Renewal

Spring is my very favorite season. Even more than little green shoots pushing up through the mud, I love the colors and the sun. I love the promise that the grey, dreary skies will eventually clear.

I am, I hope, close to done with my six-year winter. I tell people that I've learned a great deal in grad school, and almost none of it what I thought I'd learn. I've learned to come up with quick answers- one of our postdocs thinks I should be a lawyer!- be assertive in the extreme, cut people off at the knees, rely on only myself for professional support and never expect encouragement. These are not necessarily things I want to know. This is not the person I want to be.

Appropriately enough, the Jewish New Year is always in the fall, with the harvest. I want the next year, once we leave, to be a season of renewal; perhaps a PhD is a harvest of years of suffering. It is supposed to start a new calendar for what one owes, to the Temple in past times and now, in a way, to one's community.

I want my new year to renew my faith in others and in myself. I want to believe that the people around me will do their jobs competently and to receive useful feedback in my job. With my faith in others, I want to tune down the cutthroat impulses, because I surely sharpen them on people who don't deserve it. I want to plant flowers and trees, repaint walls and sand down cupboards, and make a new home for myself and my sweet husband.

After I am done with six years of winter, I want to bring a little light. I want to have enough time away from work to give something back to my new city. I want to teach people about science, and see their faces light up, and know that my work is making the world a better place in some small way. My hope for renewal is that the spring will help me bring my love of science, beaten down by six years of this, back to life, if only as a little sprout.

scientiae-carnival

A Few Random Observations

• My spouse's magic tea (chamomile, honey, lemon, cayenne; sounds revolting; tastes revolting; works anyways) really does do something to colds. (Possibly: decongests them.) Hallelujah.
• My advisor and I have now advanced to the stage where his main response to me is 'Sounds good.' Comforting? Alarming? Yes.
  
• Last week in lab meeting, he suggested something, looked at my faint expression of alarm (gotta work on that poker face some more), and said 'Oh. You don't want to do that. Never mind.'
• What the hell.
  
• Did I mention that Dr. S wrote an RO1 for his temporary-postdoc advisor? He did. The whole. damn. thing.
  
• In return for I got a free five-day trip to San Diego in late March (with Dr. S), and he got a bottle of very nice Scotch.
• Which aren't anywhere near enough to make up for it. But it's a good start.
  
• If this guy's sterling recommendation letter doesn't get Dr. S a faculty job someday, I'll be seriously annoyed.
• Also Dr. S works in a lab entirely made up of Turkish people. They try to feed him all the time because he's so skinny.
  
• Winter? Please go away. Or at least stop RAINING.
• Dear labwork: Kindly stop with the incomprehensible results. Stop. It hurts.

Off to get my hair chopped back into recognizably-human form so I don't look like a dandelion any more.

Soon: Why Plastics Are (Sometimes) Bad, In Three Easy Lessons; and How To Send One's Spouse Off Alone To Buy a House (What Are You So Afraid Of, Dear?); and When America Meets Turkish Culture And Then It Implodes

Also, Foil Hats Don't Keep Out Aliens

I am sure that all of you have heard of the recent measles outbreak in San Diego. Drugmonkey touches on the deep inconvenience of quarantining that many people.

Why do we vaccinate? First, to prevent people getting preventable illnesses. Even in the US, somewhere between one in three hundred and one in a thousand measles cases die. Second, to prevent secondary consequences of infections in the patient. For example, strep throat would, generally, resolve on its own. But there is some chance of developing rheumatic fever which, in previous times, caused significant mortality from its weakening effects on the heart.

But the biggest public-health reason to vaccinate for measles and rubella is neither of these. It's because they cause serious birth defects (rubella, also known as German measles) and frequent preterm labor and spontaneous abortion (measles) in pregnant women. They're not a public health concern because kids get sick. They're a concern because you get dead babies.

I just have no sympathy for people who refuse the evidence in front of them in favor of anecdotes and conspiracy theories. Because:

1. Vaccines do not cause autism, and never have.
2. There is no 'industry conspiracy' around vaccines. -and-
3. Vaccine-preventable diseases are serious. That's... why we bother to vaccinate.
   

I wonder if anyone in San Diego ever thought of their daughter losing her baby because Grandma was afraid of science. I rather doubt it.

Edit: Annoyance makes me hyperbolic. Maybe birth defects aren't the biggest reason. But they're up there.

