by Guilherme Antonio Calabria Bayma Costa
When I took on the coordination of the Public Policy Evaluation and Data Science Unit (NAPCD) at Recife City Hall in 2021, one of the biggest challenges was to thoroughly understand the impacts of the Compaz Network, a community center policy aimed at preventing violence and promoting social inclusion. In 2022, we had the opportunity to carry out an executive participatory evaluation with the support of Clear Lab, which allowed us to strengthen the culture of evidence-based decision making in municipal management.
Cities around the world, including many in Latin America, are incorporating artificial intelligence solutions into their urban services: video surveillance and facial recognition systems for public safety, traffic management, citizen services, waste collection and tourism promotion.
In contexts of urban vulnerability, evaluation is never neutral. Every evaluation reflects a way of seeing reality, deciding what counts as a problem, what is considered an achievement, and who gets to interpret it. From this perspective came the article 
When we set out to evaluate Co-Inspira, a peacebuilding initiative in Colombia, we knew we were facing an unconventional challenge. This was not about assessing a traditional intervention, but something far more complex: a Systemic Action Research (SAR) process that was, in itself, already a collective exercise in knowledge generation.
I’m genuinely delighted to share a personal take on Chapter 7: Participatory evaluation of a public transport support policy: an inclusion and transformation perspective – Jalisco (Mexico), recently published in the book Evaluation, Democracy and Transformation: Experiences of Participatory Evaluation in Latin America. I co-wrote it with Sugey Salazar and Selene Michi, and together with other colleagues we reflect on what it really means to carry out public policy evaluation using participatory approaches from within the public sector.
In 
When I wrote 
Outcome Harvesting is a participatory method used to identify, formulate, analyze, and learn from the changes brought about by an intervention, especially when cause-effect relationships are complex or unknown.