function of time of day. Available time started when I woke up. If I woke up at 5 am, and by 10 am had worked 3 hours, the efficiency at 10 am would be 60%. The display showed the current day as a line and previous days as points. During the day the line got longer and longer.

The blue and red points are from before the display started; the green and black points are from after the display started. The red and black points are the final points of their days — they sum up the days. A week or so after I made the display I added the big number in the upper-right corner (in the example, 65). It gives the percentile of the current efficiency compared to all the efficiency measurements within one hour of the time of day (e.g., if it is 2 p.m., the current efficiency is compared to efficiency measurements between 1 p.m. and 3 p.m. on previous days).

I started looking at the progress display often. To my great surprise, it helped a lot. It made me more efficient. You can see this in the example above because most of the green points (after the display started) are above most of the blue points (before the display). You can also see the improvement in the graph below, which shows the final efficiency of each day.

My efficiency jumped up when the display started.

Why did the display help? I call it percentile feedback because that name sums up a big reason I think it helped. The number in the corner makes the percentile explicit but simply seeing where the end of the line falls relative to the points gives an indication of the percentile. I think the graphical display helped for four reasons:

1. All improvement rewarded, no matter how small or from what level. Whenever I worked, the line went up and the percentile score improved. Many feedback schemes reward only a small range of changes of behavior. For example, suppose the feedback scheme is A+, A, A-, etc. If you go from low B- to high B-, your grade won’t change. A score of 100 was nearly impossible, so there was almost always room for improvement.

2. Overall performance judged. I could compare my percentile score to my score earlier in the day (e.g., 1 pm versus 10 am) but the score itself was a comparison to all previous days, in the sense that a score above 50 meant I was doing better than average. Thus there were two sources of reward: (a) doing better than a few hours ago and (b) doing better than previous days.

3. Attractive. I liked looking at the graphs, partly due to graphic design.

4.  Likeable. You pay more attention to someone you like than someone you don’t like. The displays were curiously likable. They usually praised me, in the sense that the percentile score was usually well above 50. Except early in morning, they were calm, in the sense that they did not change quickly. If the score was 80 and I took a 2-hour break, the score might go down to 70 — still good. And, as I said earlier, every improvement was noticed and rewarded — and every non-improvement was also gently noted. It was as if the display cared.

Now that I’ve seen how helpful and pleasant feedback can be, I miss similar feedback in other areas of life. When I’m walking/running on my treadmill, I want percentile feedback comparing this workout to previous ones. When I’m studying Chinese, I want some sort of gentle comparison to the past.

 

 

 

 

 

Efficiency Measurement Update

Here is another example of the efficiency graphs I’ve blogged about (here, here and here). The line is the current day; it shows how well I’m doing compared to previous days. It goes up when I work, down during breaks. The number in the right corner (“77”) is the percentile of my current efficiency (at the time the graph is made) compared to measurements within one hour (e.g., a measurement at 2 pm is compared to previous measurements between 1 pm and 3 pm).

The blue points come from before I started the feedback; the green points, afterwards. The red and black points are the final points of a day (that is, at quitting time). That the green points are above the blue points suggests that the graphical feedback helped. Here is a better way of seeing the effect of the feedback.

I didn’t expect this, as I’ve said. It is not “the effect of feedback”; before the graphical feedback, I’d gotten non-graphical feedback. It is a comparison of two kinds of feedback.

Why was the new feedback better? Here’s my best guess. It helped a little that it was pretty (compared to text). It helped a lot that it was in percentile form (today’s score compared to previous scores). This meant the score was almost never bad (from the beginning the percentile was was usually more than 50) and yet could always be detectably improved (e.g., from 68 to 70) with a little effort. I wish I could get such continuous percentile feedback in other areas of life – e.g., while treadmill running. I think feedback works poorly when it is discouraging or unpleasant and when it is too hard to improve. When I taught a freshman seminar at Berkeley, I got feedback (designed by a psychology professor) that was so unpleasant I stopped teaching freshman seminars. Because it came only at the end of the term, it was hard to improve — you’d have to teach the class again to get a better score. Moreover, it compared your score to everyone else’s.  I think I was in the lower 50%, which I found really unpleasant. There was no easy way to give feedback about the feedback; maybe it is still in use.

In contrast, I love the feedback shown in the upper graph. Not only does it really help, as the lower graph shows, it leaves me at the end of the day with a feeling of accomplishment.

Why Did Graphical Feedback Improve My Work Habits?

A few days ago I posted about the effect of efficiency graphs — graphs of time spent working/available time vs time of day  (see below for an example). I used these graphs as feedback. They made it easy to see how my current efficiency compared to past days. As soon as I started looking at them (many times/day), my efficiency increased from about 25% to about 40%. I was surprised, you could even say shocked.  Sure, I wanted to be more efficient but I had collected the data to test a quite different idea. In this post I will speculate about why the efficiency graphs helped. Continue reading “Why Did Graphical Feedback Improve My Work Habits?”

