Original Reality Theory
Original Reality Theory

An Investigation in Progress

Under Development

1. Introduction

Original Reality Theory (ORT) is a research proposal devoted to developing a conceptual framework capable of describing reality in terms of fundamental principles common to a wide range of phenomena.

It did not originate as an attempt to create an alternative to existing theories, but emerged from a long process of inquiry that began with the author’s own experience. This process started with systematic observation of the author’s own mind: seeking to understand how thoughts arise, how interpretations are constructed, how they can be changed, and how different ways of perceiving reality alter one’s understanding of the world.

Throughout this inquiry, the hypotheses developed were continually examined in light of knowledge from fields such as neuroscience, psychology, anthropology, sociology, history, physics, biology, systems theory, and other disciplines. The aim was never to confirm a personal intuition, but to keep it in ongoing dialogue with existing knowledge.

Along the way, it became clear that several theories seek an integrated understanding of reality. These include, for example, General Systems Theory, Complexity Theory, Cybernetics, Information Theory, and various contemporary efforts toward unification in physics. Original Reality Theory acknowledges the importance of these contributions and identifies areas of overlap with many of them.

However, Original Reality Theory does not propose to replace these theories or compete with them. Nor does it begin from the assumption that current knowledge is mistaken. On the contrary, it seeks to learn from that knowledge, engage with it, and use it as a reference for developing its own conceptual framework.

Its central hypothesis is that different fields of knowledge may represent distinct abstractions of the same reality. The inquiry seeks to determine whether there is a conceptual framework fundamental enough to integrate these different perspectives without erasing their distinctive features.

The theory is currently undergoing formalization. Its conceptual architecture is already established, but publication requires ongoing revision, refinement of terminology, logical organization, and demonstration. Part of this process involves developing mathematical formalizations intended not to replace conceptual language, but to express certain relationships rigorously wherever possible.

For this reason, the articles and essays published on this site do not constitute a complete exposition of the theory. They present reflections, analyses, and applications developed from concepts that form part of Original Reality Theory and are still being organized for publication.

This space will document that evolution. As the theory takes more consolidated form, its foundations, concepts, demonstrations, and possible applications will be published progressively, enabling readers to follow its development and, above all, to evaluate it critically in light of the theory’s own internal logic and the available scientific knowledge.

2. Original Reality Theory: Foundations and Method of Analysis

2.1. What Is Original Reality Theory?

To know is to differentiate reality and combine its differences into information. To abstract is to follow the reverse path: progressively eliminating information by reducing conceptual differences.

The theoretical limit of the construction of knowledge is total differentiation. The theoretical limit of abstraction is the absence of differentiation and, therefore, of information. In Original Reality Theory (ORT), Original Reality corresponds to this second limit: a reality without any differentiation, perspective, interpretation, or representation of it.

Original Reality, therefore, cannot be fully known. To know it is already to differentiate it.

The moment something is distinguished from something else, a difference arises. Perceiving and differentiating, in this sense, constitute the same phenomenon, even though they may be separated conceptually for explanatory purposes. There is no perception without difference, because perceiving something necessarily means distinguishing it.

From this differentiation, interpretation and representation become possible. What was conceptually undivided becomes divided into distinguishable elements, which can then be related and combined. Information arises from these combinations.

Perceived, interpreted, and represented reality therefore no longer corresponds to Original Reality at its theoretical limit. It constitutes a derived reality.

This distinction between Original Reality and derived reality is itself also a derivation. The concepts of “Original Reality,” “derived reality,” “differentiation,” “information,” and all other concepts used by ORT are representations. The theory necessarily operates within a derived reality in order to formulate conceptually that which, at its limit, would no longer admit any conceptual formulation.

For this reason, Original Reality is not an object that ORT seeks to reach or fully know. It functions as a theoretical limit of abstraction.

We can represent it by means of a conceptual scale.

At one end would be maximum differentiation: the growth of the distinctions, concepts, interpretations, representations, and information through which a derived reality becomes progressively more complex.

At the opposite end would be maximum abstraction: zero differentiation and, consequently, zero information.

This zero point corresponds conceptually to Original Reality.

The extremes of this scale are theoretical limits. The ORT method necessarily operates between them.

2.2. The ORT Method

If knowing means differentiating and constructing information from differences, abstracting means making the opposite movement.

The ORT method consists of progressively deconstructing conceptual differentiations, moving the analysis toward the limit of Original Reality without assuming that this limit can actually be reached.

As differentiations are removed, phenomena that initially seemed distinct may begin to reveal common structures. Distinctions necessary at a given explanatory layer may disappear when the analysis reaches a more abstract layer.

Abstraction, in this sense, does not add information. It reduces it.

To abstract means to know less at that scale of analysis: to remove details, categories, concepts, and divisions that previously made it possible to differentiate one thing from another. The purpose of this reduction, however, is not simply to destroy knowledge.

Deconstruction is followed by reconstruction.

Human knowledge reaches the individual, to a large extent, already structured. Concepts, categories, explanations, and fields of knowledge are received as constructions already made. The individual can learn these constructions and use them without necessarily reconstructing intellectually the path through which they became possible.

ORT proposes a different movement.

First, it deconstructs.

Then, it reconstructs.

In deconstructing a given body of knowledge, it seeks to progressively reduce the differentiations that constitute it. In reconstructing it, it retraces the path in the opposite direction, recovering the differentiations and observing how progressively more complex structures can emerge from the preceding ones.

