As you are well aware, Dear Reader, I have been a bit disappointed with the NIH response to the finding first reported in Ginther et al, 2011, i.e., that Black PIs suffer a grant funding disparity. From Ginther “[R01]applications from black investigators were 13.2 percentage points less likely to be awarded“. Of course this sounds better than it actually is since the white investigator award probability was only 29.3% in that sample, thus the disparity is better described as black investigators’ applications having only a 55% chance, relative to the white investigators’. A 45% reduction is a lot nastier sounding than a 13.2% reduction.

Sidebar: If this is all news to you, go read the Ginther paper and pay close attention to the supplemental materials. Before you start in on the “obvious” explanations.

Sidebar 2: Do NOT come at this with the hunt for nefarious, racist Snidely Whiplash on study section. This is absolutely not helpful. It doesn’t disprove this bias just because nobody says or writes directly and obviously racist twaddle. It doesn’t disprove that you are yourself part of the problem just because you don’t feel racist. Or are a black NIH funded PI yourself. Implicit and systemic biases go far beyond this.

Ginther had a followup publication in 2018, which appeared to support the NIH’s favored stance of “blame the victim”. The top line takeaway was that Black PIs had deficient CVs, in terms of paper count, citations and JIF, and thus it was totally their own fault if they were less successful at grant getting. Just from the Abstract alone we learn ” We found that black applicants reported fewer papers on their Biosketches, had fewer citations, and those that were reported appeared in journals with lower impact factors. Incorporating these measures in our models explained a substantial portion of the black/white funding gap.“. Pretty good stuff if you want to excuse this away. The Abstract is careful to note that “Although these predictors influence the funding gap, they do not fully address race/ethnicity differences in receiving a priority score” and if you look into the results you find comments such as ” The full model explains 52% of the black/white funding gap. Half of the explained gap is due to Biosketch publications “. I can’t recall if I blogged this particular juncture, I was getting pretty exhausted with the whole thing. But this was definitely a time when the top-line, headline type takeaway message was along the lines of “Well those black PIs are crappier scientists! Of course they can’t get funded”. Yeah. The paper then goes on to note the contribution of things such as black PIs being much less likely to be at the top 100 funded institutions and to have fewer collaborators. Eye of the beholder territory as to whether you see this as more criticism of the unworthy or as part and parcel of the systemic discrimination and disparity of opportunity. But still….only half of the disparity is explained away, even if you credit that these bibliometric indices should dictate who gets funded.

The most recent offering from the NIH on this topic is Hoppe et al, 2019. Which supports more victim blaming from the NIH but also provides some additional clarity on Gither et al, 2018. The dataset is now a post-Ginther one, running from 2011 to 2015 and, shocker, the disparity is again confirmed since “although the award rate has dropped for all applicants over the past decade, the funding rate for WH scientists remains approximately 1.7-fold higher than for AA/B scientists “. So….replication. Almost precisely. They did…..absolutely nothing in the immediate wake of Ginther. Nothing. Oh and it continued into FY17. The mind…..boggles.

One interesting new bit is the highly defensive “IC decisions do not contribute to funding gap” section which attempts to excuse out-of-order decision making. Problem is, they used this analysis technique: “below the 15th percentile, there was no difference in the average rate at which ICs funded each group; applications from AA/B and WH scientists that scored in the 15th to 24th percentile range, which was just above the nominal payline for FY 2011–2015, were funded at similar rates.” This doesn’t actually tell us on an IC by IC and round by round basis where the paylines were and whether a given grant was within-payline or an obvious pickup. For example, NCI, the largest IC by some margin, was running sub 10%ile paylines most of this time. So anything 10-15%ile at NCI was a pickup but not scored as such by the Hoppe analysis, if I have it right. Presumably this analysis did not exclude those ICs which go strictly by paylines and don’t make any pickups, either. In short, I’m not convinced.

The big deal of the paper, however, was a fancy topic word cluster analysis which shows that black PIs tend to cluster into certain topic domains and that these topic domains suffer disparately low rates of funding. For example:

Defining words in the eight clusters with the highest percentage of applications from AA/B applicants include socioeconomic, health care, disparity, lifestyle, psychosocial, adolescent, and risk; these clusters had funding levels ranging from 11.2 to 17.2% (table S7). In contrast, frequently used words in the eight clusters without any AA/B applicants (see Fig. 3A) include osteoarthritis, cartilage, prion, corneal, skin, iron, and neuron; these clusters had funding levels ranging from 12.5 to 28.7%

My SABV fan Readers will particularly enjoy the fact that “…the cluster with the lowest award rate, 7.5%, is characterized by the words ovary, fertility, and reproductive“. Lovely.

