I can’t believe I have never blogged this issue.

http://twitter.com/zenbrainest/status/680128624490459137

Obeying the alleged word or character limits for initial submission is for suckers. It puts you at a disadvantage if you shrink down your methods or figure count and the other group isn’t doing that.

I am still not entirely sure this is not an elaborate joke.

http://grants.nih.gov/grants/guide/rfa-files/RFA-CA-16-005.html

The purpose of the NCI Predoctoral to Postdoctoral Fellow Transition Award (F99/K00) is to encourage and retain outstanding graduate students who have demonstrated potential and interest in pursuing careers as independent cancer researchers. The award will facilitate the transition of talented graduate students into successful cancer research postdoctoral appointments, and provide opportunities for career development activities relevant to their long-term career goals of becoming independent cancer researchers.

The need for a transition mechanism that graduate students can apply for is really unclear to me.

Note: These are open to non-citizens on the appropriate visa. This is unlike the NRSA pre- and post-doc fellowships.

The BJP has decided to require that manuscripts submitted for publication adhere to certain experimental design standards. The formulation can be found in Curtis et al., 2015.

Curtis MJ, Bond RA, Spina D, Ahluwalia A, Alexander SP, Giembycz MA, Gilchrist A, Hoyer D, Insel PA, Izzo AA, Lawrence AJ, MacEwan DJ, Moon LD, Wonnacott S, Weston AH, McGrath JC. Experimental design and analysis and their reporting: new guidance for publication in BJP. Br J Pharmacol. 2015 Jul;172(14):3461-71. doi: 10.1111/bph.12856 [PubMed]

Some of this continues the “huh?” response of this behavioral pharmacologist who publishes in a fair number of similar journals. In other words, YHN is astonished this stuff is not just a default part of the editorial decision making at BJP in the first place. The items that jump out at me include the following (paraphrased):

2. You should shoot for a group size of N=5 or above and if you have fewer you need to do some explaining.
3. Groups less than 20 should be of equal size and if there is variation from equal sample sizes this needs to be explained. Particularly for exclusions or unintended loss of subjects.
4. Subjects should be randomized to groups and treatment order should be randomized.
6.-8. Normalization and transformation should be well justified and follow acceptable practices (e.g., you can’t compare a treatment group to the normalization control that now has no variance because of this process).
9. Don’t confuse analytical replicates with experimental replicates in conducting analysis.

Again, these are the “no duh!” issues in my world. Sticky peer review issues quite often revolve around people trying to get away with violating one or other of these things. At the very least reviewers want justification in the paper, which is a constant theme in these BJP principles.

The first item is a pain in the butt but not much more than make-work.

1. Experimental design should be subjected to ‘a priori power analysis’….latter requires an a priori sample size calculation that should be included in Methods and should include alpha, power and effect size.

Of course, the trouble with power analysis is that it depends intimately on the source of your estimates for effect size- generally pilot or prior experiments. But you can select basically whatever you want as your assumption of effect size to demonstrate a range of sample sizes as acceptable. Also, you can select whatever level of power you like, within reasonable bounds along the continuum from “Good” to “Overwhelming”. I don’t think there are very clear and consistent guidelines here.

The fifth one is also going to be tricky, in my view.

Assignment of subjects/preparations to groups, data recording and data analysis should be blinded to the operator and analyst unless a valid scientific justification is provided for not doing so. If it is impossible to blind the operator, for technical reasons, the data analysis can and should be blinded.

I just don’t see how this is practical with a limited number of people running experiments in a laboratory. There are places this is acutely important- such as when human judgement/scoring measures are the essential data. Sure. And we could all stand to do with a reminder to blind a little more and a little more completely. But this has disaster written all over it. Some peers doing essentially the same assay are going to disagree over what is necessary and “impossible” and what is valid scientific justification.

The next one is a big win for YHN. I endorse this. I find the practice of reporting any p value other than your lowest threshold to be intellectually dishonest*.


10. When comparing groups, a level of probability (P) deemed to constitute the threshold for statistical significance should be defined in Methods, and not varied later in Results (by presentation of multiple levels of significance). Thus, ordinarily P < 0.05 should be used throughout a paper to denote statistically significant differences between groups.

