The Universal & Atomic Elements of Organization
A falsifiable scientific theory proposing that the same irreducible structures organize both thought and reality — from the quantum to the social scale.
O-Theory proposes that four irreducible structures — Distinctions, Systems, Relationships and Perspectives (DSRP) — form the universal grammar of organization. Rather than being merely useful ways of thinking, these structures are hypothesized to be the atomic elements from which every organized phenomenon emerges, whether in cognition, biology, physics, mathematics, society, or the cosmos.
| D | S | R | P |
| Distinctions | Systems | Relationships | Perspectives |
| Identity ↔ Other | Part ↔ Whole | Action ↔ Reaction | Point ↔ View |
| D := (i ↔ o) | S := (p ↔ w) | R := (a ↔ r) | P := (ṗ ↔ v) |
This is a living scientific evidence compendium: an open, continually evolving collection of independent empirical research, formal theory, mathematical proofs, cross-disciplinary analyses, applications, critiques, and proposed falsifications. Every entry is included because it supports, refines, challenges, or attempts to falsify the theory.
Scientific theories are strengthened not only by evidence that confirms their predictions, but also by surviving attempts to falsify them. This compendium brings both together: independent evidence from researchers who were not testing DSRP and proposed counterexamples evaluated against the formal theory.
One counterexample is enough to falsify O-Theory. Until then, the question remains: do the same four structures organize everything from quantum systems to human thought?
Independent convergence is one of the strongest forms of scientific evidence because researchers arrive at the same conclusion while investigating different questions for different reasons.
The number is not the point. Researchers in different fields, studying different questions with different methods, repeatedly arrived at the same structural predictions—almost always without testing DSRP or using its language.
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This compendium began as the peer-reviewed literature review “A Literature Review of the Universal and Atomic Elements of Complex Cognition,” published in the Journal of Systems Thinking with 109 studies. That paper is the peer-reviewed foundation. What you see here is its living, continuously updated version . New studies are checked before they are added, and the collection now holds and keeps growing. Open any card to see what the researchers found, why it bears on DSRP, and where the original review discusses it, the fuller account.
The collection is updated continuously, so the citation carries the date you consulted it rather than a study count — the count changes weekly, and putting it in the reference would make the same collection look like a different work to everyone who cites it. To cite a single claim or study, use its own address: every one has a permanent link.
This is the adversarial half of the compendium. Where the evidence track asks what converges on DSRP, this one asks what would end it: a single organized phenomenon whose structure needs a fifth pattern, a ninth element, or a fifth structural dynamic. It holds written up from candidates across territories, and resolutions — the general answers those cases settle against. Every case is published whether it held or failed, including the ones still open.
Cite this rather than the evidence collection when the point is what survived attack. The two are separate works with separate addresses: one asks what converges on the theory, the other asks what would end it, and a reference to the first does not support a claim about the second. Case and resolution numbers change when the record is revised, so cite a case by its own permanent link rather than by number.
This collection is meant to keep growing. Send us a study, paper, book or critique that bears on DSRP, whether it supports the theory or cuts against it, and we will read it and decide whether it belongs.
Authors Hou & Dai
Year 2026
Publisher Entropy
Discipline Information Science
Read it at the publisher 10.3390/e28080872
Causal emergence (CE) is a phenomenon in which macrodynamics provide better effective information (EI) than microdynamics. The CE is widely used as the objective function in Markov aggregation. The existing works focus on deterministic aggregation, which may not offer a good solution since the search space of each step is finite. To solve this problem, we propose a sequential Markov probabilistic aggregation (SMPA) algorithm. We first express the aggregation problem as an optimization problem, then find that the EI is maximized when the transition probability matrix is a permutation matrix, and prove that the optimization problem is a nonconvex function of the probabilistic aggregation matrix. In the SMPA algorithm, the optimization problem is split into multiple univariate optimizations. Compared with the deterministic aggregation algorithm, SMPA can achieve better greedy solutions. The experimental results indicate that probabilistic aggregation generally performs better than deterministic aggregation.
Probabilistic aggregation maximized effective information when macrostate transition dynamics formed a permutation matrix, producing macro-level dynamics with greater causal effective information than the underlying microdynamics.
The study demonstrates that probabilistically aggregated macrostates can possess greater causal information than the microstates from which they are constructed.
Patterns it shows S, R
Added 2026-08-05
How to cite this Hou & Dai (2026). A Sequential Markov Probabilistic Aggregation Algorithm for Causal Emergence in Markov Aggregation. Entropy.