Despite the fact that the Abstract reads “Topic choice alone accounts for over 20% of the funding gap after controlling for multiple variables, including the applicant’s prior achievements” there was a tendency for the headline level news reporting to focus primarily on the topic as yet more victim blaming. The rationale is, basically, that this is not actually funding bias, or at least not bias directed at the racial characteristics of the PI. The maddening part is the data actually do not support this and in fact further reinforce the notion of racial bias. How so?

In the results of the paper, too far to expect your average journalist or the Director of NIH to go, we find this critical caveat: “WH applicants also experienced lower award rates in these clusters, but the disparate outcomes between AA/B and WH applicants remained, regardless of whether the topic was among the higher- or lower-success clusters“. The disparity remains. Even if you are working in the least-likely-to-be-funded topic domains, you still see a disparity. To the good, if you are white, and to the bad, if you are black.

THIS should be the messaging. Just as with the extensive set of analyses in the Supplement to the Ginther et al., 2011, paper, this shows that no matter how you slice it, there is disparity. No matter how many other factors you can identify that contribute, the essential core remains. (Until you get down to so many factors that you lose power and, voila!, no difference.)

Hoppe et al take a bit of a stab at the Matthew effect and then bring their strongest paragraph, peculiarly in the Results and not Discussion.

Viewed together, our data lead us to speculate that the funding gap between AA/B and WH scientists may be driven by a vicious cycle, beginning with AA/B investigators’ preference in the aggregate for topics less likely to excite the enthusiasm of the scientific community, leading to a lower probability of award, which in turn limits resources and decreases the odds of securing funding in the future. Mathematical modeling of the NIH review process has found that subtle depressions in score—the equivalent of a three-quarter point reduction on a scale of 1 to 9 by the three reviewers who provide the initial critiques used to inform which applications will be discussed—are sufficient to substantially bias the number of funded applications in favor of a preferred class of investigators (Day, 2015)

This is where I got really irritated with the quote from NIH Director Collins in the NIH’s press release. “We need to understand whether there is an intrinsic bias against such topics by reviewers, or whether the methodologies used in those fields of research need an upgrade.”   See? If those black PIs would just use the right methodologies, then all would be well. Because it is the topic domain. Oooops, except the paper actually addressed that and found that white PIs in those domains enjoyed higher funding rates. And by the way, the bias against the topic is about the “reviewers” and not about the NIH system. Because of course the NIH is at all times a perfect reflection of the objective merit of proposals.


In fact the NIH grant selection is inherently conservative. Those that do the initial, and most important, evaluation are peer scientists. But not just any old peer scientists. They have to have been successful at winning grant funding already. Which means they have been selected to favor, on average, certain topics, approaches and, yes Director Collins’ “methodologies”, over other ones. Like begets like in the NIH grant system. And all the while the participants pat themselves on the back about how they know what constitutes the “best science”. And everyone else agrees with them because they have been selected to do so. And those who are most successful at the operative game have a great reputation for knowing what is the “best science”. And so it becomes true.


I am not sure if Director Collins really can’t grasp the issues with the Matthew effect and the subjective value masquerading as objective value or whether he is out and out gaslighting on this. Today’s tweet from the Director of the NIMH is of a similar vein.

Since you have been reading along, you will spot the two things that are inconsistent with what Hoppe et al actually reported. First, it’s only 20% of the funding gap that is accounted for by topic choice. That is right there in the Abstract so you really have to wonder how NIMH Director Gordon could have possibly missed that. Second, when you correct for subject matter, Hoppe reports that the disparity remains! Strike two.

It could be intentional gaslighting on the part of NIMH Director Gordon. More likely it is that the top-level, headline takeaway is so seductive to NIH officials unwilling to face up to the implications of Ginther, etc, that they cannot retain anything else in their minds. This adds up to systemic gaslighting. Implicit perhaps. They are basically gaslighting themselves.

This is what I want to believe, anyway.

The Discussion in the Hoppe paper is an absolute disaster and I would really like to know about the various influences on it. Did reviewers insist on some of this? NIH officialdom? As mentioned above, the key bit is hidden in the Results for no apparent reason. The Discussion then puts these two sentences together in space.

While not underrepresented relative to applicants, the absolute number of AA/B reviewers is still quite small [2.4%], and it is conceivable that a more demographically diverse group of reviewers might have different opinions on the significance of some grant applications.

Together, our findings point to the salient factors for which targeted interventions could be considered in future attempts to address the funding gap. The first and most fundamental of these is to encourage a more diverse applicant pool.