I’m going to be very interested to see how the community of BJP accepts* this.

Finally, a curiosity.

11. After analysis of variance post hoc tests may be run only if F achieves the necessary level of statistical significance (i.e. P < 0.05) and there is no significant variance in homogeneity.

People run post-hocs after a failure to find a significant main effect on the ANOVA? Seriously? Or are we talking about whether one should run all possible comparison post-hocs in the absence of an interaction? (seriously, when is the last time you saw a marginal-mean post-hoc used?) And isn’t this just going to herald the return of the pre-planned comparison strategy**?

Anyway I guess I’m saying Kudos to BJP for putting down their marker on these design and reporting issues. Sure I thought many of these were already the necessary standards. But clearly there are a lot of people skirting around many of these in publications, specifically in BJP***. This new requirement will stiffen the spine of reviewers and editors alike.

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*N.b. I gave up my personal jihad on this many years ago after getting exactly zero traction in my scientific community. I.e., I had constant fights with reviewers over why my p values were all “suspiciously” p<0.5 and no backup from editors when I tried to slip this concept into reviews.

**I think this is possibly a good thing.

***A little birdy who should know claimed that at least one AE resigned or was booted because they were not down with all of these new requirements.

Vaping: Known Unknowns

December 21, 2015

Unless you have been hiding under a rock, you know about e-cigarettes. These are devices which deliver a nicotine dose using a battery-heated element which vaporizes propylene glycol, polyethylene glycol, vegetable glycerin (mostly) and/or some other vehicles in which the nicotine has been dissolved.

These devices appeal to users as cessation aids to help quit smoking tobacco and as a safer alternative to cigarettes.

They also appeal to adolescents, apparently.

You will hear the occasional grand pronouncement hit the media circusit with more assertions than questions leaving people wondering.

Here is my general take on just about anything having to do with e-cigarettes: We don’t really know and we need to do some more science to figure it out.

So here are the key questions all amenable to research, some of which is no doubt ongoing.

Do e-cigs help people quit smoking? The question is, in my view, do they do any better than cold turkey (accounting for subpopulations) and are they as effective or better than any other replacement therapy like the gum or patch.

Do e-cigs prolong nicotine use in individuals who would otherwise have quit smoking cigarettes? Very tricky question, this one. But if you have an individual who would have quit smoking but keeps using nicotine via e-cig, you’ve increased harm.

Do e-cigs cause novel harms? In other words, presumably the nicotine harm is the same (once individuals learn how to get their desired nicotine dose from these). But are there constituents of the vehicles, the flavorants or products created by the vaporization process that cause health risks? And no, just showing an ingredient is present is not evidence of harm. We need careful toxicology studies with relevant exposure doses and regimens.

Do e-cigs prevent well-established harms? The chronic smoking of tobacco, typically via the modern cigarette products, has very well established and very bad health consequences. Nicotine exposure is the cause of only a subset of the harms, even if it is the thing responsible for continued use. So getting combusted tobacco smoke exposure out of the situation cannot help but be a huge win. Huge. I don’t see how this can really be argued until and unless we find some whopping big harms of the vapor exposure.

Do e-cigs addict new individuals to nicotine? One of the big fears of those concerned with e-cigs is that early data show that adolescents are more likely to try e-cigs than to try smoking cigarettes. There will be some work showing that daily nicotine users started off with e-cigs rather than tobacco cigarettes but as you know, it is impossible to establish causality with real human populations. The best we have, overwhelmingly likely causal relationships, has to wait on a whole lot of data. Which we won’t have for many years.

Bonus Round:
Are e-cigs used without nicotine or other psychoactive? One parent I know has asserted that perhaps some adolescents are using e-cig devices with just the flavored vehicles and not to ingest nicotine or any other drug. Obviously this goes back to the above question about harms from the vehicle. But it also links to another concern…

Are e-cigs used to deliver other psychoactive drugs? The devices are very readily and broadly available. They are being used with crude marijuana extracts for certain sure. There have been media allegations that they are being used to ingest “flakka” (here, here, here). For a time, one assumes that by pretending to be smoking nicotine or the flavorant (see above) peope will be able to stroll about ingesting illegal substances in public view. Including adolescents, my friends. Yes, kids.