Twisted

I had something clever to say, but I forgot it. I leave you with this:


Whenever I hear 'crew and good captain well seasoned'

I think of this.

Siiiiiiiiick.

There is nothing quite like wandering about the house at 4 AM feeling faintly queasy and wondering if one must scrap a valuable in-progress brick preparation. Fortunately.

Also I contrived to drop pliers on my head yesterday. (Small ones.) Still: OWW.

Falsifying Data II: Hits, Runs, Errors

Or, More Favorites

3. Someone does an experiment five times. It works once. They report it worked.
Problems: Irreproducible. But many, many perfectly valid results are more or less irreproducible, or can only be done under the same exact circumstances. These are what we call 'non-robust' results. Probably more likely to slip through. I personally think cherry-picking is the worst: the person who does it knows that their result is probably not the real one, and maliciously chooses to hide a valid part of their data set. Somehow it seems nastier to cheat than to lie outright. I suppose because it's more devious than baldfaced. Of course, the fact that I spent six months trying to replicate someone's cherrypicked data has nothing to do with it, oh no...

4. Someone makes a mistake and doesn't catch it in time.

These fall into two camps: Honest (also Kind of Honest, Or We Were Really Sloppy), and Not. Good retraction: Oops, we made a mistake; we're sorry that we misinterpreted our data. Thanks to so-and-so for setting us straight. (Although part of the problem is that high-profile papers take shortcuts, but that's another problem.) Bad retraction: Oops, we got caught.

My lab, on the other hand, just discovered that an artefact caused a 10-fold error in a value we reported. Erratum? No way.

Sigh.

Some of you fine readers maintain that outright fakery is worse. And I agree intellectually. But personally, I must say I find the other kinds much more inconvenient.

I Do Not Think It Means What You Think It Means

Or, Things That Make My Editor's Soul Rejoice

The opposition blames the government and the pro-government Muttonhead Quail Movement (MQM), which runs Karachi, for the violence.

Falsifying Data I: Some of Our Favorite Fakes

L., a former member of Dr. S's lab, published a paper- several years ago- with un-reproduceable data. She confided to my spousal unit, when he tried to repeat the experiment, that she got the result once and ignored the other ten times.

Somehow, faked data came up in conversation. 'Well, L. falsified data,' I said.

'No she didn't!' protested Dr. S. 'She reported a part of it. But she really got the data.'

'She published a result she knew wasn't true,' I said. 'How is that not falsifying data?'

L. now has a faculty job at Snooty U. Virtue rewarded.

***
Our favorite kinds of fake data:

1. Someone makes up a result out of whole cloth, or Photoshop, as it were. Or republishes with a different caption.

These people often get caught. Some bright-eyed person notices that the cells look disturbingly similar, or that the graph appeared in another paper. In some ways, this is morally the worst- after all, there is no ambiguity: DO NOT MAKE UP DATA. Doubtless a fair bit does get through, especially with less high-profile papers. But it is not a subtle lie. This one bothers me less than subtle faking, somehow.

2. Someone makes up part of a result, or fills in a form that was partly blank- on purpose, knowing it's wrong- and so on.

I imagine this gets through a lot more often. It seems to happen frequently in clinical trials, possibly because their data sets are often re-analyzed by more than one group (and so it gets caught in these circumstances). There was that one breast cancer trial (whoops- apparently a lot of breast cancer trials! Money does lead to corruption!)- at Dartmouth maybe? where a lab member discovered the PI had massaged the data interpretation. The PI was fired.

Partial fakery, I find very objectionable. It seems malicious in a way that outright lying doesn't, although the intent is no different: to report a false result. Perhaps it's squidgier because it may have a lower chance of detection: after all, some of the data is real.

Which one do you think is worse, full-on or partial making-it-up? Any juicy stories to tell?

Next: Mistakes, White Lies, and Retractions

Scenes: Failure to Deduce

1) Two of the fluorescent tube lights are not on. The tech goes to the light switches. Flick: on, off. Flick: on, off on the second one. Flick. Flick. Flick. Flick. Flick. Flick. Finally, I say "The. Lights. Are. On. STOP NOW."

2) The tech has a Pipet-Aid thing, which sucks liquid up into pipettes. Pipettes are pre-marked at small intervals. (See below.)

She gets it calibrated.*

*If you are measuring out a cup of water with a... cup measure... this is like getting your kitchen faucet calibrated.