Home Birther Logic. or “Logic” actually

Riddle me this.

For background, Isis the Scientist started some shit by posting

Your Home Birth is Not a Feminist Statement

which sounds totally noncontroversial right from the start. But since it reviewed some data on home birth suggesting up to 37% of planned home births result in emergency hospital visits and noting as much as a 0.3% uptick in the neonatal death rate, well, the home birth fans went shitnutz.

One can only hope that this homebirth person who had one kid die, one need resuscitation and still can’t understand why anyone would think she’s high risk is rare. Very rare.

Kate Clancy, for whom I have a great deal of respect on most issues, has a somewhat reasonable post up on the motivations for home birther fanaticism.

And these motivations are key, I agree. Because these motivations are driving otherwise reasonable people into a frenzy of woo based illogic that is really something to see.

There is one particular bit of thinking that I cannot for the life of me grasp. I’m going to pick on this post from homebirthercurious Dr.B

Hospitals are clearly equipped for dealing with the worst case scenarios. But it also seems that they are big fans of unnecessary interventions.

but really it pops up everywhere. Such as on the Twitts:

Given that it’s kinda a one way trip, how does one determine this? RT @DrSnit: @drisis I don’t see your blog about unnecessary c-sections

and

absent evidence of convenience scheduling, you simply have no idea what the “unnecessary” rate actually IS. No way to tell. @DrSnit

Right? RIGHT??????

In birthing, the only way to know if a procedure was “unnecessary” or “necessary” is to either do it or not do it and figure out if the bad consequence is prevented, ameliorated or unaffected. And unfortunately you only get one try for each case study. Which means that you cannot actually know for sure for any particular case whether the procedures were in fact “necessary”.

Amirite?

Please explain to me, homebirther fans who wield the “unnecessary intervention” cudgel, exactly how you can determine which procedures were and were not necessary in advance. Because I am missing your logic here.

Look, science-based and/or evidence-based medicine recognizes that in the cases that are interesting*, there is rarely such a thing as a clear cut 100% accurate prediction of the future. What there is are probability distributions. If the kid’s heart rate slows down by such and such, the damn cord is wrapped around it’s neck X% of the time. Or, when the kid is in breech, Y% of the time the delivery ain’t going well.

Which always leaves some percentage of the time that everything is going to be fine and dandy.

Between fine-and-dandy land and 100% of births, however, you are playing with the health, well-being and even viability of a new human being. And this, mind you, is just for the stuff we can actually detect with high confidence is an adverse effect on the child. Dying is a pretty good one there, also hypoxia induced brain damage.

We do not know, however, if there are more subtle effects. Maybe you knock 5 pts off the kid’s IQ because you insist on laboring too long for “the experience”. Maybe you bathe that little wackaloon in hormonal responses that produce a raft of a subtle effects on development? Or maybe the child’s innate stress responses set a different stage. Who knows? Me, I’m betting on the side of smooth deliveries. Relatively rapid appearance of the kid once the laboring commences is my preference.

This last part is MY version of birth woo. I’d rather not take chances.

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*i.e., debatable.

Racial Disparity in NIH Grants: Solutions from Your Humble Narrator

A comment by Halophile on a prior post asks:

I’m honestly interested in how a hypothetical NIH Director DrugMonkey would handle the situation.

This was in response to my expressed skepticism that putting together an advisory panel was the right solution. Especially when they are tasked with:

Its charge will focus on five key transition points in the pipeline: (i) entry into graduate degree programs; (ii) the transition from graduate degree to post-doctoral fellowship; (iii) the appointment from a post-doctoral position to the first independent scientific position; (iv) the award of the first independent research grant from NIH or equivalent in industry; and (v) award of tenure in an academic position or equivalent in an industrial setting. The Committee will provide concrete recommendations to the NIH Director on ways to improve the retention of underrepresented minorities, persons with disabilities, and persons from disadvantaged backgrounds through these critical periods.

These are age-old concerns of academia and the solutions are not at all simple. And the obvious stuff comes up over and over again. With little success*. I am making the leap here that the primary motivation of this new panel is a response to the recent revelation that African-American Principal Investigators who apply to the NIH for research grant funding are having poorer outcomes than are white PIs. Correspondingly I think they should be focusing on the proximal problem and not letting themselves get distracted into the larger problem. Yes, even if the proximal issue is a death-of-a-thousand-cuts type of dealio. Yes.