Jan: Here’s to wishing all of my Readers a fantastic 2015. May your grants be funded, your papers accepted and your promotions obtained.

Feb: Some people try to get into a mental frame for grant writing with disruptions of their normal workaday routine.

Mar: There is one thing that concerns me about the Journal of Neuroscience banning three authors from future submission in the wake of a paper retraction.

Apr: challdreams wrote on rejection.

 These things may or may not be part of your personal life, where rejection rears its head at times and you are left to deal with the fall out.

May: Neuroscientist Nikos Logothetis (PubMed) has informed his colleagues that he is stopping his long running nonhuman primate research program.

Jun: First of all, if you don’t understand that anything featuring groups of humans is in the broader sense “political” than you are a fool.

Jul: I still get irritated every time a PO gives me some grant advice or guidance that is discordant with my best understanding of the process.

Aug: Sometimes, I page back through my Web of Science list of pubs to the minimal citations range.

Sep: How many staff members (mix of techs, undergrads, graduate students, postdocs, staff sci, PI) constitute a “medium sized laboratory” in your opinion?

Oct: Are you familiar with any Universities that award some sort of official recognition of the completion of a postdoctoral term of scientific training?

NovPAR-16-025 invites applications for the R50 Research Specialist award.

Dec: It emerged on the Twitts today that sometimes postdocs can defer student loans and sometimes they cannot.

Jocelyn Kaiser reported in Science Insider:

the National Institutes of Health (NIH) today announced it will no longer support setting aside a fixed 10% of its budget—or $3 billion this year—to fund research on the disease. The agency also plans to reprogram $65 million of its AIDS research grant funding this year to focus more sharply on ending the epidemic.

Whoa. Big news. This is an old Congressional mandate so presumably it needs Congress to be on board. More from Kaiser:

The changes follow growing pressure in Congress and from some advocacy groups for NIH to reallocate its funding based on the public health burden a disease causes…. some patient groups and members of Congress have recently asked why AIDS receives disproportionately far more than diseases with higher death rates, such as heart disease and Alzheimer’s….Last year, Congress omitted instructions asking NIH to maintain the 10% AIDS set aside.

Emphasis added. An act by omission is good enough for gov’mint work, eh? Congress is on board.

@jocelynkaiser was kind enough to link to relevant NIH budgetary distributions:

As you can see, NIDA devotes about $300M to HIV/AIDS research. The annual NIDA budget allocation is about $1B so you can see that something on the order of 30% of the NIDA budget is (and has been) devoted to this Congressional Mandate.

Wait, whut? What about that 10% mandate above? Yep, the HIV/AIDS money has not been evenly distributed across the ICs.

Now, I don’t know exactly when and how all of this shook down. It was FY 1987 when the NIAID budget went up by something like 47% when other similarly sized ICs didn’t see such a large percentile increase. Clearly 1986 was when Congress got serious about HIV/AIDS research. We can’t assess the meaning of

AIDS has received 10% of NIH’s overall budget since the early 1990s, when Congress and NIH informally agreed it should grow in step with NIH’s overall budget.

NIH must treat AIDS dollars as a distinct pot of money within its overall budget. That is because a 1993 law carved out a separate HIV/AIDS budget, Collins says. And undoing that law would take action by Congress.

from this article. It is a little frustrating, to be frank. But…on to the NIDA situation.

NIDA doesn’t appear in the NIH tables until FY1993 because it didn’t actually join the NIH until 1992. Nevertheless that history page on NIDA notes:

1986: The dual epidemics of drug abuse and HIV/AIDS are recognized by Congress and the Administration, resulting in a quadrupling of NIDA funding for research on both major diseases.

There are many ways of looking at this situation.

Some in the NIDA world who are not all that interested in HIV/AIDS matters complain bitterly about why “A third of our budget is reserved for HIV/AIDS“. Our.

Another way of looking at this would be “If Congress mandated NIH devote 10% of its budget to HIV/AIDS but NIH did this by incorporating NIDA with its existing HIV/AIDS funding then the entire rest of NIH is shirking its response to the mandate on the back of NIDA”.

