Calling Bullshit Profile picture
May 2, 2021 26 tweets 9 min read Read on X
In our course, we spend a couple of lectures talking about how tell whether scientific research is legit.

callingbullshit.org/tools/tools_le…
Appearing in a journal from a reputable scientific publisher is a good start. But it's no guarantee.

@lastpositivist pointed us a paper from a journal produced by the largest scientific publisher, Elsevier.

sciencedirect.com/science/articl…
The study looks for the genetic basis of psychic ability.

Yes, you read that right.

To do that, I suppose you have to start with psychics. And they did.

"Candidate cases were vetted for their psychic claims."
Vetted? How?

By self-report, followed by a couple of "tests"

(Interesting twist: the main test involved "precognitive ability" to guess a random number that a computer hadn't selected yet.)
Of course any good study needs a control group, and so they created one. Fair enough.

Interesting that all "vetted psychics" were Caucasian women over 37.

We are not told the demographics of the full 3000+ who filled out the original survey. Any guesses?
The control group then completed the same tests of psychic ability.

Here's the thing.

They did just as well as the group of "vetted psychics" did!
But wait! The text says they did better on the the Remote Viewing test. Maybe that's the one that really matters, and the other tests aren't good tests.
Nope. Read the fine print under the table.

The authors *claim* the difference reached statistical significance in the text, but in the fine print note that it didn't actually reach significance once you account for multiple comparisons.
If you ever see these sort of thing in a paper—either their claims that that "most Xs are bigger than Ys, even though it's not significant", or worse yet a claim in the text that a difference is significant coupled fine print in a table saying that it is not—be very wary!
Let's take stock where we are: We've got a group of "vetted psychics" and a control group of random non-psychics, who have scored the same on the researchers' own test of psychic ability.
And where we're going: We want to find genetic differences associated with the differences in psychic ability THAT WE DIDN'T FIND BETWEEN OUR CASE AND CONTROL GROUPS.

How would you proceed at this point? I sure wouldn't waste the genetic tests. But the authors are bolder than I.
They went ahead and collected some sort of unspecified DNA sequence data. Whole genome sequence I would guess? Remarkably, I don't think the paper ever tells us.

And what did they find?

No differences between vetted psychics and controls in protein coding regions.
Nope, all they found was that all of the case samples but only two of the control samples had an A instead of a G in an intron, a part of the gene that is cut out before it is used to code for a protein. Such differences are generally expected to have no physiology effect.
Let's take stock again.

Now we've got a group of vetted psychics and a group controls who have

(1) no differences in psychic ability on the researchers' own choice of tests and

(2) no genetic differences.

Should be a pretty open and closed case, right?
Well, not according to the Discussion section of the paper.

The authors argue that the reason they didn't see any statistical difference in ability was not because there was none, but rather "likely due to the small number of participants".
A couple of observations here.

First, if I look for difference in flying ability between penguins and ostriches and find none, there's more likely hypothesis than "the small number of participants".
Second, sample size is under the control of the investigators, let these investigators argue that "the performance tests were not powered to detect differences."

Why on earth would you run a study you knew was not powered to detect the differences you were looking for?
But we shouldn't make too much of those tests anyway, the authors tell us. The psychics reported that the "tasks did not adequately capture their particular set of skills."

That's what I told Mrs. McClellan after I failed seventh grade social studies.

She gave me an F anyway.
Here I pause simply to note that the authors must travel in different circles than I do.
Besides, the authors note, there were some differences between cases (psychics) and controls.

Cases were more likely to believe in paranormal phenomena.

No kidding. You just screened them for *believing they were psychic.*
Next we get detailed cross-cultural sociogenetic analysis.

Wow. That sound like some serious science.

No. Actually it's a term that's appeared only once before—in a different paper by one of this study's authors.

Don't be intimidated by jargon! Or least make sure it's real.
Anyone with a bit of background in population should read the above. It's wild. To summarize, the authors find a single base pair difference in a non-coding genomes of a very small sample of people who don't differ in psychic ability, and from this posit a selective explanation.
Namely, modernization led to relaxed selection on psychic ability (which, I remind you, is determined by this single base-pair difference in a non-coding region and not manifested in the phenotypes of the study subjects), and this is driving a shift in allele frequencies.
Another tip: the extraordinary amount of effort here put into the analysis of a complete non-result should itself be a red flag, even if you don't know enough population genetics to realize that GPT-3 could have written something more convincing.
Next the authors note that the more common allele in their controls is less common in the population at large. They forget that the controls are just that—random controls—and not people selected for lack of psychic ability.

So they conclude that psychic ability must be common!
Honestly I'm a bit exhausted at this point and feel like I just finished watching Inception backward, stoned. I'll leave you with the conclusion of the paper and remind you that it is based on finding no genetic differences between two small groups with no phenotypic differences.

