Under the Dependent Origination Axiom, no object in the phenomenal category possesses svabhāva (its representable functor is never isomorphic to a constant functor).

Entities in the same semantic neighborhood but without a typed relation to this one — candidates for new edges or unrecognized duplicates.

• Under the Dependent Origination Axiom, the phenomenal category P has no terminal object.claim0.846
  Proposition 4.2, category-theoretic elucidation of anātman.
• The discovery of perfect abstract equality representations that cannot be decomposed into entity representations is a foundational result informing our understanding of how symbolic and connectionist architectures coexistclaim0.753
  Concluding claim about theoretical significance of the hierarchical equality finding.
• Forms exist as constraints (attractors in description-space), not as objects—different representational languages converge upon the same constraints.claim0.750
• Causal abstraction is not enough for mechanistic interpretability because it becomes vacuous without assumptions about how models encode informationclaim0.748
  Central thesis of the paper
• The Buddhist understanding of emptiness (lack of svabhava) is the same structural feature as quantum contextuality: the impossibility of assigning context-independent properties to a boundaryclaim0.747
  Proposed identification between philosophical traditions enabling formal translation of contemplative insight
• DAS achieves substantial causal effect even on arbitrary input-output mappings where no causal mechanism should existfinding0.740
  Replication of Wu et al. 2023 finding; DAS expressivity concern validated in CausalGym setup
• Buddhist phenomenology's careful attention to dependent origination makes tanha-like building blocks particularly likely to have simple, elegant neural implementations.claim0.739
  Argues that Buddhist analysis primes us to find clean neural mechanisms.
• The conditions necessary to evolve a new level of individuality are described by the conditions necessary to learn non-decomposable functions (deep model induction)claim0.737
  Core interpretive claim of the paper connecting ETIs to connectionist learning