The Baltimore Shipyard Study

In a comment on my last post, Sean Estey described a study of Baltimore shipyard workers, some of whom handled radioactive materials. The ones exposed to more radiation were healthier than those exposed to less. The difference in death rate was huge: 25%. This is so large and consistent with other data I doubt it is due to a confounding.

You can read more about this study here and here. If one quarter of all deaths are due to suboptimal stimulation of repair systems, that’s extraordinary news. The study was finished around 1990. The plausibility of such a large benefit should have led to experiments. The observation that people in mountain states (such as Colorado) have less cancer than those in gulf states (such as Alabama) as well as greater radiation exposure suggested to John Cameron, a professor of toxicology, an experiment in which some gulf state residents are exposed to enough radiation to bring their total exposure up to what mountain state residents receive. This has yet to be done.

In a paper about the effects of low-dose radiation, the authors say we should ignore the Baltimore study because of “the healthy worker” effect — the possibility that persons in one exposure group were healthier than those in another exposure group because workers are healthier than non-workers (and fitness for work may have differed between the exposure groups in the Baltimore study). They give three examples to illustrate the healthy worker effect. In these examples, a group in which everyone has a particular job were healthier than the general public, which includes many people without a job. In their examples, the median effect of being in the full-employment group (in which everyone has a job) is a 10% decrease in mortality compared to the general-public group (in which some people don’t have a job because of disability). That should give a good idea of the maximum size of the healthy worker effect — when something is explicitly varied, that’s what happens. The Baltimore study compares person with job to person with job, not person with job to person without job. This suggests that in the Baltimore study, the healthy worker effect was smaller than the effect in the examples, meaning smaller than a 10% reduction. Such an effect cannot explain a 25% reduction.

A comment by Alrenous on my earlier post linked to a 2007 study of people in Taiwan whose apartment building was accidentally contaminated with radioactive materials. By the time of data collection, they had gotten far less cancer (3% of what would have been expected) than the general Taiwan population. A healthy worker effect cannot explain this. Again, the reduction is so great it is unlikely to be due to confounding.

If I could buy something to put under my bed that would expose me to the level of radiation received by people in Colorado, I would.

Beijing Smog: Good or Bad?

I am in Beijing. The smog is bad. It is more humid than usual and the air is dirtier than usual. At his blog, James Fallows, who is also in Beijing, has posted  pictures and pollution measurements. (Incidentally, Eamonn Fingleton, an excellent writer, will be guest-blogging there. In Praise of Hard Industries is one of the best business/economics books I’ve read.)

The effect of smog on health isn’t obvious. Maybe you know about hormesis — the finding that a small dose of a poison, such as radioactivity, is beneficial. It has been observed in hundreds of experiments. It makes sense: the poisons activate repair systems. Even if you know about hormesis, you probably don’t know that one of the first studies of smoking and cancer found that inhaling cigarette smoke appeared beneficial: inhalers had less cancer than non-inhalers. R. A. Fisher, the great statistician, emphasized this (pp. 160-161):

There were fewer inhalers among the cancer patients than among the non-cancer patients. That, I think, is an exceedingly important finding.

This difference (a negative correlation) appeared in spite of two positive correlations: Heavy smokers get more cancer than light smokers; and heavy smokers are more likely to inhale than light smokers. It is far from the only fact suggesting the connection between smoking and health isn’t simple.

So I am not worried about Beijing smog. The real danger, I think, is not eating fermented foods. Which, thankfully, is infinitely more under my control.

Do Fermented Foods Shorten Colds?

Alex Chernavsky writes:

I had an interesting experience recently. On Thursday afternoon, I started feeling a little run-down. Then I began to sneeze a lot, and my nose really started to run. I thought I was coming down with a cold. I took an antihistamine and felt a little better. I woke up Friday morning with a mild sore throat (the sneezing/runny nose had stopped). Within a couple of hours, my throat wasn’t sore anymore — and I haven’t felt sick since then. In summary, I believe I had a cold that lasted less than 24 hours. This almost never happens to me. Typically, my colds last at least a week, and usually more (and I usually get two or three colds per year). There is only one other time in my adult life [he’s in his forties] when I can remember having a very short-duration cold.

Maybe it’s the fermented foods I’m eating. After I started reading your blog, I began to brew my own kombucha, and I drink it every day. I also sometimes eat kim chee, fermented dilly beans, fermented salsa, umeboshi plums, and coconut kefir.

