Korrelation und Kausalität – Verblödung der Sozialwissenschaften
Beides Dauerthema seit der Frühzeit meines Blogs.
Leserzuschrift:
Studie zu Verwechslung Korrelation und Kausalität in Geiseswissenschaften
Sehr geehrter Herr Danisch,
nun ist es amtlich, in Papers wird zunehmend Koreelation mit Kausation verwechselt
Correlation is increasingly being written like causation, study of 194,631 papers finds
August 29, 2026
Researchers analysed 194,631 cross-sectional social-science papers and found causal language in nearly half, with the rate climbing above 60% by 2024. A separate experiment showed that the wording can change what readers believe the evidence proves.
Und darin:
Researchers analysed 194,631 cross-sectional social-science papers and found causal language in nearly half, with the rate climbing above 60% by 2024. A separate experiment showed that the wording can change what readers believe the evidence proves.
“People who exercise more are happier.”
That sentence sounds simple, but scientifically it leaves an important question unanswered.
Does exercise make people happier, or are happier people simply more likely to exercise?
New research suggests social-science papers are increasingly using language that can blur this distinction.
Researchers analysed 194,631 cross-sectional studies published between 1980 and 2024 and found that 46.3% used causal language in their titles or abstracts, despite relying on research designs that generally cannot establish cause and effect on their own.
The trend has also accelerated dramatically.
Around 20% of the papers used causal language at the beginning of the 2000s. By 2024, the proportion had risen to more than 60%.
The study, published in Nature Human Behaviour, suggests that one of science’s most familiar warnings remains surprisingly relevant:
[…]
Calvin Isch and colleagues at the University of Pennsylvania searched large academic databases covering five areas of social science.
They first identified studies that relied exclusively on cross-sectional data and excluded papers containing longitudinal or experimental components.
The researchers then examined the titles and abstracts of those papers for language implying that one variable caused, changed, increased, reduced or otherwise affected another.
Because manually reading almost 200,000 articles would be impractical, the team developed automated classifiers and validated them against expert human judgements.
The final dataset contained 194,631 cross-sectional studies.
Across those papers, 46.3% contained language the researchers classified as making or implying a causal claim about the study’s own results.
Naja, das sage ich ja seit Jahren über die Sozial- und Geisteswissenschaften: Wer eine Korrelation findet, darf sich eine Kausalität frei aussuchen.
Warum?
Weil es da nicht um Wisssenschaft, sondern um die Rhetorik der willkürlichen Behauptungen geht. Die Korrelation ist die Rhetorik zur Behauptung.
Und wie wirkt das?
Readers actually believed the stronger wording
The researchers then tested whether this language makes a practical difference.
They recruited 1,105 college-educated adults in the United States and gave them abstracts from cross-sectional studies published in prominent journals.
Some participants saw the original abstract containing causal language.
Others saw a rewritten version that described the findings only as associations.
Another group received the original abstract together with a short note explaining that the study was cross-sectional and therefore could not establish causality on its own.
Readers exposed to the causal wording were more likely to conclude that the research had demonstrated a genuine cause-and-effect relationship.
Changing the wording or clearly identifying the methodological limitation reduced that tendency.
The language therefore did more than make the paper sound stronger.
It changed what readers thought the evidence had actually shown.
Und ein Beispiel geben sie auch:
One word can substantially change the meaning
Consider two hypothetical headlines:
“Working from home increases productivity.”
And:
“Working from home is associated with higher productivity.”
They may sound almost interchangeable in everyday conversation.
Scientifically, they make different claims.
The first implies that changing where someone works will change their productivity.
The second says only that the two were observed together.
If the underlying research surveyed workers once, the second formulation is usually the safer interpretation.
Remote workers may have different occupations, employers, personalities, working conditions or levels of seniority. Any of those differences could contribute to the observed relationship.
Small changes in wording therefore carry surprisingly large assumptions.
Und
Most people will never read the methods section of an academic paper.
They encounter research through abstracts, university press releases, newspaper articles, social-media posts and headlines.
That means the title and abstract have disproportionate influence.
Wir haben also eine zunehmende Korrelation von Sozialwissenschaften mit wissenschaftlicher Verblödung.
Wie herum aber liegt die Kausalität? Oder gibt es eine dritte Größe, von der beide abhängen?
- Machen Sozialwissenschaften immer blöder?
- Oder werden immer mehr Blöde Sozialwissenschaftler?
- Oder brauchen sie einfach immer hanebüchenere Aussagen? Wissen sie vielleicht selbst, dass es Blödsinn ist, aber es bringt ihnen einfach weiter Geld und Einfluss?
- Oder waren sie schon immer einfach nur Mietmäuler und Schreibhuren der Politik, und die Bestellungen aus der Politik werden immer bekloppter?
Was mir daran jetzt gut gefällt, ist, dass sie Ratschläge geben:
The easiest defence is surprisingly simple
For ordinary readers, the research suggests a useful habit.
Whenever an article says that something “causes”, “increases”, “reduces” or “leads to” something else, ask one additional question:
How did the researchers actually know that?
If people were randomly assigned to different conditions, there may be a strong basis for causal interpretation.
If the researchers followed changes over time or exploited a natural experiment, the case may also be persuasive.
If they simply surveyed people once and discovered that two variables were related, more caution is required.
The difference sounds technical.
It is actually one of the most important distinctions in understanding research.
Science is not weakened when researchers say that two things are associated.
Sometimes that is exactly what the evidence shows.
The danger begins when a more exciting sentence quietly claims that it showed something more.
Eine interessante Regel. Immer dann, wenn jemand behauptet, dass eine Größe eine andere irgendwie beeinflusst, qualitativ oder quantitativ, die Frage stellen, wie sie darauf kommen.
Die Frage, wie die Soziologen und Genderologen darauf kommen, dass Geschlecht ein soziales Konstrukt ist, stelle ich seit 2012. Und habe bis heute keine Antwort darauf bekommen. Aber die Fakultäten, Autoren, Berater, Politiker haben Milliarden dafür bekommen, dass sie es behaupten.