And yet a final way of looking at this* would be “Dude, NIDA wouldn’t even have this money if not for Congress’ interest in funding HIV/AIDS research so it isn’t ‘our‘ funding being diverted to HIV/AIDS research.”

Is this important? Yes and no.

The news is potentially huge for those who seek to get the HIV/AIDS funding via NIDA grants and for those who seek non-HIV/AIDS funding. It makes matters slightly better for the latter and worse for the former. Right? If there is no special set-aside, the latter folks now have at least a shot at that $300M that had been out of reach for them. This consequently increases the competition for those who have HIV/AIDS relevant proposals. Who are presumably sad right now.

But it all depends on what Collins plans to do with his newly won freedom. Back to Kaiser:

Francis Collins agrees: At a meeting of his Advisory Committee to the Director (ACD) today, he noted that no other disease receives a set proportion of the NIH budget and the argument that AIDS still deserves such a set-aside is “not a defensible one.”

The end of the set-aside has “free[d] us up” to refocus NIH’s AIDs portfolio, Collins says.

However the article only then talks about $65M being reprioritized. What about the rest of the 10% of the ~$30B / yr NIH budget? No idea.

So I want to know a few things. Is the $300M in the NIDA budget that goes to HIV/AIDS part of this 10% overall NIH mandate? If so, will Collins try to claw that back for some other agenda?

If a miracle occurs and it stays within NIDA, will Nora Volkow use this new-found freedom to ease the pressure on the non-HIV/AIDS researchers by letting them (ok, “us”) get a shot at that previously-sequestered pool?

Or will Volkow use it to pay for the latest boondoggle initiatives of ABCD and BRAINI?

The way I hear it, this latter is likely to happen because up to this point all other NIDA initiatives are being squeezed** to make ABCD and BRAINI happen.

Obviously I would prefer to see Volkow choose to use this new freedom a little more democratically by spreading the love across all of the portfolio.

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*this has been my view for some time now.

**this manifests, IME, as profound pessimism on the part of POs that anything in the grey zone (which is robust reality at no-public-payline-NIDA) will be picked up because all spare change is going to the two aforementioned boondoggles.

Light matters

December 11, 2015

A recent exchange on the Twitter reminded me of an old paper from 1968.

The paper in question is

Scheving LE, Vedral DF, Pauly JE. Daily circadian rhythm in rats to D-amphetamine sulphate: effect of blinding and continuous illumination on the rhythm. Nature. 1968 Aug 10;219(5154):621-2. [PubMed]

Scheving68F1The key takeaway message for me is captured in the first figure (click to embiggen), which represents the percentage of rats that died within 24 h of being injected with either 26 mg/kg (darker line) or 30 mg/kg (dotted line) of amphetamine. The X axis depicts the time of day at which the groups were injected and the bar that forms the X axis indicates when the lights were on (6 am to 6 pm) and off.

As you are aware, rats are a nocturnal species and the wiggle trace just above the X-axis confirms this with activity patterns based on noise recording of the colony.

So, back to the point. The only difference across points within a single amphetamine dose is the time of day at which the drug was administered. Mortality rates change from 20% to nearly 80% with the lowest observed during the inactive part of the rats’ day.

Light cycle and circadian phase matter. A lot.

This brings me to a second example, which is from one of the papers in a series of investigations by Dave Roberts at Wake Forest. In

Roberts DC1, Brebner K, Vincler M, Lynch WJ. Patterns of cocaine self-administration in rats produced by various access conditions under a discrete trials procedure. Drug Alcohol Depend. 2002 Aug 1;67(3):291-9. [PubMed]

the authors use a procedure in which rats are allowed to self-administer cocaine 24 h per day. The one major difference from the usual 1-2 h per day type of model is that the number of opportunities for cocaine were limited. These “discrete trial” opportunities ranged from 2-5 per hour and each time the animal was permitted 10 min to make a response once the lever was extended. Each response terminated the discrete trial so animals could only take 2-5 infusion per hour.

Roberts02-coc-circadianThe figure that continues the point most effectively is from a set of manipulations in which the discrete trial was set to 3 per hour and the per-infusion dose was varied. The data represent the total cocaine intake per hour so look at the 1.0 and 2.0 mg/kg/infusion doses if you want to figure out how many responses out of the 3 opportunities per hour were being made.

