[mbuda]

Yep, amazing points!

Agree with the measures; follow-up question: what's the insight definition? I think exposing some of those measures would help people better understand what the analysis covered, in other words, how much data was actually analyzed. Maybe an additional measure is some kind of breadth (I guess it could be derived from the throughput).

"Informational leverage" reminded me of "retrieval leverage" because yeah, the scale of data didn't change, the ability to extract insights did :D

[kellkell]

Good question.

By “insight” I mean a measurable reduction in uncertainty that improves decision quality or predictive accuracy.

In practical terms, an insight could be defined as:

•A hypothesis generated and testable from the dataset

•A model parameter adjustment that increases predictive performance

•A structural relationship discovered that reduces entropy in the system representation

So compression efficiency would be something like:

(uncertainty reduced) / (data processed)

Breadth is interesting — I’d treat it as dimensional coverage: how many independent variables or graph regions are meaningfully integrated into the model.

“Retrieval leverage” is a great term. It highlights that the dataset size remains constant, but navigability and relational traversal improve — which increases effective cognitive reach.

Some of these broader ideas around informational sovereignty and anomaly-driven cognition have been explored in independent empirical work, though they’re still niche.

[mbuda]

Love it!