These people know how review works. 2.4% isn’t going to do anything, even if you assume black reviewers are free from implicit biases themselves. (See comments above about the conservatism of review and you’ll understand this itself is a bad assumption.) They know this. So how can a more diverse applicant pool do anything? It can’t. You need to get to a more diverse pool of FUNDED PIs who can do their work, get their reputations, increase their citations….

record scratch. Oh yeah. About that Ginther 2018 finding. No. fricken. duh. Those who get more citations are those who publish more work, generate more academic progeny, collaborate with similarly active peers, etc….which are, you guessed it, those who have the grant funding.

It’s circular.

…and NIH is so stoned on their own supply that they cannot understand this. What is “the best science” on the “objective bibliometric measures” is a function of what they have funded.

The solution is quite simple. Fund the PIs who are currently suffering the disparity. Fund the topic domain African-American applicants. Remember, that only accounts for 20% of the problem. So you are by no means done yet, NIH. Fund the 50% that you screen out based on bibliometrics. How? I dunno. Maybe try dividing productivity and JIF by aggregate funding. Don’t forget to include all of those sources. And throw in a teaching load factor too.

But that won’t be enough either because those papers report only accounting for part of the White PI advantage.

So you may have to do what you already do for women PIs and ESI PIs. You know, NIH, when you have a disparity that you actually care about. You don’t commission all these reports and try desperately to escape the obvious. You don’t misrepresent a paper’s findings. You just….act. To close the gap.

You should try that with this one.

Diversity and Disadvantage

December 9, 2019

Mike Lauer, head of NIH’s Office of Extramural Research, has a blog post up which points to new and expanded “diversity” criteria for Administrative Supplements and other purposes. The Notice is: NOT-OD-20-031. The blog post includes the fact that fewer than 1% of the diversity supplements they awarded in 2018 were for the “disadvantaged background” criterion. It also shows that the vast majority of applications were under Hispanic or African-American categories (and the success rates for those were 70% and 62%, respectively).

The old “disadvantaged” criteria were:

Individuals who come from a family with an annual income below established low-income thresholds

Individuals who come from an educational environment such as that found in certain rural or inner-city environments that has demonstrably and directly inhibited the individual from obtaining the knowledge, skills, and abilities necessary to develop and participate in a research career.

The second one is almost laughably imprecise and amorphous and apparently instead of this resulting in a deluge of applications, it resulted in very few. So they’ve decided to expand and elaborate:

Were or currently are homeless, as defined by the McKinney-Vento Homeless Assistance Act

Were or currently are in the foster care system, as defined by the Administration for Children and Families;

Were eligible for the Federal Free and Reduced Lunch Program for two or more years;

Have/had no parents or legal guardians who completed a bachelor’s degree (see the U.S. Department of Education);

Were or currently are eligible for Federal Pell grants (;

Received support from the Special Supplemental Nutrition Program for Women, Infants and Children as a parent or child;

Grew up in one of the following areas: a) a U.S. rural area, as designated by the Health Resources and Services Administration Rural Health Grants Eligibility Analyzer, or b) a Centers for Medicare and Medicaid Services-designated Low-Income and Health Professional Shortage Areas  (qualifying zip codes are included in the file). Only one of the two possibilities in #7 can be used as a criterion for the disadvantaged background

So there you have it. More opportunities for those who are at disadvantage in the sciences to get support. Most pointedly, these individuals will qualify for Research Supplements to Promote Diversity in Health-Related Research (PA-18-586). These are administrative supplements, meaning any PI of a host of research grant mechanisms can request additional funds to support staff at any level ranging from high school students to investigators. No kidding!

My main purpose here is advertising/PR/education to the PI and to prospective candidates, as per usual. If you are, or know of, a candidate that fits, it may be worth trying this mechanism to get support. These new expanded definitions of socio-economic disadvantage may make it easier to determine who fits, relative to the prior criteria.

Do note that if you are a prospective candidate, you may have to self-identify to a PI. I mean, this is also the case for racial / ethnic qualifications, of course. But that’s hard enough for the PI to parse. Believe me, “say, are you some sort of minority that qualifies” is not an easy conversation to have with prospective trainees as it is. People of majoritarian presentation who may have no particular expression of their childhood disadvantage are even less likely than those with certain surnames or apparent skin tone to trigger an inquiry.

Moving on to the editorial part……you knew there would be a “but”……

I have always been a bit suspicious of efforts to add socio-economic considerations to affirmative action / diversity efforts. These come in, I have seen, whenever an institution appears to be under assault from anti-affirmative action positions that are mostly against giving opportunities to African-American, Hispanic and Native-American individuals. It isn’t that I don’t think socio-economic disadvantage is bad for the academy, I do. And in the best of worlds I would love it if we added this as an “also”. Which, given by the less than 1% stats reported by Lauer, the NIH program has been until this point. It does not appear to have chipped away at the awards to Hispanic or African-Americans in any large numbers. So….great. That’s the tactical angle- and I will be looking to see if Lauer updates us over time as to how these proportions are changing with the re-defined language.

