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.
Cabrera, Derek, 2026, Journal of Systems Thinking — Cognitive Science
Patterns: Distinctions, Systems, Relationships, Perspectives
Our reading: this one does something the containment papers do not. Those decompose an existing formalism; this measures a quantity – the gap between the organization a reasoner uses and the organization it reports – and shows the gap is real and sizable in systems whose reasoning can be interrogated directly. It also gives the DSRP program a mechanism for a familiar complaint about definitions: a dictionary definition captures a fragment of an identity, so specifications built on definitions produce ambiguous records, brittle classifications, and interoperability failures, which is the same gap the UML and network runs found formalisms paying for in workarounds. The nonce-term manipulation is the load-bearing methodological move: swapping vorg for leadership changes only the information, so anything that survives the swap is organization.
Answers tracked the supplied organization rather than the definition: GPT matched it at .84 to .86, Claude at 1.00. Identities with identical structure counts but different structures produced disjoint answers, so which structures exist matters and not merely how many. Removing a Pattern removed the answers that Pattern supported. Changing one identity altered inferences about neighboring identities. Across 1,440 unidentified cases neither model collapsed unknown into false, so the three-way affirmed / negated / unidentified status survived. Dark matter was measured directly as the gap between operative and reported organization: GPT used .86 of the identity while reporting .25. Claude showed almost no gap while instructed to use only the supplied material, and once that instruction was removed reported mainly the definition while continuing to use the wider identity. With only a definition and familiar terms, GPT built a road-vehicle identity for vorg out of nothing supplied; rewriting the same world in nonce terms made that imported structure disappear. Cabrera concludes that identity behaves as an organized field of what is, is not, and remains unknown, that the field extends past what was explicitly given, and that the same machinery supports disciplined inference when visible and unsupported assumption when it is not.
Defines the identity of a thing in a model as its full assembled DSRP structure – what it is and is not, contains and belongs to, relates to, and is framed by – and defines cognitive dark matter as the organization a system uses but does not report, CDM = O minus I(O). Then tests both constructs empirically on large language models using an invented identity whose definition is held fixed while the surrounding organization is varied.
Formal apparatus: CI(X|C) is the set of DSRP structures involving X that are affirmed, expressly negated, or unidentified in context C at time t. The count signature N(X|C) is a four-by-three matrix, Patterns by status, and the worked vorg example yields 14 affirmed, 10 negated, and 4 unidentified across 28 possibilities. Cognitive dark matter is CDM = O minus I(O), the operative organization less the reported organization. Study design: an invented focal identity, vorg, with a fixed definition, embedded in a surrounding organization built from nonce terms (greeb, tandra, draye), then rewritten with familiar terms (leadership, management, influence) holding structure constant, and probed with questions the definition alone cannot settle. Two model families, GPT and Claude. Semantic blinding is used as an epistemological instrument: because only the information changes when nonce terms are unblinded, the technique separates organization a model uses, organization it reports, and organization it supplies without knowing it did. Cabrera's stated limitations are unusually careful and worth keeping: the theory specifies the structure of Organization, not the neural format implementing it, so the machine results test organizational claims and are not evidence about brain implementation; the report-use discrepancy measures the presence of dark matter but does not by itself establish that unreported structure caused a particular judgment, since a changed mind, a misunderstanding, a strategic answer, or reorganization during elicitation remain live alternatives; a failed behavioral prediction could mean a missing structure or a mischaracterized one; and the advanced Is/Is Not operation exposes a discrepancy without guaranteeing that the first explanation offered for it is right.
What is a thing? We propose that its identity in a model is the organized account of what it is and is not, what it contains and belongs to, what it relates to, and how it is framed: its DSRP structures – Distinctions, Systems, Relationships, and Perspectives – constitute its contextual identity. Cognitive dark matter is the Organization a system uses that is absent from its own account of itself: CDM = O - I(O). We tested these constructs in two large language model families using an invented identity, vorg, holding its definition constant while varying the surrounding Organization and asking questions the definition left unresolved. The supplied Organization, not the definition, determined the answers: GPT matched it at .84-.86 and Claude at 1.00; identities with the same structure counts but different structures produced disjoint answers; removing a Pattern removed the answers it supported; changing one identity altered inferences about neighboring identities; and neither system collapsed unknown into false across 1,440 unidentified cases. Taken together, the findings show that identity behaves as an organized field of what is, is not, and remains unknown, and that this field can extend beyond what is explicitly supplied. With only a definition, GPT built a road-vehicle identity for vorg from familiar terms; when the same world was rewritten with nonce terms, that imported structure disappeared. Cognitive dark matter was therefore measurable as the gap between operative and reported Organization: GPT used .86 of the identity while reporting .25, whereas Claude showed little gap until the instruction "use only the supplied material" was removed, after which it too reported mainly the definition while continuing to use the wider identity. Perspective thus changed both what Organization entered the task and whether the Organization doing the work remained visible. The same structural machinery supported disciplined inference when visible and unsupported assumption when it was not. In real-world judgment, this means that what people or machines conclude can depend less on the information in front of them than on the unreported Organization through which that information is being interpreted.
These researchers were not testing DSRP. The finding is theirs; the correspondence to DSRP is drawn by this site.