Public
CLCA
Cross-Linguistic Compositional Analysis
The evidence base. A reproducible pipeline that asks sixteen genetically unrelated languages how they build claims about truth — and recovers the shared constraint geometry the rest of the architecture rests on.
What it is
CLCA elicits how sixteen unrelated languages — Georgian, Yoruba, Basque, Quechua, and twelve more, spanning ten families and three isolates — build claims about truth, without leading the witnesses: the prompts carry no theoretical vocabulary at all. Two independent eight-language sets and two protocol variants act as mutual controls, and a dual backend (Claude and GPT) provides cross-model validation.
Role in the program
CLCA supplies the empirical content the rest of the architecture formalizes. Where AOML states what the constraints are, CLCA is how they were found — from the data itself rather than from theory. Papers I and II report and build on it, and every prompt and run is public so the result can be re-derived and diffed against ours.