There’s also a strategic angle. The strategy of making affirmative action a strategy to redress individual, personal disparity. This has been pursued by anti-affirmative action voices and has been a matter of craven capitulation from those who should know better.

Affirmative action, done right, is to address the systematic problems. A given University, say, that lacks a diverse faculty body, isn’t concerned with specific individuals. It is concerned with increasing the diversity of its faculty overall and it can’t expect this to be precise. It isn’t trying to be fair to Joe Smith who somehow deserves a position at that particular University.

The idea of enhancing diversity of the faculty is to enhance the diversity of the instruction and scholarship and other perspectives embodied by the professors. Should any one person be obliged to cover all the bases at once? Is the ideal candidate for diversity poor, LGBTQ+, female, of color, disabled etc? Of course not, that’s a Bill Maher bit.

And this is the slope that we start down with including socio-economic disparity in the diversity sphere. Combined with the aforementioned misdirection that this is about personal fairness, we open the door to the idea that the only legitimate diversity hire is the one where you can prove individual suffering from socio-economic disparity. It doesn’t matter that the person may have systemic discrimination and bias against them relative to others with their own background, you see. It doesn’t matter what perspectives they can bring to bear. Because we’re in the Oppression Olympics now, baby. And we’ve now moved to argue that only by demonstrating individual adversity relative to everyone, that we have achieved true progress towards identifying individuals who deserve diversity of opportunity.

This is a mistake.

And I will be keeping my weather eye on the NIH to see how they behave with this newly expanded definition.

I saw the following comment on twitter the other day and I can’t get this out of my head.

It reads:

A prestigious institution (from #1) told me that I was actually tied in the vote with their top candidate [a white male], but they’d only be making an offer to him because it’d be unfair to consider my race and gender in whether to make me an offer.

and the tweet in the thread that is referenced here reads:

1. When I asked why I didn’t get a faculty job at a prestigious institution, three different professors there told me they weren’t sure if I did my own research (sure, because my theorist advisors are so great with observations…).

I simply cannot get past this rather explicit comment than when a person of color or of female* presentation is viewed as being equal to a white man in academia, the decision has to be that the POC or female person must surely be passed over because otherwise it would be an “unfair consideration of race and/or gender”.



This is a situation that apparently reflected a vote of individuals. But I want you to broaden this to any situation in which scientists’ respective accomplishments are being assessed, even within the head of a single person. I suspect this kind of situation is a lot more common than could be revealed by the explicit statement such as is the subject of the tweet thread.

First, the notion that one has to pick the majoritarian person to be “fair” in resolving a tie is in fact unfair. The only way to be strictly fair would be to toss a coin. The outcome for women or people of color in general would, of course, continue to be unfair if they are underrepresented in the pools of exact ties but as far as this head-to-head comparison goes, a coin flip or other random decision maker would be fair.

Second, it is pretty obvious given implicit and explicit biases against women and people of color that they only get up to so called “objective” equivalence by being one heck of a lot better than the majoritarian person. They have higher hurdles to surmount to get up to the level of being judged as good.

Or do they?

One of the reasons that this remains on my mind is that I am not infrequently made aware of related situations in scientific job searches. People have a tendency to make observations to me about how they are trying to make a difference in hiring in their departments and how that is being stymied by their colleagues. The issues of comparative judgment, being “fair” and “objective” about the talents of the majoritarian candidates, obliviousness or unjustified protestations of innocence vis a vis implicit bias….these issues are a common feature.

And lurking behind much of it is the sort of unjustified anti-affirmative action trope that holds that surely it is the women, and the people of color, that have had a sweet ride on Easy Street. It is the Others that have had all the benefits of doubt, un-earned legs-up, chances and opportunities, not the good old straight white man, you see. Academia is, according to this trope, entirely biased for POC and for women and has been for decades.

Thus if we have equal assessment it is somehow in reality the white man who is the poor struggler who deserves the special consideration.

To be fair.

I am sure there are many of you that do not have these types of experiences in your departmental job searches. I’m sure that many of you have seen successful and fair recruitments occur.

But we are still struggling to move the needle on many of the statistics when it comes to representation and diversity in academic scientific hiring. So on the balance, we are still looking for ways to improve.

Being aware of, and prepared to counter, these sorts of reverse-racism analyses may be helpful.

*Yes I am well aware that women of color suffer a double whammy in these situations. And that there are LBGTQ issues. The oppression olympics are not, however, the topic of the day. The issue is majoritarian vs the Other that is perceived to have some sort of advantage when the decision goes to them following otherwise “equal” assessment.

This is an extension to some thoughts I posted on Twitter awhile ago.