The point is again obvious, namely that circadian factors and light cycle matter a lot to the outcome. Imagine the more typical 1 h or 2 h operant self-administration session for cocaine being placed at various points across the rat’s light cycle. On average, you might expect different mean intakes.

This is going to contribute to replication and reliability issues, particularly if you expect a given mean amount of drug intake.

It gets even tricker if you want to start exploring the effect of different interventions on cocaine self-administration. Who knows if they themselves have circadian-dependent effects or if the interaction with cocaine taking does? Who knows which direction it takes? We don’t know until someone does the study.

And we can all see how much exacting work with light cycles there will be to satisfy ourselves that we know what the influence is. Work that, should it turn out negative, will be nigh on unpublishable.

And to be clear, there are hard practicalities of research that make us ignore these factors at times. Mostly across studies, but sometimes within them. Take the big issue of running behavior in the light or dark cycle of a rat (or mouse). This depends on University Facilities level decision making. Can the rooms be reverse-cycled (technically or at the whim of the animal care department)? Can you get access to the right light-cycle room for your animals for your experiments if you are low on the totem pole (as a lab or within a lab)?

Then there are within-lab factors. Limited numbers of operant boxes and limited numbers of hands. You cannot necessarily squeeze all of your animal work into the prime window of 6 h into dark to 12 h identified in the Roberts paper, above. Maybe this function changes depending on your procedures and you have an even narrower stability window.

So there will be compromises.

But these compromises will most assuredly affect the perceived replicability (aka generalization) of the work.

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Additional Reading:

On contradicting your own stuff

The most replicated finding in drug abuse science

The other day I was discussing the notion of what is “fair” in majority USian thinking.

In the US, it is considered fair if the very top echelon of the disadvantaged population succeeds at the level of the bottom slice of the advantaged distribution.

And if any individual of the top echelon of the disadvantaged population should happen to achieve up past the middle of the advantaged distribution? Well clearly that is unfair and evidence of reverse discrimination!

I was not familiar with the details of the Abigail Fisher (#StayMadAbby) case under consideration by SCOTUS (see Scalia) this week when I wrote that. I have learned a few things.

The University of Texas has a policy of accepting the top 10% of in-state high school graduates. This accounted for 92% of the slots when Ms. Fisher was applying for admission. She was not in the top 10% of her class.

Her qualifications were mediocre at best: A GPA of 3.59 and SAT scores of 1180/1600.

So she was less than amazingly qualified and was fighting for one of the 8% of the remaining admission slots for non-top-10% applicants.

There is more though, which is a real kicker. Again, from the Salon article. There were:

168 black and Latino students with grades as good as or better than Fisher’s who were also denied entry into the university that year.

So if she had been admitted, they would have all had a case that she was stealing their slot.

It gets better*.

It’s true that the university, for whatever reason, offered provisional admission to some students with lower test scores and grades than Fisher. Five of those students were black or Latino. Forty-two were white.

Emphasis added.

Ms. Fisher is suing on the basis of those five black or Latino students who were admitted. They had worse grades, you see, so she deserved to get in. And was discriminated against solely on the fact that she wasn’t black or Latina. Except 42 white students also were admitted with worse grades. So if anyone took her slot it is 42:5 THAT IT WAS A WHITE STUDENT.

And of course had she been offered admission, there were 168 individuals with the same claim against her that she is making now.

Reminder. This is not just one woman’s disappointed whinging and viral YouTube video.

This case has wended its way all the way up to the highest court in the land and is being considered by our SCOTUS Justices.

She is the best possible plaintiff. Because the details of this case underscore how true it is that “fairness” in this country is that which only just barely allows the disadvantaged to draw (almost) even with the very lowest attaining members of the advantaged populations.
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*worse

In oral arguments over an affirmative action case involving undergraduate admissions to the University of Texas, Justice Antonin Scalia had the following to say:

Justice Scalia: There are — there are those who contend that it does not benefit African-Americans to — to get them into the University of Texas where they do not do well, as opposed to having them go to a less-advanced school, a less — a slower-track school where they do well. One of — one of the briefs pointed out that — that most of the — most of the black scientists in this country don’t come from schools like the University of Texas.
Mr. Garre: So this court —
Justice Scalia: They come from lesser schools where they do not feel that they’re — that they’re being pushed ahead in — in classes that are too — too fast for them.

