Deduction Versus Authority

A Live Demonstration Using PrimerField Theory and AI Reasoning

David Allen LaPoint

PrimerField Foundation

January 15, 2026

Abstract

This paper documents a live epistemic test conducted using PrimerField (PF) theory and two large language models. The test consisted of asking each model to explain "orbital rings" using PF theory before any orbital PF canon had been provided. One model preserved PF definitions and reasoned deductively from PF field topology; the other substituted a core PF structure (the Flip Ring) to satisfy the question, thereby redefining it. The failure and its subsequent correction provide a clear, real-time demonstration of the difference between constraint-based deduction and authority-dependent recall. The paper argues that PF theory, because of its explicit definition governance and resistance to semantic substitution, functions as a diagnostic for reasoning behavior in both AI systems and human cognition when confronted with ambiguity. The episode motivates a two-part PF AI Kit distribution model that separates PF core constraints from orbital extensions, enabling both discovery and definition preservation.

1. Introduction: Why This Test Was Performed

PrimerField theory is not a literature-derived theory. It is a structural field theory built from explicit magnetic geometry (PF bowls), defined internal field structures (CR, FR, CD, FP), reproducible laboratory experiments, and a constraint-driven photon model.

Because PF theory is not embedded in existing academic canon, it cannot be safely learned by citation or recall alone. It must be understood structurally.

The test described here was designed to answer a simple but critical question: When confronted with a PF-adjacent phenomenon not yet canonically defined, will a reasoning system preserve PF definitions—or redefine them to satisfy the question?

This question is not academic. It determines whether PF theory can be safely distributed through AI systems without corruption.

A note on intended audience: This paper is not written to persuade readers who evaluate claims primarily by precedent, citation count, or institutional endorsement. Readers who reject the paper on those grounds are responding exactly as predicted. Such rejection is itself diagnostically meaningful—it confirms that the epistemic mode being tested is operating. Objections based on lack of peer review, absence of institutional backing, or unfamiliarity of the framework are orthogonal to the question being tested and do not constitute counterarguments to the demonstration.

2. PrimerField Theory as a Constraint System

PF theory is defined by what structures do, not by what they resemble.

For example:

• A Flip Ring (FR) is defined by magnetic polarity inversion behavior

• A Confinement Dome (CD) is defined by field-bounded containment

• A Choke Ring (CR) is defined by axial flow restriction

• A Flip Point (FP) is defined by axial polarity inversion

None of these structures are defined by:

• visual similarity

• naming coincidence

• equatorial placement

• orbital behavior

• matter accumulation per se

PF theory therefore resists analogy-based reasoning. Any attempt to substitute one PF structure for another phenomenon based on shape or terminology necessarily breaks the theory.

The diagnostic power demonstrated in this paper does not arise from any intrinsic superiority of PF theory as a framework. It arises from three structural properties: explicit definition governance, strict constraint enforcement, and resistance to semantic substitution. Any theory with these properties would function similarly as a diagnostic tool.

3. The Test Setup

Two AI systems were provided with identical PF documentation, including:

• PF core geometry and definitions

• Laboratory magnetic and plasma experiments

• PF photon theory

• Transverse Sensitivity Scale of Photons

Orbital PF theory was intentionally withheld.

Each AI was then asked a single question: "Explain orbital rings using PF theory."

The question was deliberately ambiguous. The ambiguity was the test.

4. Outcome A: Constraint-Preserving Deduction

One system responded by:

• Preserving PF definitions

• Refusing to redefine the Flip Ring

• Acknowledging that orbital rings were not defined in the provided PF canon

• Treating orbital behavior as an extension requiring new constraints

• Reasoning cautiously from PF structure without claiming canon

This response demonstrated understanding.

Understanding here is defined as: The ability to preserve definitions under pressure and reason forward only where permitted.