There is a certain species of “amazing scientist who is revolutionizing everything” biographical puff piece that strikes an interesting chord about academics. These are details that come up in seminar introductions, blog posts, media profiles, institutional profiles, award nominations and obituaries.

I am referring specifically to the part where they talk about hobbies, interests and activities that are not directly related to work*.

I surmise the hobby is discussed in these types of pieces to humanize the nerd or to amaze you that their non-science time is just as obsessive and elite as their science**. Possibly both of these apply simultaneously. Typical realms of discussion are obsessive sports participation (very commonly running long distance events or triathlon competition), foodie obsession (he cooks lavish meals for his lab), wine snobbery or the arts. With respect to the arts, you most commonly hear about how the scientist being lionized plays a musical instrument in a band. Presumably this ties into our societal obsession with rock n rollers and their supposed rebel natures. We know Francis Collins plays the guitar in a band. We know Nora Volkow likes to run. I can’t remember hearing about any community minded hobbies of any of the other IC directors.

You don’t hear about how the awesome scientist pulls his (it’s usually a him) weight at home in these types of settings. Obsessive plumbing leak fixer! Soccer dad! Makes meals for his family on the regular!

You don’t hear about community stuff either. Many scientists participate in local groups for improving the schools or city governance or their faith community. Many spend their time volunteering in the classroom.

And it isn’t just the puff pieces that draw this distinction between the externally-focused activities and the obsessively internally-focused ones. Academic science actually punishes people for anything they do that isn’t self-oriented.

If one is highly accomplished in science it is okay to have hobbies as long as they are obsessively self-involved ones like running marathons. It is obvious that any sort of external activity or hobby is only okay if the science work is considered to be of the highest rank. If one is considering a middle of the road scientist then clearly they should be spending more time at work and less time training for a marathon!

Look, I get that we like to know more about people’s life outside of their work. Pursuit of the personal detail fuels industries valued in the billions of dollars when it comes to famous movie stars, musicians, politicians and professional athletes. There is no reason that people in science wouldn’t also have an interest in the non-work activities of the more famous members of our professions.

But still. The relative selectivity in what we choose to lionize versus criticize about our science peers seems meaningful to me. It has an effect on all of us, including (most importantly) our trainees. Personally, I do not want people in science thinking (no matter how implicitly) that obsessive, self-involved hobbies are associated with the most revered scientists and that community type, external benefit activities are the hallmark of the scientific nobody.

Perhaps we could think twice about those seminar speaker intros we give and the nature of the puff pieces we write or contribute background to.

*Calm yourselves debate champeens. This set of observations is about which hobbies we choose to laud in a professional context and which ones we do not. It doesn’t mean you are horrible for running every day. Exercise is healthy and good for you. We should all do more of it.

**And I should also note that this doesn’t have to devolve into “I only have time for work” snark, no matter the reality. I’m not criticizing hobbies and activities at all. I think that is great if you have things that make you happy. Again, this is about the type of such non-science hobbies that we find reason to congratulate or merely to note in a professionally-oriented biographical piece.


July 12, 2018

One of my favorite thing about this blog, as you know Dear Reader, is the way it exposes me (and you) to the varied perspectives of academic scientists. Scientists that seemingly share a lot of workplace and career commonalities which, on examination, turn out to differ in both expected and unexpected ways. I think we all learn a lot about the conduct of science in the US and worldwide (to lesser extent) in this process.

Despite numerous pointed discussions about differences of experience and opinion for over a decade now, it still manages to surprise me that so many scientists cannot grasp a simple fact.

The way that you do science, the way the people around you do science and the way you think science should be done are always but one minor variant on a broad, broad distribution of behaviors and habits. Much of this is on clear display from public evidence. The journals that you read. The articles that you read. The ones that you don’t but can’t possible miss knowing that they exist. Grant funding agencies. Who gets funded. Universities. Med schools within Universities. Research Institutions or foundations. Your colleagues. Your mentors and trainees. Your grad school drinking buddies. Conference friends and academic society behaviors.

It is really hard to miss. IMO.

And yet.

We still have this species of dumbass on the internet that can’t get it through his* thick head that his experiences, opinions and, yes, those of his circle of reflecting room buddies and acolytes, is but a drop in the bucket.

And they almost invariable start bleating on about how their perspective is not only the right way to do things but that some other practice is unethical and immoral. Despite the evidence (again, often quite public evidence) that large swaths of scientists do their work in this totally other, and allegedly unethical, way.

The topic of the week is data leeching, aka the OpenAccessEleventy perspective that every data set you generate in your laboratory should be made available in easily understood, carefully curated format for anyone to download. These leeches then insist that anyone should be free to use these data in any way they choose with barely the slightest acknowledgment of the person who generated the data.