This was the first cold he’s gotten since he started eating lots of fermented foods in June. I believe the correlation reflects causation — the fermented foods improve his immune function. The microbes in the food keep the immune system “awake”. I also believe that Alex’s colds would become even less noticeable if he improved his sleep.

A Chinese Physicist Resigns

A Chinese physicist recently resigned from his job (pure research) at a Beijing research institute. His salary was too low. The base salary is something like $200/month, with something like $1200 for each paper you publish. He explained his decision in a letter to his bosses, which he posted on the Internet. From Google Translate:

Dear leaders:

Hello!

August 2006, I single-handedly carried the mat, one hand holding the quilt to the school to report to work. Slept on the floor in the office 3 nights later, Frank and others XX XXX Street, shares a house, 800 yuan per month. Themselves feel better. However, when my wife came to see me when to Shanghai, but a cry. She did not expect this to write beautiful prose, in English is superb, the monthly salary of ten years ago, men who have three thousand dollars so come down: the room to work without a decent table, there is no place to sit, could only sit bed; office also can take place without her. Yes, until now, my office is a chair, a common HP laser printer or the wife gave me a birthday present. His wife’s insistence, in March 2007, after six months sharing with others, I moved to Village X XX X, X round room (Reference: College on XXXX XXX), monthly rent of 1,600 yuan.

Continue reading “A Chinese Physicist Resigns”

Why Psychologists Don’t Imitate Economists

Justin Wolfers, an economist, via Marginal Revolution:

When I watch and speak with my friends in psychology, very little of their work is about analyzing observational data. It’s about experiments, real experiments, with very interesting interventions. So they have a different method of trying to isolate causation. I am certain that we have an enormous amount to learn from them. But I am curious why we have not been able to convince them of the importance of careful analysis of observational data.

By “careful analysis of observational data” I think Wolfers means the way economists search within observational data for comparisons in which the factor of interest is the only thing that changes (which is why he says “isolate” rather than “infer”). He’s right — it really is a methodological innovation that psychologists are unfamiliar with. It lies between ordinary survey data and experiments.

Here’s why I think this innovation has had (and will have) little effect on psychology:

1. Most psychology professors are bad at math. They still use SPSS! Which is terrible but they think R is too difficult. Economics papers are full of math. That is part of the problem. Math difficulty also means they have trouble with basic statistical ideas. When analyzing data, they’re afraid they’ll do the wrong thing. For example, most psychology professors don’t transform their data. It wasn’t in some crummy textbook so they are afraid of it. Lack of confidence about math makes them resistant to new methods of analysis. Experimental data is much easier to analyze than observational data. You don’t need to be good at math to do a good job. So they not only cling to SPSS, they cling to experimental data.

2. Psychology studies smaller entities than economics. Study of the parts often influences study of the whole; the influence rarely goes the other way. This is why, when it comes to theory, physics will always have a much bigger effect on chemistry than vice-versa, chemistry a much bigger effect on biology than vice-versa. Method is different than theory but if you aren’t reading the papers — and physicists don’t read a lot of chemistry — you won’t pick up the methods.

3. There is a long history of longitudinal research in psychology. Studying one or more groups of children year after year into adulthood. The Terman Genius project is the most famous example. I find these studies unimpressive. They haven’t found anything I would teach in an introductory psychology class. I think most psychologists would agree. This makes observational data less attractive by association.

4. Like everyone else, psychologists have been brainwashed with “correlation does not equal causation”. I have heard many psychology professors repeat this; I have never heard one say how misleading it is. To the extent they believe it, it pushes them away from observational data.

5. Psychologists rarely use observational data at all. To get them to appreciate sophisticated analysis of observational data is like getting someone who has never drunk any wine to appreciate the difference between a $20 wine and a $40 wine.

Shamelessness in Chinese Academia

Professor Wang Hiu, a Tsinghua faculty member in the Chinese Language Department, was accused of plagiarism several months ago. You can read about it here. Professor Wang is no stranger to controversy:

Wang Hui was involved in controversy following the results of the Cheung Kong Dushu Prize in 2000. The prize was set up by Sir Li Ka-shing, which awards one million RMB in total to be shared by the winners. The 3 recipients of the prize in 2000 were Wang Hui, who served as the coordinator of the academic selection committee of the prize, Fei Xiaotong, the Honorary Chairman of the committee, and Qian Liqun, another committee member. Wang Hui was then the editor-in-chief of Dushu magazine, which was the administrative body of the prize.

He awarded the prize to himself! And his fellow committee members. Wang was editor in chief of Dushu for ten years. During that time, he published many hard-to-understand articles by his friends. The influence of the magazine shrank considerably.

Eczema, Nighttime Cough, Antibiotics, and Fermented Food (more)

This comment was made recently on an earlier post:

I am so glad I found this blog.

