Consciousness-Like Structural Regimes as Constraint-Driven Emergence
Bibliographic record
Abstract
This paper establishes a formal framework for analyzing consciousness-like structural regimes as emergent properties of recursive symbolic systems operating under constraint. It defines consciousness not as subjective experience or agency, but as a specific structural pattern of persistence observable in systems capable of recursive self-modeling. Abstract Summary The framework integrates tools from dynamical systems theory, information theory, and non-equilibrium physics to identify the operational criteria for why certain symbolic structures persist while others collapse. By treating persistence, coherence, and identity as structural outcomes of constraint-driven self-modeling, the model yields falsifiable predictions and a substrate-independent account of cognitive architecture. Core Components • Formal Definitions: Defines symbolic systems \bm{S=(X,R)} and characterizes "admissibility" through constraints \bm{\mathcal{C}} that represent entropy bounds and resource limits. • Axiomatic Foundation: Provides four core axioms: Constraint Survival, Entropic Pressure, Recursive Stability, and Identity as Invariance. • Structural Regimes: Formally defines a consciousness-like regime (\bm{S \in \mathcal{CR}}) based on its ability to preserve internal representations and resist entropic perturbation. • Metaphysical Reframing: Reframes traditional metaphysical terminology—such as Soul, God, and Faith—as structural shorthands for limit behaviors and symbolic invariants. • Falsifiability: Outlines five explicit conditions under which the framework would fail, ensuring empirical and computational testability. Key Contribution The work dissolves mind-body dualism without resorting to computational essentialism by demonstrating that if two symbolic structures are isomorphic and satisfy identical constraints, their physical implementation is irrelevant to their persistence.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.007 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".