Nobody does this. Right? It’s a tiny minority of all academic scientific endeavor that meets this standard at present. Limited in the individuals, limited in the data types and limited in the scope even within most individuals who DO share data in this way. Maybe we are moving to a broader adoption of these practices. Maybe we will see significant advance. But we’re not there right now.

Pretending we are, with no apparent recognition of the relative proportions across academic science, verges on the insane. Yes, like literally delusional insanity**.

*94.67% male

**I am not a psychiatristTM


June 4, 2018

There is a new blog at that seeks to give voice to people in STEM disciplines and fields of work that have experienced sexual harassment.

Such as Jen:

The men in the lab would read the Victoria’s Secret catalog at lunch in the break room. I could only wear baggy sweatshirts and turtlenecks to lab because when I leaned over my bench, the men would try to look down my shirt. Then came the targeted verbal harassment of the most crude nature

or Sam:

I’ve been the victim of retaliation by my university and a member of the faculty who was ‘that guy’ – the ‘harmless’ one who ‘loved women’. The one who sexually harassed trainees and colleagues.

or Anne:

a scientist at a company I wanted to work for expressed interest in my research at a conference. … When I got to the restaurant, he was 100% drunk and not interested in talking about anything substantive but instead asked personal questions, making me so uncomfortable I couldn’t network with his colleagues. I left after only a few minutes, humiliated and angry that he misled about his intentions and that I missed the chance to network with people actually interested in my work

Go Read.

There was a comment from girlparts on my prior post which triggered an anecdote from my past. It seemed worth having its own post. I guess in a way it is relevant to the broader question of how one should react if someone speaks disparagingly of “diversity hire” professors. This little experience certainly went into helping me to see yet another way that the Defenders Of Quality are total hypocrites when it is something dear to them. Unsurprisingly because such individuals tend to lean conservative and therefore act like conservatives- i.e., selfishly hypocritical.

girlparts observed:

And, of course, members of underrepresented minorities are much less likely to be able to benefit from knowing someone famous etc.

During one of my science training stops I was in a Department that had a couple of these anti-affirmative action type established Professors. They were loud and confident so we were under no illusions whatsoever about what they thought about a whole host of things. They were walking reddit threads* long before reddit was a thing.

Relevant to this tale is that there were two individuals hired during my association with that Department that were widely and almost openly derided as “dean’s hire” affirmative action appointments. Particularly by the aforementioned rightwinger Defenders of Quality but you tended to hear it from everyone. EveryoneKnows(tm) They Are AffirmativeAction Hires That We Wouldn’t Have Hired Save For The Dean.

Of course they were generally shit on by the department. I was not privvy to specific details but I watched as they got crappy space (literally in the basement), nobody seemed to want to collaborate and they always seemed to struggle to get access to resources. Both of them eventually left. This, bad as it is, is not the main point of the tale.

The main point is that a few years later there was a non-minority hire in the department. She had trained in the department and that alone was a tiny bit eyebrow raising because the Department definitely had the ethos of geographic nomadism being the best. It goes without saying that some of the Defenders of Quality were had been the loudest about how surely we could not hire our own trainees or anybody too well-associated with the department! That would compromise our quality.

But even better was the fact that soon after the hire it turned out that she was engaged to one of the established faculty. Naturally that guy was one of the jerkiest Defenders of Quality and most fervent Anti-Affirmative-Action Warriors. The most reddit of walking reddit threads. And here he was, engineering the tenure track Assistant Professor appointment of his soon-to-be spouse.

Of course the tale gets even better. There were at least four examples of women married to established professors in the department who had tried to get faculty appointments over the previous decade and a half. None of them got Asst Prof offers and had to settle for bad non-tenure track barely faculty appointments. They struggled along on the margins of slightly above adjunct teaching gigs and shoe string research activities. So on the one hand, of course this couple that pulled it off had to be totally secret about their relationship until after she’d gotten hired.

OTOH… oooooh, baby there were some angry folks.

*thanks to someone who may or may not choose to self-identify in the comments for this little gem

Thought of the day

February 27, 2018

Someone on the Twitters was asking for ideas about what to say in response to faculty that say, dismissively, that other faculty members are “diversity hires”. The implication, stated or not by such folk, is that persons of color, or of nonXY chromosomal identity, are clearly inferior merely because of such identities.

In context of prospective new faculty during a hiring cycle, the VeryConcerned person often asserts that they are only concerned with keeping up the standards of the department.

“Can’t have all these inferior diversity hires dragging us down, chaps! Hrm, hrm.”

My thought is this.

In science, the young, new hires are always better than the department’s current average. They have more cutting edge techniques, fresher ideas, less historical baggage and/or likely better collaborative relationships. They are not yet burned out, quite the contrary.

