This paper uses a quasi-randomized field experiment in Zimbabwe to understand the impact of a large-scale intervention targeting community attitudes. I measure the impact that the program has had on attitudes, the behaviour of teachers and caregivers, and the learning and progression outcomes of at-risk youth. The quantitative survey and learning assessment data I use for this is complemented by transcripts from focus groups and interviews, which I analyze using innovative text mining methods to measure changes in community sentiment towards marginalized groups. I find that the program improved community attitudes toward girls’ education by 0.403 SD over the three and a half year project. This contributed to a 20.9 percentage point increase in the likelihood that students in the treatment group reported receiving enough support from their community to continue learning during COVID-19 school closures, along with other changes in the behaviours of community members and families. The program facilitated better learning and progression outcomes, with marginalized students performing 0.28 SD better on learning assessments after the project. These findings lead to two important conclusions about the efficacy of interventions designed to reshape community attitudes. The first is that community attitudes can be influenced in a relatively short time to become more supportive towards marginalized groups. The second is that these interventions can support education outcomes. This paper also demonstrates the usefulness of qualitative methods and text mining techniques for future experimental work.