• • •

Missing some Tweet in this thread? You can try to force a refresh
 

Keep Current with Calling Bullshit

Calling Bullshit Profile picture

Stay in touch and get notified when new unrolls are available from this author!

Read all threads

This Thread may be Removed Anytime!

PDF

Twitter may remove this content at anytime! Save it as PDF for later use!

Try unrolling a thread yourself!

how to unroll video
  1. Follow @ThreadReaderApp to mention us!

  2. From a Twitter thread mention us with a keyword "unroll"
@threadreaderapp unroll

Practice here first or read more on our help page!

More from @callin_bull

Apr 7, 2022
Where have we heard this before?
"Sophisticated algorithms based on machine learning may discover very delicate and elusive nuances in facial characteristics and structures that correlate to innate personal traits and yet hide below the cognitive threshold of most untrained nonexperts."

callingbullshit.org/case_studies/c…
Read 6 tweets
Mar 13, 2022
Campbell's Law states that "The more any quantitative social indicator is used for social decision-making, the more subject it will be to corruption pressures and the more apt it will be to distort and corrupt the social processes it is intended to monitor."
Even the most elite institutions succumb.

Here's a beautiful example of how one tracks down and debunks quantitative malfeasance.

Report author Michael Thaddeus says it best:

"Columbia is a great university and, based on its legitimate merits, should attract students comparable to the best anywhere. By obsessively pursuing a ranking, however, it demeans itself. The sooner it changes course, the better."
Read 5 tweets
Dec 13, 2021
Some of you may have seen this before, but if you haven't: This slide from Moderna compares their flu mRNA vaccine to the one from Sanofi.

Can you spot the misleading dataviz trick? Image
This was a fascinating exercise. People pointed out a lot of important issues.

The different age groups, while not a dataviz trick per se, do smack of the sort of apples-to-oranges comparison we worry about.
Using a log scale for bar charts is questionable territory, though a log scale is quite appropriate here for this kind of data and I've been guilty of the same. We wrote a bit about this special case: callingbullshit.org/tools/logarith…
Read 5 tweets
Dec 10, 2021
In our course, we spend a lot of time talking about selection bias and related phenomena. These issues can be extremely subtle. Example:

The question is whether you are better protected against COVID if you've first vaccinated then reinfected, or first infected then vaccinated.
To answer that, you might look at data such as those in a recent medRxiv paper by Goldberg et al.

Comparing infection rates, it *appears* you are better off 6-8 months after being infected then vaccinated ( RtV) than you are 6 months after being vaccinated then infected (VtR).
(Here I'm setting aside issues of significance, multiple comparisons, etc. — this is intended as a teaching example.)

But there's a problem with that inference, grounded in the fact that we are looking at observational data: the groups caught COVID under different circumstances.
Read 6 tweets
Sep 22, 2021
Obviously the murder rate in the US is a dreadful thing and we want to find ways to reduce it.

But I find the graph below, which is making the rounds today on social media, to be quite misleading.

Let's take a look at why.

nytimes.com/2021/09/22/ups… Image
The first thing to notice is that this graph shows annual *change* in murder rate. Showing changes is fine, when there's a good reason to—and there may be one here.

But notice the consequence. The much larger decrease, spread over many years from the late 90s, is backgrounded.
Here is are the absolute numbers over the same time period. To the credit of the @nytimes, this graph is shown in the article as well.

But of course that's not the one that takes off on twitter, facebook, etc. Image
Read 6 tweets
May 24, 2021
I just read a *great* paper on digital literacy.

The authors explore how three different groups—Stanford students, professional academic historians, and fact checkers—evaluate the reliability of online information.

papers.ssrn.com/sol3/papers.cf…
tl;dr — the fact checkers are very good at this, whereas the students and history professors alike are terrible.

What's the difference? Fact checkers read laterally instead of vertically.
Lateral reading means leaving the site one is trying to evaluate and learning about it from external sources—wikipedia, newspaper articles, etc.

Vertical reading is close reading of the site itself, trying to ascertain reliability from subtle cues therein.
Read 9 tweets

Did Thread Reader help you today?

Support us! We are indie developers!


This site is made by just two indie developers on a laptop doing marketing, support and development! Read more about the story.

Become a Premium Member ($3/month or $30/year) and get exclusive features!

Become Premium

Don't want to be a Premium member but still want to support us?

Make a small donation by buying us coffee ($5) or help with server cost ($10)

Donate via Paypal

Or Donate anonymously using crypto!

Ethereum

0xfe58350B80634f60Fa6Dc149a72b4DFbc17D341E copy

Bitcoin

3ATGMxNzCUFzxpMCHL5sWSt4DVtS8UqXpi copy

Thank you for your support!

Follow Us!

:(