So the VeryConcernedColleague can rest at ease. The new hire is going to improve the Department, no matter who is hired out of the Long List of reasonably attractive candidates.

…a picture he took with the 0.2%.

A News piece in Science by Jeffrey Mervis details the latest attempt of the NIH to kick the Ginther can down the road.

Armed with new data showing black applicants suffer a 35% lower chance of having a grant proposal funded than their white counterparts, NIH officials are gearing up to test whether reviewers in its study sections give lower scores to proposals from African-American applicants. They say it’s one of several possible explanations for a disparity in success rates first documented in a 2011 report by a team led by economist Donna Ginther of the University of Kansas, Lawrence.

Huh. 35%? I thought Ginther estimated more like a 13% difference? Oh wait. That’s the award probability difference. About 16% versus 29% for white applicants which would be about a 45% lower chance. And this shows “78-90% the rate of white…applicants”. And there was Nakamura quoted in another piece in Science:

At NIH, African-American researchers “receive awards at “55% to 60% the rate of white applicants,” Nakamura said. “That’s a huge disparity that we have not yet been able to seriously budge,” despite special mentoring and networking programs, as well as an effort to boost the number of scientists from underrepresented minorities who evaluate proposals.

Difference vs rate vs lower chance…. Ugh. My head hurts. Anyway you spin it, African-American applicants are screwed. Substantially so.

Back to the Mervis piece for some factoids.

Ginther..noted…black researchers are more likely to have their applications for an R01 grant—the bread-and-butter NIH award that sustains academic labs—thrown out without any discussion…black scientists are less likely to resubmit a revised proposal …whites submit at a higher rate than blacks…


The bias study would draw from a pool of recently rejected grant applications that have been anonymized to remove any hint of the applicant’s race, home institution, and training. Reviewers would be asked to score them on a one-to-nine scale using NIH’s normal rating system.

It’s a start. Of course, this is unlikely to find anything. Why? Because the bias at grant review is a bias of identity. It isn’t that reviewers are biased against black applicants, necessarily. It is that they are biased for white applicants. Or at the very least they are biased in favor of a category of PI (“established, very important”) that just so happens to be disproportionately white. Also, there was this interesting simulation by Eugene Day that showed a bias that is smaller than the non-biased variability in a measurement can have large effects on something like a grant funding system [JournalLink].

Ok, so what else are they doing?

NIH continues to wrestle with the implications of the Ginther report. In 2014, in the first round of what NIH Director Francis Collins touted as a 10-year, $500 million initiative to increase the diversity of the scientific workforce, NIH gave out 5-year, $25 million awards to 10 institutions that enroll large numbers of minority students and created a national research mentoring network.

As you know, I am not a fan of these pipeline-enhancing responses. They say, in essence, that the current population of black applicant PIs is the problem. That they are inferior and deserve to get worse scores at peer review. Because what else does it mean to say the big money response of the NIH is to drum up more black PIs in the future by loading up the trainee cannon now?

This is Exhibit A of the case that the NIH officialdom simply cannot admit that there might be unfair biases at play that caused the disparity identified in Ginther and reinforced by the other mentioned analyses. The are bound and determined to prove that their system is working fine, nothing to see here.

So….what else ?

A second intervention starting later this year will tap that fledgling mentoring network to tutor two dozen minority scientists whose R01 applications were recently rejected. The goal of the intervention, which will last several months, is to prepare the scientists to have greater success on their next application. A third intervention will educate minority scientists on the importance of resubmitting a rejected proposal, because resubmitted proposals are three times more likely to be funded than a de novo application from a researcher who has never been funded by NIH.

Oh ff….. More of the same. Fix the victims.

Ah, here we go. Mervis finally gets around to explaining that 35% number

NIH officials recently updated the Ginther study, which examined a 2000–2006 cohort of applicants, and found that the racial disparity persists. The 35% lower chance of being funded comes from tracking the success rates of 1054 matched pairs of white and black applicants from 2008 to 2014. Black applicants continue to do less well at each stage of the process.

I wonder if they will be publishing that anywhere we can see it?

But here’s the kicker. Even faced with the clear evidence from their own studies, the highest honchos still can’t see it.

One issue that hung in the air was whether any of the disparity was self-inflicted. Specifically, council members and NIH officials pondered the tendency of African-American researchers to favor certain research areas, such as health disparities, women’s health, or hypertension and diabetes among minority populations, and wondered whether study sections might view the research questions in those areas as less compelling. Valantine called it a propensity “to work on issues that resonate with their core values.” At the same time, she said the data show minorities also do less well in competition with their white peers in those fields.

