I've spent the past month digitizing Thomas Bullard's 1987 UFO abduction taxonomy — 550 motif codes across 270 cases — into a queryable relational database. Bullard himself has been corresponding with me about the methodology. The original work catalogued narrative elements across abduction accounts: what beings look like, what examinations involve, what messages are delivered, what aftereffects persist. Bullard found remarkable consistency across cases that had no contact with each other. But his data lived in two out-of-print volumes that almost nobody has read. So I built a pipeline. The database now holds 5,570+ sequenced events. Each event maps to a specific motif code from Bullard's taxonomy — tagged with source citation, page number, and sequence position. Here's where it gets interesting. I'm now running John Mack's clinical case studies through a blind extraction engine. The AI has never seen Bullard's coding for these cases. It receives the raw chapter text with no dates, no investigator names, no cultural context — and extracts motif events against the taxonomy. The narrative structure holds. The motif distribution from Mack's cases maps onto Bullard's corpus-wide baseline with predictable, explainable deviations. The consistency Bullard found by hand in 1987 survives automated extraction from a completely independent clinical source written seven years later. I'm not making ontological claims about the phenomenon. This is computational folkloristics — testing whether consistent narrative structures exist across encounter accounts spanning different cultures, time periods, and investigator methodologies. The answer, so far, is yes. The database is called the Mack-Bullard Matrix. Happy to answer questions about the methodology, the findings, or Bullard's taxonomy itself. submitted by /u/eurydicewrites [link] [comments]