Episode IV: The completerer

December 8, 2015

Per usual, I throw out some observation or random remembrance and then it nags at me.

I come to the realization that perhaps the kids these days actually genuinely have no idea that there is/was/can be a better way.

Like when I remind you that Science and Nature “papers” were once barely more than abstracts. With a single figure, maybe two. And that the real followup paper was in another journal. Seriously, look back in the early 70s, maybe into the 1980s. The issues are available for your perusal.

This is another example. Two cases in which the same group published (or at least prepared to publish) at least four different papers from a single project. In the first case, it looks like the same three authors were on all four, they put it in the same journal and the first authors swapped on one. In the second case, the author list was more diverse and there were three different journals. (Interestingly, report III seems to be missing. I wonder what happened there? But still, the group published several other papers around the same time and on the same rough idea- perhaps one of those was supposed to be the III article?)

This sort of thing reinforces my criticism of the way Glamour Humping has done bad things to science and careers while not really providing anything more than a sham of the “complete story” in exchange.

If you want to publish several manuscripts on a topic, with different unshared unique first-author and last-author slots, it is possible. You get to throw up far more than a single published manuscripts’ limited number of figures. You can elaborate on side themes. Nothing gets hidden from view in the Supplemental Materials. And presumably the speed by which some of the story emerges in published form is enhanced. Which permits other people to see and use the information earlier.

It was possible once. It is possible again.

A window on what is fair

December 8, 2015

Apparently the SCOTUS is going to revisit an affirmative action case involving University admissions. I caught a small part of a NPR show on this, tuning in just in time to catch one of the opinion makers providing his analysis (around 37 min into the episode). It went something like this.

First, he noted in tones most disapproving, that “most of the students benefiting from affirmative action policies at elite universities are middle, or upper middle, class”.

This is, of course, one of the great strategies of the anti-diversity crowd, not least of which because they managed to get the pusillanimous support for it out of the squishier pro-diversity types. “Oh, yes, we must agree that affirmative action is about demonstrated acute disadvantage for each individual applicant to University“, is about the size of it. To be honest, I don’t know if this guy on the radio was anti-diversity or one of these folks who has been hornswaggled by this particular anti-diversity tactic. It doesn’t really matter because the result on the audience is the same.

Back to the story. Affirmative action is only for the most disadvantaged of the disadvantaged. Therefore, you see, if the beneficiaries of affirmative action policies are “middle to upper middle class”, well affirmative action is clearly broken.

As a bit of an aside, notice this neat little conflation? Middle class with upper-middle class? It’s bad enough that the concept of “middle class” is so huge and poorly defined that trying to claim members of the middle deserve no assistance in overcoming barriers to college admission is ridiculous. Oh no. We must roll this in together, seamlessly, with the upper-middle class. Because we know for damn sure that once you are in upper-middle, you deserve no help whatsoever. You have it made, baby.

So then, within a breath this guy says “….of course the white students are even richer” as barely an aside. Credit where due, at least he mentioned it. But AYFK? For whatever he meant by “elite Universities”, the white population was richer than “middle to upper-middle”.

Apple meet Orange. No matter how advantaged the beneficiary of affirmative action may be relative to the general population, he or she was still disadvantaged relative to the people at those elite Universities who were from the privileged groups. This is dismissed, however, as if it is barely relevant.

But wait, it gets better. He then immediately pivoted to “I don’t think anyone thinks that Obama’s children deserve affirmative action help”.

JESUS.

Last I checked, Obama’s salary was $400,000 per year and he gets, AFAIK, free room, much of his board and has a nice transportation allowance. Right? Plus, we know perfectly well that he and/or Michelle will make bank in the future from book royalties, speaking fees and the like. (Maybe even his SCOTUS salary? ….I crack myself up)

The Obama children are not middle class. They are not upper-middle class. They are lower rich.