Collins offered another possibility. “I’ve heard stories that they might have been mentored to go into those areas as a better way to win funding,” he said. “The question is, to what extent is it their intrinsic interest in a topic, and to what extent have they been encouraged to go in that direction?”

Look, Ginther included a huge host of covariate analyses that they conducted to try to make the disparity go away. Now they’ve done a study with matched pairs of investigators. Valantine’s quote may refer to this or to some other analysis I don’t know but obviously the data are there. And Collins is STILL throwing up blame-the-victim chaff.

Dude, I have to say, this kind of denialist / crank behavior has a certain stench to it. The data are very clear and very consistent. There is a funding disparity.

This is a great time to remind everyone that the last time a major funding disparity came to the attention of the NIH it was the fate of the early career investigators. The NIH invented up the ESI designation, to distinguish it from the well established New Investigator population, and immediately started picking up grants out of the order of review. Establishing special quotas and paylines to redress the disparity. There was no talk of “real causes”. There was not talk of strengthening the pipeline with better trainees so that one day, far off, they magically could better compete with the established. Oh no. They just picked up grants. And a LOT of them.

I wonder what it would take to fix the African-American PI disparity…

Ironically, because the pool of black applicants is so small, it wouldn’t take much to eliminate the disparity: Only 23 more R01 applications from black researchers would need to be funded each year to bring them to parity.

Are you KIDDING me? That’s it?????

Oh right. I already figured this one out for them. And I didn’t even have the real numbers.

In that 175 bin we’d need 3 more African-American PI apps funded to get to 100%. In the next higher (worse) scoring bin (200 score), about 56% of White PI apps were funded. Taking three from this bin and awarding three more AA PI awards in the next better scoring bin would plunge the White PI award probability from 56% to 55.7%. Whoa, belt up cowboy.

Moving down the curve with the same logic, we find in the 200 score bin that there are about 9 AA PI applications needed to put the 200 score bin to 100%. Looking down to the next worse scoring bin (225) and pulling these 9 apps from white PIs we end up changing the award probability for these apps from 22% to ..wait for it….. 20.8%.

Mere handfuls. I had probably overestimated how many black PIs were seeking funding. If this Mervis piece is to be trusted and it would only take 23 pickups across the entire NIH to fix the problem….


Twenty three grants is practically rounding error. This is going to shake out to one or maybe three grants per year for the ICs, depending on size and what not.

Heck, I bet they fund this many grants every year by mistake. It’s a big system. You think they don’t have a few whoopsies sneak by every now and again? Of course they do.

But god forbid they should pick up 23 measly R01s to fix the funding disparity.

Michael Balter wrote a piece about sexual harassment accusations against paleoanthropologist Brian Richmond, the curator of human origins at the American Museum of Natural History that was published in Science magazine.

This story has been part of what I hope is a critical mass of stories publicizing sexual harassment in academia. Critical, that is, to stimulating real improvement in workplaces and a decrease in tolerance for sexual harassing behavior on the part of established scientists toward their underlings.

There have been a very disturbing series of tweets from Balter today.

Holy….surely it isn’t connected to….

Oh Christ, of course it is….

but they published it so…?

Well THAT should have a nicely suppressing effect on journalists who may think about writing up any future cases of sexual harassment in academia.

UPDATE: Blog entry from Balter.
ETA: I am particularly exercised about this after completing, just this week, a survey from AAAS about what the membership expects from them. The survey did not seem to have a check box item for “Fight against scientific and workplace misconduct”.

One of the things that determines success in science careers is the opinion ~three peer reviewers have about your manuscript as offered up for publication in a given journal.

Hopefully I do not have to rehash the way that journal identify of a scientist’s published work affects career success.

Hopefully I do not have to rehash the way that bias creeps into what otherwise is supposed to be objective analysis.

And let us leave your well-intentioned, but hopelessly naive calls for blinded peer review aside until that nirvana is reached.

Do you think about reviewer diversity at all? Many journals publish a year-end list of all reviewers (these don’t say how many each reviewer wrote, of course). Have you ever scanned them for, say, gender balance? If you are an AE or EIC….does diversity* concern you?

On the author side, would you work to ensure your suggestions for potential reviewers are not biased? Do you ask for about as many women as men? Does ethnic or other minority characteristic of your suggestions play a role?

I’m guessing the answer is no?

I have taken to trying to suggest equal numbers of male and female reviewers when I submit a manuscript. This is pretty simple in my fields of work, so long as you think about it.

Other forms of representation? Not really possible, is my first thought. But….now I’m thinking about it. Maybe I’ll put a few people on my usual lists that I do not typically consider.

And when I get a chance I’m going to go through those published reviewer lists. I’m curious how the journals I think of as being in my field are doing.

*Editorial boards are another place to look, those are published.

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.

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.

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.