Comment by tptacek | Hacker News Reader

Comment by tptacek | Hacker News Reader

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I've heard a lot of complaints from a lot of different people working in lab science (in my case, my interest was in bio & chem) and none of them were about "tightly walled journals" (working academic researchers generally have institutional access, and when the logins are annoying to manage they just sci-hub like everyone else) or IRBs.

Rather, it was very basic stuff, like being told to come in at 5:30AM to feed a cell line only to have the PI show up at 2PM, throw the experiment in the garbage, threaten the student's livelihood, and then demand they stay until 11:30PM redoing the experiment. Over and over again, at random intervals.

I asked around about this stuff because a family member now works in the field and had some startling experiences, only to find that this is apparently almost universal, and that what I'm describing is on the lighter end of it. There are stories about labs at elite universities where the grad students have set up secluded spaces to go hide from their PIs and cry. It's everything you've heard about working as a developer at a video game company, dialed up to 11.

I don't really speak out of concern of the well being of those in research, but for the health of the system as a whole.

The fact it's a monster that eats people alive to me is an evidence that the whole thing needs to be torn down and replaced, which is the best way to erase all these sorts of harms.

But this isn't about today's scientists. I fully expect a collapse of academia to harm anyone currently in it, because the skills you need to succeed will change dramatically

>The fact it's a monster that eats people alive to me is an evidence that the whole thing needs to be torn down and replaced, which is the best way to erase all these sorts of harms.

It is easy to tear down but hard to build.

I get that you are jaded, but tearing down institutional science is just going to harm future scientists by robbing them of opportunity. Yes the system isn't perfect, but that doesn't mean we have to throw it in the trash in its entirety.

What does Opportunity have to do with science?

In this case, it seems like the Opportunity is an opportunity to get trapped in a system that is likely to be both unsatisfactory and unproductive.

My fear is that we've crossed the event horizon and we can't rollback all the alterations that accumulated over the years and gotten academics into a cul-de-sac or box canyon. (Pick your metaphor...) next stop, the singularity, where we will have the opportunity to experience life as a dimensionless point...

>What does Opportunity have to do with science?

Most science requires specialized tools and materials that cannot be obtained outside of an institutional environment. Tearing down the institutions means ceasing basically all non-profit generating "big science" efforts. That robs future scientists of working on the cutting edge.

A garage lab is fun idea, but the reality is infeasible in most circumstances. Even if possible, it will be slap-shod and a gigantic money pit that no granting agency will give a dime to.

>My fear is that we've crossed the event horizon

Hyperbole. Science existed before institutions and will exist after if it all should come tumbling down. There are more scientists than there has ever been, and as a result a lot of "boring" but necessary science is happening, but that doesn't mean there aren't rebels and outlaws in that same system asking interesting questions and overturning ideas.

Very interesting points. Thanks for taking the time to share.

I had a friend who made a big board with switches and knobs on it that changed lights and other stuff. It connected to nothing. But sometimes the professor would come to the lab to "be helpful". So they would point to the board and say turn that switch when I ask. Or rotate that knob or whatever. And the professor would get bored and leave after a while. But I guess he was good at getting money so that's all that matters in some places.

A lot of this seems to be poor leadership ability. Unfortunately, it seems like in the sciences you can get get promoted because you’re really good technically, but these skills don’t mean you can manage a hill of beans. Rather than treating the whole system down, maybe we need to look to promote those who can manage teams rather than just those who are “merely” technically bright.

Hiring boards at major universities know leadership ability is valuable, it's just that there are very few people with the skills, the credible track record, the leadership/teaching ability, and willing to apply, that they have to settle for less. And it so happens that this is where it's easiest to justify settling.

A lot of folks talk about how hard it is to find a tenure track job but it's actually trivial for anyone in the 99th percentile of all 3 categories.

But for anyone with that combination of talents, they can easily make 7 figures in a comfortable job outside of academia so not many of them apply even at the Stanfords and Harvards of the world.

>And it so happens that this is where it's easiest to justify settling.

Why do you think this is so? Is it because technical skills are more easily measurable and thus more defensible than so-called “soft skills”?

I think it goes without saying that most 99 percentilers can get the job of their choosing within that skillset. My question is more about the ranked priorities of the rest of the "middling" candidates. Why is the value system is structured to reward one type of skills when everyone seems to conclude it doesn’t provide good outcomes?

Because leadership skills and teaching ability are much harder to objectively measure on a CV and in a few hours of face-to-face meetings.

Whereas everyone on a hiring committee can tell quite quickly if a prospective applicant is blowing smoke about their technical skills, competence at navigating academia, etc...

This is the same dynamic everywhere when multiple qualities are valued but only some of those qualities are easy to quantify or assess.

I tend to agree. But I do think it’s a solvable problem by valuing, teaching, and prioritizing leadership skills. I think one of the problems in academia is that specialization requires people to forgo learning those traits, and they revert to what they’re comfortable evaluating (because it’s also what they specialize in)

What? Do you understand my previous comment?

I think so. I’m drawing a distinction between the difference being due to an ability to measure and the difference being due to self-selection, predicated on the need to specialize.

If you’re interviewing with a group of mathematicians, there’s a greater likelihood they will consider math skills to be the Ine Important Thing, in part because they’ve had to focus on that so much it becomes disproportionately important in their worldview. It’s a bias due to being overly focused on a specialization.

> I tend to agree. But I do think it’s a solvable problem by valuing, teaching, and prioritizing leadership skills. I think one of the problems in academia is that specialization requires people to forgo learning those traits, and they revert to what they’re comfortable evaluating (because it’s also what they specialize in)

I don't see where you drew the distinction, can you point it out?

How does the possibility of mathematicians being narrow minded in your second paragraph relate to this distinction?

>I don't see where you drew the distinction, can you point it out?

>"I think one of the problems in academia is that specialization requires people to forgo learning those traits, and they revert to what they’re comfortable evaluating (because it’s also what they specialize in)"

There's a distinction in avoiding a measure because it's not quantifiable and just plain not feeling as comfortable in that domain.

>How does the possibility of mathematicians being narrow minded in your second paragraph relate to this distinction?

When you're a hammer, every problem looks like a nail. Humans tend to be cognitively lazy, so they revert to what they know when faced with uncertainty. E.g., a mathematician feels more comfortable measuring math skills, even though a better measure may be a combination of math and leadership skills. So they tend to hire quants with poor management traits. It doesn't mean they couldn't evaluate the soft skills, it means they chose not to.

Using a different analogy, if you asked a sprinter to choose a decathlete, what skills do you think they would more heavily weight in their evaluation? I'm saying it's likely they would more heavily weight the sprinting events because they don't know how to evaluate the other events as well. They specialize in sprinting, after all, and that's what they know and feel comfortable with. The result probably isn't going to select the best overall decathlete, but it doesn't mean the other events couldn't be measured.

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