Skip to main content

People Prefer Reductive Explanations

Readers favor a certain explanatory style when learning about complicated scientific topics, according to a study published in the journal Cognition by University of Pennsylvania researchers. Deena Weisberg, a senior fellow in the psychology department at the School of Arts & Sciences, philosophy graduate student Jordan Taylor and former postdoc Emily Hopkins found that people prefer descriptions with information from more reductive scientific fields, even when those details aren’t relevant to understanding the finding.

One way people make a complex idea clear is to break it down into basic, digestible chunks. “If I’m trying to talk about how a car works,” Dr. Weisberg said, “I have to stop talking about the whole car at a certain point and instead, start talking about its components and how they work together.”

Similarly, Dr. Weisberg said, people prefer clarifications that separate findings into smaller parts or refer to more fundamental processes, otherwise called reductive explanations.

Drs. Weisberg and Hopkins partnered with experts across the university to write a series of explanations for scientific topics looking at two variables: quality of explanation, or good versus bad, and whether reductive information was included versus not included. “Good” explanations detailed a phenomenon well, while “bad” ones lacked certain relevant information to understand that phenomenon’s occurrence. “Reductive” ones included extra information from a more reductive field, such as explaining how a cell behaves biologically by referring to its internal chemistry. “Non-reductive” explanations used only evidence from a single science, for instance, talking about how the cell’s biological behavior works with the rest of the biological system. Critically, the reductive explanations did not add any information necessary to grasping the phenomenon.

Study participants, which included Penn undergraduates and a sample of people recruited through a crowdsourcing website, received explanations that used different combinations of variables, reductive good, reductive bad, non-reductive good and non-reductive bad, then rated how satisfied they felt with each type of explanation.

The researchers found across all sciences, participants showed a significant bias for reductive details, rating good descriptions that used reductive information higher than those without reductive information. The same held true for logically flawed explanations.

“It’s not like their compass for judging information is entirely broken in any sense,” Dr. Weisberg said. “The strongest and most consistent finding is that they can tell between good and bad. The good ones are always better than the bad. Within that, you get a bump for the reductive explanation.”

The findings may have ramifications for how science is taught, according to Dr. Weisberg.

“Most college undergraduates are not going to be professional scientists,” she said, “but they are going to be consumers of science, people who are using it in some way in their daily lives.” 

In future research, Drs. Weisberg and Hopkins said they plan to investigate whether and how other factors like graduate studies or a general knowledge of scientific practices can reduce this bias.  

Back to Top