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Thanks for the discussion this morning!
Much to my regret, I didn't hear the Yuva Centre presentation - my speciality is monitoring and evaluation so this is a topic of particular interest! I did see the presentation beforehand and thought it raised some fascinating issues.
I think involving users in qualitative data analysis is relatively straightforward. We understand and use language all the time, and there are a number of methodologies designed to involve stakeholders in qualtiative analysis. Most Significant Change is one example; this involves collaborative decision-making about which changes from a project are the most example. See here for more information: https://www.betterevaluation.org/en/resources/guides/most_significant_change
Collaborative quantitative data analysis is much more difficult. Quantitative analysis is quite a specific skill, and much more often done individually, compared to qualitative analysis. I would love to hear some examples of this!
Yes, participatory data analysis can feel a step too far for some CSOs, but perhaps a more accessible way of looking at it is to involve participants and other stakeholders in sense-checking your findings. As Adam says, quantitative analysis is usually a solitary activity but asking people whether the statistics ring true for them is an interesting way to bring people back in to the conversation. If the data doesn't represent their experience, you can start asking those 'how' and 'why' questions.
From memory @duncanshallard-brown implied (with a shaky yes/no hand!) that Prisoners Abroad has some ways of involving its clients after initial data collection... We didn't have time to get into the specifics in our break-out room, but do share any points of interest here Duncan if you have a second
Wonder whether @aditya kumar, @bunita and others from Cape Town might have anything to share on this? Lots of work on mapping, enumerating, profiling areas with communities - how/do you involve people beyond this initial data collection phase?