Near-Death Experience (NDE) Research Cluster
concept
Serious university scientists have documented that up to a quarter of people who nearly die report the same vivid experience.
Who they are
The Near-Death Experience (NDE) research cluster — top-tier academic study of consciousness during clinical death.
What they do
The engine treats it as the highest-quality peer-reviewed body of work on non-ordinary experience (after the Stargate remote-viewing program).
How it works
Key researchers include Bruce Greyson (University of Virginia, who created the Greyson NDE Scale in 1983), Sam Parnia (NYU Langone, AWARE cardiac-arrest studies), and Pim van Lommel (a 2001 Lancet study), with roughly 10-25% of cardiac-arrest survivors reporting NDE experiences across studies.
Why it matters
The engine is careful to draw a line: this consistency is a real, repeatable observation, but it is NOT proof of consciousness surviving death — though it notes the reported beings (Beings of Light, Guides) resemble those described in DMT and channeling experiences.
The engine's record — word for word
Tier-1 academic research on consciousness-during-clinical-death. Primary researchers: Bruce Greyson (Univ Virginia, Greyson NDE Scale 1983, 'After: A Doctor Explores What Near-Death Experiences Reveal About Life and Beyond' 2021), Sam Parnia (NYU Langone, AWARE / AWARE-II multi-center cardiac arrest studies), Pim van Lommel (Lancet 2001 'Near-death experience in survivors of cardiac arrest: a prospective study'), Pat Fenske, Jeffrey Long (NDERF database). Tier-2/3 boundary: Eben Alexander 'Proof of Heaven' (2012). Engine relevance: HIGHEST-TIER peer-reviewed corpus in non-ordinary-communication ecosystem AFTER Stargate. Phenomenological consistency: ~10-25% of cardiac-arrest survivors report NDE phenomenology across studies. Hyperreal-claim distinction critical: phenomenological consistency ≠ ontological claim about post-death consciousness. NDE entity-class (Beings of Light, Guides) maps onto DMT entity-class + channeled-entity-class typology — cross-cluster convergence finding.
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