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.
Try a different term or clear the filters.
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 Gauthier and Tarr
Year 1997
Publisher Vision Research
Discipline Cognitive Science
Read it at the publisher 10.1016/s0042-6989(96)00286-6
Sensitivity to configural changes in face processing has been cited as evidence for face-exclusive mechanisms. Alternatively, general mechanisms could be fine-tuned by experience with homogeneous stimuli. We tested sensitivity to configural transformations for novices and experts with nonface stimuli ("Greebles"). Parts of transformed Greebles were identified via forced-choice recognition. Regardless of expertise level, the recognition of parts in the Studied configuration was better than in isolation, suggesting an object advantage. For experts, recognizing Greeble parts in a Transformed configuration was slower than in the Studied configuration, but only at upright. Thus, expertise with visually similar objects, not faces per se, may produce configural sensitivity.
How does facial recognition work in the brain?
The "expert" group (the ones with longer and more productive exposure to the distinctions) had a faster response time and slightly more accurate results on average.
Purposefully "training" yourself to make distinctions increases the speed at which you can distinguish identities and the accuracy with which you make those distinctions.
Gauthier and Tarr 1997 worked with computer generated things called “greebles.” These were created in order to test different aspects of facial recognition processes in humans. In their experiment, they worked with 32 Yale University undergraduates. They generated 60 of the “greebles”, which are organized into five families and two genders based on the physical configuration of the generated greeble.
Each individual is unique, even though some might look as if they are quite similar. 30 of the generated greebles were used in the expertise training, while 24 of the unused ones were used for both the novice-level and expertise-level test phases. They designated “nonsense words” to call the five families,
two genders, and each individual greeble. 16 of the participants were “experts” and 16 were “novices.” The novice test group were only given the names of the 3 greeble parts: boges, quiff, and dunth.
No extra training was given to the novice group. They then were shown 6 novel greebles with a quick flash of their names (1 second) for 36 trials. Afterwards, the participants were given a forced-choice recognition of the parts. This was done in the form of a greeble’s name and part was shown on the screen (e.g. Pimo’s Boges) and the participants were asked to identify the part. There were three conditions for this test:
1. “Studied-configuration: the two choices were the specified part and a foil part, both in the context of the Greeble specified in the prompt; 2. Transformed-configuration: the two choices were of the specified part and a foil part, both in the context of the Greeble specified in the prompt but with the top parts moved 15 deg towards the front; 3. Isolated-part: the two choices were of the specified part and a foil part, both in isolation on the screen.”
The same procedure was done with inverted greebles afterwards. If the participants were in the “expert” test group, then they were given extensive training to make them experts at greeble recognition. This was done by having them practice greeble recognition at the family, gender, and individual levels with 30 different greebles. They then had to do 60 trials in which they verified their experts status by labelling novel greebles. The participants did 360 randomized trials where their response time and accuracy was collected. On average, those in the expert category responded more accurately and faster than those in the novice groups. Their results indicate that the more exposure one has to fine-tuned and novel distinctions, the better they will be at recognizing them. This is significant for the universal patterns of thought as it implies that the more aware that one is of the Distinctions around them, the more accurate and quick they will be at recognizing and thinking with them.
Patterns it shows D
How to cite this Gauthier and Tarr (1997). Becoming a “Greeble” Expert: Exploring Mechanisms for Face Recognition. Vision Research.