struggling to find good datasets and experiments on how humans reason.
Surprisingly, sharing raw data when producing publications and books was not a standard when seminal studies on human reasoning were being released from the 1980s-2000's.
Wason - Foundational reasoning study - aggregated error rates and selected reasoning excerpts, but not complete datasets.
Kahneman & Tversky - Prospect theory, heuristics and biases- only summary statistics, not raw response data.
Hutchins - Cognition in the wild - recorded full reasoning chains for navigation teams across people, tools, and charts in real-time, full process- raw observational data was never released.
Modern day research like: Alpsbench '26, Twin 2k-500 '25, Personagym '24, H-ARC '24, try to bridge this, but each is insufficient in it's own way. Specifically when requiring explicit visibility on human reasoning especially in regards to deep thinking over time.
So I had to look towards fields where a reasoning chain must be provided, publically and transparently. The legal field in particular is ripe with this information; publicly available, structured format, over time, with mechanical attributes like precedent citation, known authorship, and most importantly, multiple judges reasoning through the same case differently.
very excited.