Open research threads.

A reproducible empirical research program and live research instrument that integrates quarterly SEC Form 13F institutional holdings, official information events, and a Wikimedia Pageviews retail-attention proxy to surface transparent, non-causal candidate herding patterns for review and empirical testing.

The Epistemic Dialectic Engine research investigates how artificial intelligence can support disciplined human reasoning without collapsing uncertainty into an immediate answer. This research has now produced Aporia, a public conversational prototype that organizes inquiry through four observation lenses—Dialectic, Socratic, Reflection, and Transfer—while making assumptions, tensions, uncertainty, and the next cognitive move more visible. The current system is a research instrument under development; its cognitive indicators are exploratory rather than validated educational or psychological assessments.

The best planners rarely follow a dashboard blindly. They combine mathematics, intuition, experience, and context. This research explores whether those decision patterns can be modeled, supported, and eventually reproduced without removing the human from the process.

Organizations generate enormous amounts of qualitative knowledge: meeting notes, emails, interviews, audit findings, and conversations, which rarely influence analytical models. This research investigates whether large language models can transform qualitative evidence into measurable variables while preserving nuance and context.

Most organizations measure whether AI improves productivity. Few measure whether people actually make better decisions because of it. This thread studies how decision-support systems should be evaluated when the output is not speed, but judgment quality.