The US has adopted more of a middle ground approach, essentially letting private companies decide what they wanted to do. Daymude and his co-authors wanted to investigate these markedly different approaches. So they developed a computational agent-based simulation that modeled how individuals navigate between wanting to express dissent versus fear of punishment. The model also incorporates how an authority adjusts its surveillance and its policies to minimize dissent at the lowest possible cost of enforcement.

“It’s not some kind of learning theory thing,” said Daymude. “And it’s not rooted in empirical statistics. We didn’t go out and ask 1000 people, ‘What would you do if faced with this situation? Would you dissent or self-censor?’ and then build that data into the model. Our mo…

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