MSAs by the numbers

This is an early baseline — a demonstration of what evidence-based data collection can look like for MSAs, not a finished product. It’s built entirely from public Instagram posts (flyers + captions), extracted and processed by Large Language Models and linked back to each source, so everything here is transparent and verifiable.

Even at this stage it begins to surface what matters: where MSAs are focusing their energy — and where they aren’t. The mix of religious, social, charity, academic, and advocacy programming; how activity rises and falls through the year; how chapters compare. That gives MSAs a clearer basis to spot gaps, set evidence-based goals, and plan the year ahead with data instead of guesswork.

On privacy: this page is public only because it draws on information MSAs have already shared publicly on Instagram. Anything collected from MSAs directly — surveys, internal metrics, and the like — will not be shared publicly; it stays between MSLA and the MSAs it serves.