HMN 2026: How We think norms spread by imitation, but one deceptively simple rule tells a more human story

A paper appearing in Proceedings of the National Academy of Sciences offers a strikingly simple answer to a longstanding question: How do people learn and settle on shared social conventions, from everyday habits to workplace norms? Researchers from the CUNY Graduate Center, the University of Pennsylvania, and Stanford University have found that people do not primarily learn by copying others or by calculating the most likely choice. Instead, they follow a two-stage process—sampling behaviors at first, then committing once enough evidence accumulates.

The Tolerance Principle goes social

The study shows that this shift is governed by a simple mathematical rule known as the Tolerance Principle, which predicts when people have seen enough regularity to treat a pattern as a rule despite some exceptions. Originally developed to explain how children learn the grammar of their native language, the researchers found, it also predicts how adults adopt shared behaviors—and even how competing norms can overturn one another.

“People often assume that social learning is about imitation or careful optimization,” said Spencer Caplan, Linguistics professor at the CUNY Graduate Center and co-lead author of the study. “What we found is something more basic and more human: People explore different options, but once a pattern crosses the threshold of ‘good enough,’ they commit to it—and stick with it even when there’s some conflicting evidence.”

Inside the coordination experiments

To study how conventions emerge, the researchers built computational models of different learning strategies and evaluated them against data from coordination experiments—including previously published studies as well as a new set of experiments the team conducted. In these experiments, participants had to independently align on shared choices—such as agreeing on a name for an unfamiliar face—while interacting in social networks. Participants received small rewards for matching others’ responses, allowing researchers to track how decisions evolved over time.

Across multiple experiments, people consistently deviated from the two dominant theories of social learning. They did not simply copy the most recent behavior they observed, nor did they always choose the statistically optimal option. Instead, they behaved probabilistically at first, reflecting uncertainty, and then made a decisive shift once their accumulated experience crossed a mental threshold.

A simple rule beats complex models

That threshold is precisely captured by the Tolerance Principle: a simple equation that helps explain when people decide they’ve seen enough consistency to treat something as a rule even if there are a few exceptions. The model not only better matched how people actually learn, but also outperformed competing approaches, including Bayesian models, in predicting human behavior in controlled experiments.

The findings suggest that a single cognitive mechanism may underlie how people learn across domains, from language to social norms. Just as children learn to say “walked” and “talked” but also know that “went” is the past tense of “go”—applying a general rule while tolerating exceptions—adults appear to adopt conventions in a similarly rule-based way once they reach a point of sufficient evidence.

Implications for social change

The research also sheds light on how social change happens. Because the model predicts when people commit to a convention, it can also estimate how large a dissenting minority needs to be to overturn it, offering new insight into tipping points in collective behavior.

“These results give us a clearer picture of how norms spread, stabilize, and sometimes flip,” Caplan said. “That has real implications for everything from public health campaigns to organizational culture to how new ideas take hold in society.”

The authors note that future work will examine how these dynamics play out in more complex, real-world settings, where social conventions are shaped not just by coordination but also by factors like identity, status, and power.

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