Posted by Janet D. Stemwedel on March 21, 2009 When scientists make claims with numbers they have clearly pulled out of thin air. For example:
Ultimately, success is only about 0.01% based on ‘strategies’ like those espoused on this blog, and 99.99% on simply doing good science and explaining a good plan well.
Is commenter Dave making a subtle joke here? Or what?
Because the way science is supposed to be played, making up frequencies (or probabilities, for that matter) is Just Not Done.
You’re upset that someone is using joke statistics to make a rhetorical point? Making up numbers *and trying to make people think they came from a valid study* is Just Not Done. But is there anyone who would read that comment and actually think that Dave had done some sort of study that showed what percentage of scientific success was based on the blog’s strategies? You’re welcome to not like that style of presenting an idea, but to conflate it with the real ethical violation of data-faking seems bizarre.
Heh heh. That’s one of my pet peeves too.
Dave is just one of a cadre of whiny-ass titty-babies who are annoyed for god knows what reason that DrugMonkey is a respected and valued source of useful advice for biomedical scientists in advancing their careers.
actually, my favorite stat was the “0.001% chance whose grant is under review and they are trailing spouses…” by OMGWTFBBQSOL in the same thread as Dave. They are utterly clueless.
jc,
I elaborated on that thread as follows: “The low percentage I chose was simply to emphasize the insignificance of the problem. However, if we could get the NIH to provide their statistics on spouses applying to the same study section, I don’t think it would be much greater than said percentage.”
Do you have any data to show that the percentage of trailing spouses applying for NIH grants in the same study section as their wife/husband is higher or lower than 0.001%? Maybe it is the comment by OMGWTFBBQJC that indicates cluelssness.
I would not do so in any context of importance. But I have been guilty of statements such as, “It is estimated that almost all, 98.674%, are . . . ” in contexts where I was sure that at least 97.645% of the readers would understand I was being whimsical.
sol, you still haven’t provided any advice for crystal. You dismissed her issue as being insignificant rather than addressing the issue she is dealing with. Nice dodge.
That’s how Sol rolls when someone makes a perfectly valid point about the perception of women in academia. He condescends their concerns and calls them whiners. I think there is a 99.999% chance that he is just being an ass.
And I like the retort of, “Yeah, I made up some numbers, but do you have any evidence that this is not the case?” that’s totes how I do science. I publish some shit saying, “x is the cause of y” without doing any experiments and, when the reviewers call my ass on the carpet I say, “Well, do you have any evidence that x isn’t the cause of y?”
QED, bitches.
jc,
Eventualy, you haven’t read my advice to her on DrugMonkey’s blog. Go and check it out, but in case you are too lazy, here it is:
‘Do not count on the fairness of the members of the study section. Highlight your own work and make every effort to avoid the study section your spouse’s grant applications are reviewed by.”
Isis, if 0.001% is the percentage of cases on which you determine perception, I believe that you are the one her ass should be called on the carpet and why you are qualified as a whiner.
Sure, we know 38% of statistics are made up on the spot.*
My point is, when scientists do it — whether in the context of a discussion of their findings, or of the prevalence of fraud in their field, or of mentoring strategies, or what have you — when they make up data rather than admitting “I don’t know the exact prevalence of X (nor does anyone, to the best of my knowledge), that’s lying. Scientists, of all people, should understand the importance of distinguishing between what you know and what you guess. Scientists, of all people, should understand the value of admitting ignorance in situations where good data has not yet been collected.
Doing otherwise may be human, but it’s not scientific.
_____
*Ironically, 38% is the number I was told the first time I heard this claim, and it’s the number I’ve used ever since in making this claim. Go figure.
Janet, your comment is so silly that I can only imagine you are attempting to re-spark debate about what is a scientist and what is scientific.
Do you really think that scientists are not permitted to use ordinary language meanings of words and colloquialisms in their non-peer reviewed discourse? And that for a scientist to do so on a blog is lying?
Perhaps you are not familiar with the distinction between scientific reasoning and scientistic posturing? Or between philosophy and pedantry?
Eventualy, you haven’t read my advice to her on DrugMonkey’s blog.
In the interest of truthful dialogue, those who do not read DrugMonkey might be interested to know that multiple different commenters–including me–debunked Rivlin’s advice as completely worthless.
This is funny. I was having a conversation with my CareBear just yesterday where he started talking (a bit like a 6 y/o, if you ask me) about a ‘million billion trillion to the billionth’ power gallons of water on a far off (hypothetical) planet. He got so carried away I was sure he’d have the magnitude of atoms in the known universe or something even greater, rather than any remotely feasible number. It annoyed me and amused me at the same time. Seriously, what is the problem with the nicely ambiguous “zillion” in this case?
Also enjoyable are “just a smidgen” “oodles and scads”, and, in the cases cited above, an “eensy weensy teeny tiny chance of …” (you have to say this in the Rachel Maddow voice though)
At the same time, I’m solidly in Jim’s 97.645%; plus I’m in the subset of those that enjoy whimsy.
So I can get annoyed by this type of thing. I generally like things to be accurate, if advertised as precise. But I also like having fun with numbers. For me, this includes guesstimating something and considering it correct if within an order of magnitude. And whimsy.
I found the other example in the previous thread more problematic than the one you pulled out. When I read “success is X% based on yada yada”, well, there’s just no meaningful way to interpret that number, regardless of the value of X. So that passes completely under my radar.
However, a statement that .001% of PIs are what was it? I forget, but that statement can actually be evaluated as true or false. So there I have a problem with made-up numbers. It’s innumerate, and dishonest. Saying it again (and again) doesn’t change that.
Isis, if 0.001% is the percentage of cases on which you determine perception, I believe that you are the one her ass should be called on the carpet and why you are qualified as a whiner.
Sol, you’re adorable. Don’t ever change.
Isn’t it rather obvious that this is a rip-off of Eddisons
“Genius is one per cent inspiration, ninety-nine per cent perspiration”?
Would you also not accept that quote?
Just want to say two words that, at least to my mind, sum up the use of made up numbers: context matters.
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