My daughter has had coughing fits for 24 months (she’s 5 1/2 yo).

Inhalers, several doctors, nothing helped. She routinely coughed until vomiting. After one 10 hour coughing fit I reached my limit and scoured the web.

After putting in her whole medical history as search qualifiers I found this [post]. The prior eczema and antibiotics were key indicators.

After 3 days of drinking 1 probiotic shake a day, she showed very marked improvement. After 1 week, no symptoms. This is a girl who’s been unable to run and play for 2 years. Who woke up coughing and gagging most nights.

After 6 weeks of the same regimen, she still shows no symptoms and is running and playing full blast.

The pulmonary specialist discounts the results we’ve seen as a fluke . . . we’ll see. Previously my daughter’s lung capacity was measured at 47% of expected.

“Unable to run and play for 2 years”! I’m impressed. Not only (a) the improvement is huge, but also (b) it resembles verification of a prediction, not just something a theory can explain, (c) it wasn’t obvious to “several doctors” or (d) the rest of the Internet, and (e) after it happened it was dismissed by an expert, even though the evidence for causality is excellent. The verification aspect reminds me of Pale Fire:

If on some nameless island Captain Schmidt
Sees a new animal and captures it,
And if, a little later, Captain Smith
Brings back a skin, that island is no myth.

Assorted Links

Thanks to Vic Sarjoo, Anne Weiss, and Marian Lizzi.

The Twilight of Expertise (by-the-book professors)

Imagine if, to get the news, you had to go somewhere and have it read to you! What a joke. From an article in the Washington Monthly about on-line education:

If Solvig needed any further proof that her online education was the real deal, she found it when her daughter came home from a local community college one day, complaining about her math course. When Solvig looked at the course materials, she realized that her daughter was using exactly the same learning modules that she was using at StraighterLine . . . The only difference was that her daughter was paying a lot more for them, and could only take them on the college’s schedule. And while she had a professor, he wasn’t doing much teaching. “He just stands there,” Solvig’s daughter said.

The excellent article misses something big, however:

A lot of silly, too-expensive things “vainglorious building projects, money-sucking sports programs, tenured professors who contribute little in the way of teaching or research” will fade from memory, and won’t be missed.

Via Aretae.

The Limits of Expert Trial and Error

Of course I loved this comment on a recent post of mine about how to flavor stuff:

I made a vegetable soup today spiced by small amounts of vegetable stock, hoi sin sauce, angostura bitters, lea & perrins worcestershire sauce, Kikkomann soy sauce, maggi wrze, marmite, maille mustard. I can honestly say it was the best tasting soup I, or any of my guests, can remember having been served.

I routinely make soups that taste clearly better than any of the thousands of soups I had before I figured out the secret. There is no failure (I’ve done it 20-odd times), no worry about over- or under-cooking. Something else odd: There seems to be a ceiling effect. The texture could be better, the appearance could be much better, the creaminess could be better, sometimes the temperature could be better, the sourness could be better, but I can’t imagine it could be more delicious.
Why wasn’t this figured out earlier? I’ve looked at hundreds of cookbooks and thousands of recipes. I haven’t seen one that combines three or more sources of great complexity, as I do and the commenter did. There may be more trial and error surrounding cooking than anything else in human life. Billions of meals, day after day.

I think it goes back to my old comment (derived from Jane Jacobs) that farmers didn’t invent tractors. Some people claimed they did but I think we can all agree farmers didn’t invent the engine on which tractors are based. You can’t get to tractors from trial and error around pre-tractor farming methods. Even though farmers are expert at farming. I think that’s what happened here. I am not a food professional or even a skilled cook. My expertise is in psychology (especially psychology and food). Wondering why we like umami, sour, and complex flavors led me to a theory (the umami hypothesis) that led me to a new idea about how to cook.

And this goes back to what many people, including Atul Gawande, fail to understand about how to improve our healthcare system. The supposed experts, with their vast credentials, can’t fix it — just as farmers couldn’t invent tractors. Impossible. The experts (doctors, medical school professors, drug companies, alternative healers) have a serious case of gatekeeper syndrome. The really big improvements will come from outsiders. Outsiders who benefit from change. To fix our healthcare system, empower them.

Michael Perelman on the Purpose of College

In a talk, Michael Perelman, a professor of economics at CSU Chico, said this:

Each semester, I tell my class that each of them has the potential to be the best in the world at something. The most important thing they can do in school [= college] is find out what that something is.

That is a sane view of college. At Berkeley, I told undergrads: “Take as few classes as possible and do as many internships as possible.”

Perelman’s talk, an intellectual autobiography, has all sorts of interesting details, such as “As the economy faltered, economists would express doubts about how the economy functioned but once the economy recovered, challenges to market fundamentalism would become rare.”