Abstract: Online peer production communities such as Wikipedia typically rely on a distinct class of users, called administrators, to enforce cooperation when good faith collaboration fails. Assessing one’s intentions is a complex task, however, especially when operating under time-pressure with a limited number of (costly to collect) cues. In such situations, individuals typically rely on simplifying heuristics to make decisions, at the cost of precision. In this paper, we hypothesize that administrators’ community governance policy might be influenced by general trust attitudes acquired mostly out of the Wikipedia context. We use a decontextualized online experiment to elicit levels of trust in strangers in a sample of 58 English Wikipedia administrators. We show that low-trusting admins exercise their policing rights significantly more (e.g., block about 81% more users than high trusting types on average). We conclude that efficiency gains might be reaped from the further development of tools aimed at inferring users’ intentions from digital trace data.