The irreducible epistemic atoms underlying the curriculum. 4,828 atoms across 8 types and 2 molecules
Meaning is constructed by receivers using their own mental models rather than transmitted intact from senders, because information contains no inherent meaning—meaning emerges from the interaction between information and context.
No human has direct access to reality; all knowledge is mediated through neurological processing and linguistic abstraction layers that filter and structure experience.
Knowledge is actively constructed by learners through engagement with experience, not passively received as transmission from external sources.
All demonstrative knowledge ultimately rests on indemonstrable first principles that cannot themselves be proven through demonstration.
Before forcing resolution of contradictory observations or beliefs, accumulate multiple instances in a contradiction log to enable pattern detection impossible from individual contradictions.
When a question receives a partial answer, preserve the original question as a persistent atom and link the answer to it rather than replacing the question, creating a visible record of how understanding evolves from open inquiry to accumulated evidence.
Distinguish domain-specific facts (treatment protocols, software frameworks, market conditions) requiring aggressive temporal updating from structural principles (logic, mathematics, core psychological mechanisms) where age indicates Lindy-tested robustness, applying opposite update strategies to each type.
For information arriving through multiple transmission steps (forwarded quotes, summarized studies, dashboard metrics), multiply the confidence value at each transmission step rather than treating endpoint confidence as equal to source confidence.
For each schema driving consequential decisions, document: (1) the schema as a sentence, (2) when you adopted it, (3) supporting evidence, and (4) what would falsify it — if you cannot articulate falsification conditions, treat the schema as dogma requiring immediate audit.
Store each schema with explicit scope documentation specifying the domain where it was built and the structural conditions it assumes, treating scope as mandatory metadata rather than optional annotation.
When someone proposes a different categorization and your first reaction is irritation that they are 'wrong,' treat this as a signal that you have mistaken a constructed category for an objective feature of reality.
Treat a validation log with no disconfirmations as a warning signal of selective documentation rather than validation success, because unbiased testing inevitably produces some surprises.
Before attempting to resolve any contradiction between beliefs, construct the strongest possible version of each side that the most informed advocate would recognize and endorse.
When evaluating confidence in a belief, count only genuinely independent lines of evidence—sources that do not share origins, methods, or assumptions—rather than total source count, because correlated sources compound confidence on a single foundation.
When adjusting a schema after disconfirming evidence, require the adjustment to generate new testable predictions rather than merely explaining away the original failure.
When using indirect evidence, assess whether indicators are genuinely independent by checking if they could agree for reasons other than the schema being true—if all evidence shares a common causal source, it counts as single evidence despite multiple data points.
Reformulate validated schemas with explicit boundary clauses that specify the conditions under which they were tested and the conditions under which they remain untested.
Accumulate anomalies (observations that don't fit the schema) in a running list and trigger full schema review when the count reaches a pre-defined threshold, rather than treating each anomaly as requiring immediate action.
When your schema can no longer formulate the questions you need to ask about a domain, treat this incommensurability as a signal that the framework itself has become a cage requiring replacement.
Treat any schema that has gone six months without deliberate review the same as a software dependency unupdated for six months - not necessarily broken but requiring verification before continued reliance.
Measure personal development quality by asking whether any practice changed a schema's structure or merely added information to existing schemas - structural change is genuine growth, information addition is not.
When a schema cannot specify any observation that would falsify it, classify it as a belief system rather than a testable model and flag it for replacement or constraint.
For each schema you operate on, document source provenance in a single field—specific person, book, cultural norm, direct experience, or unknown—then prioritize verification effort by source weakness.