My take with respect to the NIH response is as follows.

i) and ii) are things the NIH is supposedly already doing and tracking with their NRSA programs, MARC training grants and assorted other topics. So first, this is being taken care of elsewhere in the institution. Second, it is pretty damn far away from the prize and you would have to start with a hypothesis that somehow the good African-American scientists are being disproportionately shelled out at grad school and postdoctoral transitions. Thus, those that make it through to apply for grants are only the mediocre ones and this relationship differs for white scientists. I think this is a low probability hypothesis. Move on.

iii) is certainly a concern, particularly with the recent focus of the NIH on transition, creation of the K99/R00 mechanism and general worry about “the next generation”. At this point I’m doing the facepalm and thinking “yeaaah, that should have been an obvious component of this K99/R00 flurry but damn I bet it wasn’t.” However. Much like my response to items i and ii, this is still a bit distant from the grant outcome issue that has been revealed.

iv and v are where the money is. This is where the NIH needs to focus. The fate of existing junior and not-so-junior faculty particularly where it comes to winning grant support from the NIH. Stop getting distracted with “tenure” though, except where you can identify that clearly with disparity in NIH grant awards, the need for African-American investigators to submit more times for a given award, etc.

I am dismayed that the charge is not to delve further into the causes of disparate grant review outcome. To go right at the proximal problem, now, with great dispatch and figure out how to fix it. As soon as possible. Why? Because this news has an immediate and discouraging effect on our current trainees! Not to mention the PIs…

Now, maybe further data mining has already been conducted or is in the works but we don’t know that. Tabak and Collins referred to some preliminary analyses that may or may not go beyond what Ginther et al reported. Here’s what I would commission from the CSR data miners.

-Outcomes for black versus white applicants on a study section by study section basis.

-Participation of African-American and white reviewers on each panel; heck throw in the same racial/ethnic breakdowns used by Ginther while we’re at it.

-Outcomes on a IC by IC basis as well.

These are important bits of information. Is there any relationship with particular scientific domains, review panels or review panel makeups? That would recommend one set of fixes. If not, we’d have to move on to other considerations.

Next up…..um, why not actually talk to the applicants? Supplementary Table 2 of Ginther says there were only 2,942 applications with Black PIs from 2000-2006, 285 awards. I think the 16 member panel could make a serious dent in interviewing this population of investigators. A couple of emails and badabing! What do they think has been helpful and detrimental to their successes and failures as applicants? Where do they point the finger? I’m not saying they will have the same viewpoint or even necessarily be correct (with respect to the broader problem) but for goodness sake this is a place to generate some hypotheses, is it not?

Finally, I come to the most immediate response of all. Programmatic alterations in funding priority. This disparity is a bias in the system, like it or not. Not dissimilar to the bias against new investigators that has been a repeated topic of my blogging. Familiar, in fact, to an older (yet sadly ongoing) discussion of bias against female investigators.

The NIH has responded quite directly in the most recent case of new investigators by putting a finger on the scale to rebalance outcomes. The less established investigators are still getting crappier scores from review panels (and maybe even worse), but the NIH is choosing to pick them up out of the review order in recognition that poorer review outcome is a bug in the system.

This is no different. So my clearest answer to the question raised by Halophile is that I’d put out the word, informally if I had to**, that I was expecting the IC heads to fix the problem pronto. To examine their portfolios of scores in each round to make sure they were prioritizing*** black PI apps in their above-payline pickups.
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*Sorry but I am exhausted by us majority white institution folks fruitlessly pointing the finger at the supply chain below us. It dilutes the blame and gives a handy out when you fail to improve. There are two methods, only, that work. They are related to each other. The pull side, “attractiveness” of a career, a University, a training program, etc, solves itself as a self-fulfilling prophesy. When women, gays, the poor and minorities inhabit specific roles in society, that makes them more imaginable to subsequent generations. Make the job “look” diverse and dismantle any real hurdles that exist and you are most of the way over the hump. How to get there? I am on record as a big fan of creating overt, visible diversity by any means necessary. This brings me to the second method- money. Making your graduate program, postdoctoral environment or faculty ranks more diverse is simple- outbid the competition for the limited resource.

**think, rightwing anti-affirmative action political bigots

***By way of disclaimer, yes, this would theoretically benefit people who’s careers are of direct personal and professional interest of mine.

NIH Director empanels working group on diversity

The initial response to the dismal news about black-white disparity in grant scores and funding is…create an advisory panel.

I have seen this reaction before and indeed served on such panels at the local institutional level.

I am not hopeful.

They have a boatload of people listed on the roster already. Going by the stats on the number of African-American PIs, this panel could easily interview each and every one of them. And make a damn good start on all the unsuccessful ones too.

I suggest they start there.

Rather than the usual hot air that never goes anywhere…