The Department of Psychological and Brain Sciences at Dartmouth College (yes, that department) has announced a most unusual academic position that they are seeking to fill.

Huh? Well, let us click through and read the details.

The Department of Psychological and Brain Sciences at Dartmouth College invites applications for a Faculty Fellow, a two-year residential postdoctoral appointment, that will convert automatically to a regular full-time tenure-track appointment as Assistant Professor. Faculty Fellows are part of a cohort of faculty committed to increasing diversity in their disciplines. We are interested in applicants whose research can connect to and/or bridge between any foci in our department including behavioral, cognitive, social and affective psychology and neuroscience. We are especially interested in candidates who have a demonstrated ability to contribute to Dartmouth’s diversity initiatives in STEM research, such as the Women in Science Program, E. E. Just STEM Scholars Program, and Academic Summer Undergraduate Research Experience (ASURE).

That’s about it. The rest is boilerplate with minimal details, including about the salary and resources being offered. So we have to assume “postdoctoral appointment” means the usual for a postdoc. Salary something along the lines of the NRSA scale and no individual resources such as a nice startup package or research space. Maybe there will be, but it is not on evidence in the job solicitation.

This is CLEARLY a DEI hire. An attempt to diversity a faculty that looks to my eye like it could use some diversification.

Instead of just hiring a person at the faculty level directly, they will be getting faculty level effort and behavior out of someone for the low, low price of a postdoc stipend. With a guarantee of “automatic” conversion which one, frankly, doubts will be iron clad.

This is so dismally emblematic of the institutional efforts to respond to the pressure to diversify their faculty.

Are any of you seeing similar proposals lauched at your University? What is the rationale here? What is the justification for this over just creating new faculty lines and hiring into them?

I can think of a couple of rationalescuses.

It is some sort of tenure clock manipulation. If they think, for whatever reason, that someone that will be able to contribute to “Dartmouth’s diversity initiatives in STEM research” will have a hard time making tenure on the usual schedule in their Department, this could be the reason for the plan. This would be an extra red flag warning to any applicant, of course. If the Department can’t get behind valuing these contributions as a substitute for their other expectations, and only see them as add-on effort that delays “real progress”, then this person will always be at odds with an unsupportive Department. Tenure is a risky proposition, no matter how long the decision is delayed.

It could be some sort of “we can get this approved quickly but oh how hard it is to get a new tenure line approved for this cycle” thing. Yeah, well that questions the commitment of the College and the “automatic” conversion. So surely this isn’t going to be raised.

A colleague from elsewhere indicated that something like this is being tried in their Department. The rationale is, from what I can tell, that scientist of color are reluctant to take on postdoctoral training (pretty sure I’ve seen data on that mentioned somewhere) and that this leak in the pipeline could be addressed by offering faculty positions earlier. Ok, I definitely buy that more security of a career would be helpful to keep promising younger scientists from bailing on the academic track before or during the expected postdoctoral interval. But. But, but but. Why not just hire straight into a faculty position? Course relief, service relief, etc, is already standard operating procedure. If a Department or University (or College) thinks this needs to be extended two or three years longer for these earlier-career hires, so be it.

This brings us to the longer arc of wage manipulation in the individual sense and in the industry sense.

If these Departments who are all really concerned about DEI and are launching various hiring initiatives were serious, they would have to be out there competing with each other for the existing pool of academic scientists in more or less the same position as their usual hires. As we know, there aren’t a lot of them, particularly when it comes to African-American scientists and some other key Federally defined underrepresented groups. So, according to market forces the Departments would have to PAY. More salary. More support. More startup cash. More housing / relocation allowances. More spousal hire opportunity. More everything.

This plan short circuits that by locking in candidates before they are as competitive on the open market. When they are still relatively desperate and/or think this is a great opportunity to jump ahead on the career arc. And as more Departments catch wind of this excellent strategy they are more likely to opt for this can-kicking strategy and less likely to PAY to get those who are currently trained to the usual point of faculty hires.

Biased objective metrics

October 19, 2021

As you know, Dear Reader, one of the things that annoys me the most is being put in the position of having to actually defend Glam, no matter how tangentially. So I’m irritated.

Today’s annoyance is related to the perennial discussion of using metrics such as the Journal Impact Factor of journals in which a professorial candidate’s papers are published as a way to prioritize them for a job search. You can add h-index and citations of the candidate’s papers on an individual basis on this heap if you like.

The Savvy Scientist in these discussions is very sure that since these measures, ostensibly objective, are in fact subject to “bias”, this renders them risible as useful decision criteria.

We then typically downshift to someone yelling about how the only one true way to evaluate a scientist is to READ HER PAPERS and make your decisions accordingly. About “merit”. About who is better and who is worse as a scientist. About who should make the short list. About who should be offered employment.

The Savvy Scientist may even demonstrate that they are a Savvy Woke Scientist by yelling about how the clear biases in objective metrics of scientific ability and accomplishment work to the disfavor of non-majoritarians. To hinder the advancement of diversity goals by under-counting the qualities of URM, women, those of less famous training pedigree, etc.

So obviously all decisions should be made by a handful of people on a hiring committee reading papers deeply and meaningfully offering their informed view on merit. Because the only possible reason that academic science uses those silly, risibly useless, so called objective measures is because everyone is too lazy to do the hard work.

What gets lost in all of this is any thinking about WHY we have reason to use objective measures in the first place.

Nobody, in their Savvy Scientist ranting, seems to every consider this. They fail to consider the incredibly biased subjectivity of a handful of profs reading papers and deciding if they are good, impactful, important, creative, etc, etc.

Even before we get to the vagaries of scientific interests, there are hugely unjustified interpersonal biases in evaluating work products. We know this from the studies where legal briefs were de/misidentified. We can infer this from various resume-call back studies. We can infer this from citation homophily studies. Have you not every heard fellow scientists say stuff like “well, I just don’t trust the work from that lab”? or “nobody can replicate their work”? I sure have. From people that should know better. And whenever I challenge them as to why….let us just say the reasons are not objective. And don’t even get me started about the “replication crisis” and how it applies to such statements.

Then, even absent any sort of interpersonal bias, we get to the vast array of scientific biases that are dressed up as objective merit evaluations but really just boil down to “I say this is good because it is what I am interested in”. or “because they do things like I do”>

Citations metrics are an attempt to crowd source that quality evaluation so as to minimize the input of any particular bias.

That, for the slower members of the group, is a VERY GOOD THING!

The proper response to an objective measure that is subject to (known) biases is not to throw the baby out onto the midden heap of completely subjective “merit” evaluation.

The proper response is to account for the (known) biases.