The public example-original project in the Causal Map app is a real, anonymised QuIP-style dataset. It is useful when you want to see what a busy map looks like after serious coding, and how filters change the picture. Screenshots below are exported from saved bookmarks (stable image files in this vault; open the matching bookmark in the app to reproduce the exact filter state).

Getting oriented: main factors#

A focused consequence story#

Frequency filters (links vs factors)#

Factor emphasis and zoom#

Factor Label filter and zoom contrast#

Group comparisons#

Tags on the map#

Path tracing and source tracing#

Links, bundles, and evidence#

Soft recode examples#