Social tipping interventions offer an indirect way to trigger change at scale, ranging from social justice to climate change. Yet, what happens when social tipping interventions meet ordinary but ingrained group identities? To examine this, we implemented an experiment around the 2020 US election.
Our recent paper In Nature Human Behavior (https://www.nature.com/articles/s41562-022-01372-0) presents a new learning framework to precisely forecast crime in the urban environment, and simultaneously demonstrates how such precise predictors may be used to reveal signatures of enforcement biases.
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