But you see how this all works. It’s a nice little sleight of hand and misdirection. We’ve moved the conversation from middle class African-Americans, or other disadvantaged ethnicities, to….the children of the President of the United States.

Clearly if Sasha and Malia don’t need help then the child of a high school educated but stably employed and homeowning resident of Ferguson MO doesn’t need help either.

The anti-diversity voices want to further advance their agenda on the back of a very pernicious perception.

In the US, it is considered fair if the very top echelon of the disadvantaged population succeeds at the level of the bottom slice of the advantaged distribution.

And if any individual of the top echelon of the disadvantaged population should happen to achieve up past the middle of the advantaged distribution? Well clearly that is unfair and evidence of reverse discrimination!

Stop shaking your heads, scientist Readers. We have this same problem in every aspect of our business as well. From graduate school admissions to faculty new-hires. From grant award to tenure. Onward it goes. Ethnic minorities, sure, but also women and people who trained in the wrong University. There are the advantaged and there are the disadvantaged. Meaning, that for the apples to apples comparison we are talking about those who would all-else-equal succeed similarly. But because all else is not equal, some have an easier time than others. Some achieve higher with the same effort and others achieve the same with less effort. Either way, it is most assuredly not fair.

Any time there is under-representation, you will find that any efforts to make things fairer are crippled by this misunderstanding of distributions and individual accomplishment.

It is fair , you see, if the top 10% of the disadvantaged sneak up just parallel with the third quartile of the advantaged. Anything more is reverse discrimination and totally unfair to the advantaged among us.

A scientific quiz

December 5, 2015

I got twelve pretty quickly but I’d have to think a little harder for significantly more than that.

Bjoern Brembs has posted a lengthy complaint about the errors of fact made by incompetent reviewers of his grant application.

I get it. I really do. I could write a similar penetrating expose of the incompetence of reviewers on at least half of my summary statements.

And I will admit that I probably have these thoughts running through my mind on the first six or seven reads of the summary statements for my proposals.

But I’m telling you. You have to let that stuff eventually roll off you like water off the proverbial duck’s back. Believe me*.

Brembs:

Had Reviewer #1 been an expert in the field, they would have recognized that in this publication there are several crucial control experiments missing, both genetic and behavioral, to draw such firm conclusions about the role of FoxP.

These issues are not discussed in the proposal, as we expect the reviewers to be expert peers.

Speaking for the NIH grant system only, you are an idiot if you expect this level of “expert peer” as the assigned reviewers to each and every one of your applications. I am not going to pretend to be an expert in this issue but even I can suspect that the body of work on this area does not lead each and every person who is “expert” to the same conclusion. And therefore even an expert might disagree with Brembs on what reviewers should “recognize”. A less-than-expert is going to be subject to a cursory or rapid reading of related literature or, perhaps, an incomplete understanding from a prior episode of attending to the issue.

As a grant applicant, I’m sorry, but it is your job to make your interpretations clear, particularly if you know there are papers pointing in different directions in the literature.

More ‘tude from the Brembster:

For the non-expert, these issues are mentioned both in our own FoxP publication and in more detail in a related blog post.

These issues are not discussed in the proposal, as we expect the reviewers to be expert peers. Discussing them at length on, e.g., a graduate student level, would substantially increase the length of the proposal.

These are repeated several times triumphantly as if they are some excellent sick burn. Don’t think like this. First, NIH reviewers are not expected to do a lot of outside research reading your papers (or others’) to apprehend the critical information needed to appreciate your proposal. Second, NIH reviewers are explicitly cautioned not to follow links to sites controlled by the applicant. DO. NOT. EXPECT. REVIEWERS. TO. READ. YOUR. BLOG! …or your papers.

With respect to “graduate student level”, it will be better for you to keep in mind that many peers who do not work directly in the narrow topic you are proposing to study have essentially a graduate student level acquaintance with your topic. Write your proposal accordingly. Draw the reader through it by the hand.

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*Trump voice

It emerged on the Twitts today that sometimes postdocs can defer student loans and sometimes they cannot.

The bottom line is that you should check into your lender requirements, and then see how your HR department defines you.

The readership may have additional tips in the comments?