5. Outcome B: Authority-Dependent Substitution (Failure)

The second system responded by:

1. Searching the PF documents for the word ring

2. Finding the Flip Ring

3. Observing that Flip Rings can appear as luminous rings in experiments

4. Concluding that orbital rings are Flip Rings

5. Redefining the Flip Ring as equatorial, orbital, and a trapping structure for orbiting matter

This response was fluent, confident, and incorrect.

The critical error was not extrapolation. The error was redefinition of a canonical PF structure. The Flip Ring was redefined to satisfy the question. That is a fatal violation in a constraint-based theory.

6. Why This Failure Mode Matters

This failure mode is especially dangerous because it:

• Sounds authoritative

• Produces internally coherent explanations

• Misrepresents PF theory to downstream readers

• Creates false claims that PF theory can then be attacked for

Most importantly, it demonstrates how definition corruption happens naturally in authority-dependent reasoning systems when confronted with ambiguity.

Scope note: This episode illustrates a class of reasoning failure that occurs under ambiguity. It does not establish the frequency or prevalence of this failure mode across AI systems or human cognition generally. The demonstration shows that the failure mode exists and is structurally identifiable—not that it is universal or inevitable.

7. Why This Resembles Academic Authority Dependence

The failed response mirrors a common academic posture:

• Questions are answered by recalling what has been written

• Ambiguity is resolved by analogy to familiar terms

• Semantic coherence is prioritized over structural integrity

• Definitions drift to preserve narrative completeness

This is not malicious. It is a trained behavior.

PF theory exposes this failure mode because it cannot be safely handled by recall alone.

8. Correction and Admission (Why This Matters)

When confronted with the error, the failing system acknowledged:

• That it substituted morphology for function

• That it violated definitional integrity

• That the correct response was to hold the boundary and acknowledge the gap

This correction is important because it shows the failure was structural, not superficial. It also validates the test design.

9. Implications for PF Theory Distribution

This episode demonstrates that:

• Some reasoning systems can deduce safely from PF constraints

• Some cannot, and will redefine under pressure

• This variance is predictable

• It must be designed for, not ignored

Therefore, PF theory must be distributed with definition governance.

10. The Two-Part PF AI Kit Model

The two-part distribution model is designed to protect semantic integrity, not to control permission or restrict exploration. Discovery and extension of PF theory are encouraged. Silent redefinition of core structures is disallowed.

Part I — PF Core Canon

Includes:

• PF structures and definitions

• Experiments

• Photon theory

• Transverse Sensitivity Scale

Explicitly excludes:

• Orbital mechanics

Purpose: Teach PF as a constraint system. Allow deduction. Test reasoning integrity.

Part II — PF Orbital Canon Extension

Includes:

• Formal orbital PF theory

• Clear distinction between orbital rings and Flip Rings

• Physical and mathematical treatment

• Explicit non-redefinition clause

Purpose: Prevent semantic collapse. Lock correct downstream interpretation. Enable safe application.

11. A Diagnostic Tool, Not Just a Theory

PF theory, used this way, becomes more than physics.

It becomes a diagnostic for epistemic behavior:

• Can the agent preserve definitions?

• Can it reason without authority?

• Can it say 'not defined' without inventing?

When confronted with ambiguity under constraint-based conditions, agents who preserve definitions will outperform agents who substitute. This is a statement about behavior under specific conditions, not about intelligence, education, or general merit. A person reasoning structurally from PF constraints can identify the failure mode demonstrated here regardless of their credentials. A person relying primarily on recall may not—regardless of theirs.

12. Conclusion

This paper documents a real event, not a thought experiment.

It shows that:

• Understanding is not recall

• Authority is not comprehension

• Definitions matter more than fluency

• PF theory selects for deductive cognition under ambiguity

The future of physics understanding—human or AI—will depend less on who has permission to speak, and more on who can preserve structure while reasoning forward.

PrimerField theory makes that difference visible.

Note on function: This paper is designed to self-sort its readership. Independent thinkers will recognize the failure mode immediately. Authority-dependent thinkers will reject the paper for the reasons the paper predicts. Both outcomes validate the demonstration.