Interview - Practice, Ethics & Integrity - Jelte Wicherts (Part 3 of 4)

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Del curso dictado por University of Amsterdam

Quantitative Methods

979 calificaciones

University of Amsterdam

Quantitative Methods

979 calificaciones

Curso 1 de 5 en SpecializationMethods and Statistics in Social Sciences

Discover the principles of solid scientific methods in the behavioral and social sciences. Join us and learn to separate sloppy science from solid research! This course will cover the fundamental principles of science, some history and philosophy of science, research designs, measurement, sampling and ethics. The course is comparable to a university level introductory course on quantitative research methods in the social sciences, but has a strong focus on research integrity. We will use examples from sociology, political sciences, educational sciences, communication sciences and psychology.

De la lección

Practice, Ethics & Integrity

In this last content module we will focus on the part of the research process that follows data collection. The specifics of storing data and using statistics form a course topic in their own right (see the specialization courses on Basic and Inferential Statistics). For now we will focus on more general issues to do with data, interpretation and dissemination of results that relate to ethics and integrity. Some of the concepts that we discuss here will be familiar if you watched the interviews of the past modules. It might be interesting to (re-)watch these if you have the time!

Interview - Practice, Ethics & Integrity - Jelte Wicherts (Part 1 of 4)7:00

Interview - Practice, Ethics & Integrity - Jelte Wicherts (Part 2 of 4) 8:41

Interview - Practice, Ethics & Integrity - Jelte Wicherts (Part 3 of 4) 6:26

Interview - Practice, Ethics & Integrity - Jelte Wicherts (Part 4 of 4) 2:25

Conoce a los instructores

Annemarie Zand Scholten
Assistant Professor
Economics and Business

We've seen some big fraud cases in the Netherlands.

>> A couple of them.

>> Yeah.

>> And some people have said, this is the reason that we have these cases.

Everything has to be earth shaking, and our research has to be always, you know,

positive finding, exciting results.

>> Yeah.

You can't comply with that always.

So, for some people, the answer is?

>> They'll make it up.

>> I'll make it up.

>> Yeah, yeah.

It's a very difficult question.

It's in, now there are different aspects to it.

And the first thing is that,

like any societal endeavor there are people who want to get ahead.

There are people who want to get ahead regardless of anything.

So, and we have an incentive structure, and

we have a structure in place in science, in which we work to publication,

the novel ones in particular, this science or

nature publications, if you, you want to mention the biggest journals in the world.

>> Mm-hm.

>> and, and there'll always be cheaters.

I'm pretty sure that there'll always be cheaters.

And there's different types of cheaters.

But there's cheaters in, in professional cycling,

there's cheaters in the banking industry, in the finance industry.

There's cheaters everywhere.

There's cheaters in school, even students do it.

They even admit doing it sometimes.

[LAUGH] Diederik Stapel

indicated

he, he was found guilty and admitted to having fabricated data.

So, making up data entirely.

Now, this is the big fraud.

He ended up they, they fully investigated it he,

it ended up that he probably fabricated data in 55 or more papers.

>> 55? >> Yes he wrote about 130 papers.

You could still probably say that half of them are genuine.

I don't know.

But the problem is 55 papers.

So, this ranks among the most biggest fraud cases.

>> Yeah.

>> And this is so this is then counted as the number of

articles that are then retracted so you can keep.

Count of the number of retracted articles.

He's not the world champion in that regard.

[LAUGH] there, there's a Japanese medical researcher Fuji,

who ranks the highest at 194.

>> Oh.

The papers are being retracted.

He had been going on for quite a long time, which is also very amazing to

see in anesthesiology, which is a very difficult word to tell.

>> Anesthesiology.

>> That's the one. >> That's the one.

>> He actually did work on Propofol, which,

which is the drug that killed Micheal Jackson.

>> Oh, right.

>> I'm not saying, suggesting that he killed Michael Jackson but [LAUGH].

He did research on that and these are very easy trials,

actually, because you can do the studies, when you have a,

a hospital with, with people who were operated on.

So, is so, also, so many, many studies completely made up.

There is also very high profile cases in what we again maybe considered,

maybe considered the ideal science, so physics, there is a guy called

Jan Hendrik Schön who was the up and coming guy, about whom some of his colleagues mentioned,

well he is either going to get the Nobel Prize or he is going to end up in jail.

[LAUGH] He didn't end up in jail, he did fall from grace, he ended up,

I don't know the number of retractions but, he,

he published, well, science and nature papers, every month.

It was ridiculous and, of course, then people found it that some of the pictures

in these papers, which are again related to completely different topics.

>> Mm-hm.

>> Were completely identical.

So, completely different measurements showed the same spikes in the graphs.

>> So, how many brilliant frauds are just better at it and are not

>> That's difficult to say, that's very difficult to say.

We know that the fraud cases across sciences.

It's not just us no, no, no, certainly not.

There may be in psychology some more but

its, there's, there's also in the medical field a lot that's a large field as well.

Are there more out there?

Probably yes.

It must be, I mean if you consider some of the,

the silly things that made up his data he didn't do

a very good job in making up the data, because it didn't look [CROSSTALK].

Now the problem is how do you estimate the number of frauds out there?

And one way to do it is just to ask people, do you know?

>> Mm. >> Of course it has,

to ask them anonymously, and

with all sorts of assurances that they will be not be hanged.

Which is, the common response, by the way, which is intriguing.

But and if you don't look at the surveys and, and Daniele Fanelli is a researcher

is Italian but now works in Canada, did a, a meta analysis of these different surveys.

>> Okay.

>> In which then researchers were ask a great deal of

questions about well things that do not bear the light of day.

Those things that, in which researchers deviate from this ideal scientific norm.

So, these are the small things as well, the grey zone, but also some of

these surveys ask directly, have you ever falsified or fabricated data and then.

Yeah, his estimates sent us around 2%.

>> 2%.

>> And that's quite a lot if you compare it to the number of cases that we know.

>> Mm. >> Should amount to 400 researches in

the Netherlands alone only, and we know only 25 cases or so [CROSSTALK] .

>> Yeah. >> So,

there, the chance of getting caught is fairly slim.

And the question then is, how.

As a science, because this is problematic.

It's problematic, because we get results that are completely fake.

>> Yap. >> They might or might not be right.

Probably not.

But we also have this problem as, because we're in, in this structure of incentives.

Stapel got a lot of grants.

>> Yeah. >> This Jan Hendrik Schön guy,

Fuji, all these people got a lot of research money.

Based on fakery.

So it's also a sense of dishonesty there and

it's weird because we don't expect scientists to do that.

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