The purpose is not to replace inherited knowledge, but to increase its structural resolution.

Deconstructing and reconstructing makes it possible not only to know that a given concept exists or to know its definition, but to investigate how its internal differentiations are organized, which distinctions are necessary to sustain it, and at what depth these distinctions begin to disappear or merge with distinctions present in other concepts.

The movement can be represented, in simplified form, in two directions:

Construction → increase in differentiations → increase in possibilities for combination → increase in information → progressively more complex derived realities.

Abstraction → reduction in differentiations → reduction in possibilities for combination → reduction in information → conceptual approach to the limit of Original Reality.

ORT deliberately follows the second direction in order to then return along the first.

Not because it is possible to reach the zero point of the scale, but because moving toward it makes it possible to investigate what disappears and what remains when differentiations are progressively removed.

It is in this process that phenomena initially classified as different may begin to exhibit common patterns.

The subsequent reconstruction then makes it possible to return to differentiated knowledge carrying a structural understanding that was not necessarily present when that knowledge was merely received in its finished form.

ORT can therefore be understood simultaneously as a theory and as a method of analysis.

The theory proposes Original Reality as the conceptual limit of the absence of differentiation and information.

The method moves toward this limit through abstraction, deconstructing differentiations, and then makes the reverse movement, reconstructing them.

Deconstruct to identify what remains when differences disappear. Reconstruct to understand how differences make possible what we call knowledge.

It is from this movement that Original Reality Theory begins its investigation of reality.

3. Before Explaining Reality

Before Explaining Reality

Before beginning the explanation of reality proposed by Original Reality Theory, it is necessary to examine the conditions under which any explanation can be constructed and communicated.

The theory will necessarily be presented through language, concepts, abstractions, representations, formulas, and other codes. Before using these tools to explain reality, this stage therefore investigates how perception, interpretation, representation, and communication participate in constructing and conveying an explanation.

The plan published below presents the initial structure of this work.

Structural Plan — Formal Model of Formation, Representation, and Communication

1. Motivation and origin of the project

This project arose from a practical problem of communication.

The initial attempt was to construct a message precise enough for its meaning to remain invariant when transmitted between a sender and a receiver—initially, between a human being and an artificial intelligence.

At first, the objective seemed achievable by increasing precision.

A definition could be accompanied by other definitions, restrictions, examples, counterexamples, formulas, and semantic tests intended to reduce competing interpretations.

However, a recurring problem arose during the very process of constructing these definitions.

Each term added to eliminate an ambiguity introduced new possibilities for interpretation.

A word used by the sender did not reach the receiver accompanied by the experience, associations, and internal relationships that determined its meaning for the person using it.

The receiver received the code, not the internal structure that gave rise to it.

Thus, an attempt to make a message semantically invariant produced a regress:

Definition
→ identification of ambiguity
→ new definition
→ new interpretive possibilities
→ new restrictions
→ new interpretive possibilities

The problem proved deeper when it became clear that no message produced in the present can anticipate all the categories, concepts, expressions, and interpretations that may arise in the future.

Even a definition capable of excluding all currently known ambiguities would remain exposed to new semantic possibilities subsequently produced by human creativity, philosophy, science, technology, cultural transformation, and the evolution of language itself.

A future concept that does not yet exist cannot be explicitly excluded by a message produced today.

This led to a reformulation of the problem.

Perhaps the objective of rigorous communication cannot be:

eliminating every possibility of semantic drift.

Perhaps it is first necessary to understand:

why drift arises;

at which stages it arises;

how perception, interpretation, and representation participate in it;

how a representation is transformed into a message;

how the message is reconstructed by another individual;

and how successive feedback cycles can alter the correspondence between what is intended to be communicated and what the receiver reconstructs.

This project emerged from that change in the problem.

Its initial objective is not to construct a perfect language.

Its objective is to construct a formal model of the process that precedes, produces, and follows communication.


2. Fundamental problem

A simplified model of communication could be written as:

Sender → Message → Receiver

This project begins with the hypothesis that this representation omits fundamental processes.

Before a message exists, there are processes of perception, interpretation, and representation.

The message requires selection and encoding.

After transmission, the message must once again be perceived, interpreted, and represented by the receiver.

Moreover, sender and receiver have singular trajectories.

Consequently, what participates in the production of the message in the sender is not absolutely identical to what participates in its reconstruction in the receiver.

The general problem becomes:

How do singular individual trajectories participate in the transformation of events into perceptions, interpretations, and representations and, subsequently, in the transformation of part of those representations into messages that will be perceived, interpreted, and reconstructed by another individual?


3. Nature of the work

The project will initially be developed as a modular theoretical-formal model.

At this stage, it is not a single empirical experiment.

Each module must combine three explicitly separate elements:

Scientific evidence

Results, mechanisms, and relationships supported by the available scientific literature.

Hypothesis

A proposition that the model intends to examine and that must not be presented as fact merely because it has a mathematical formalization.

Formalization

A mathematical or logical representation created to make variables, relationships, dependencies, and consequences explicit.

Formalization will not be treated as evidence.

An equation can represent a hypothesis without demonstrating that the hypothesis corresponds empirically to the phenomenon.


4. Fundamental methodological rule

The reality under study will not be presumed to be divided into the same parts used in the demonstration.

Perception, interpretation, representation, state, message, and other categories will be separated because explanation requires distinctions.

Therefore:

The order belongs to the demonstration. The modeled dynamics are continuous, recursive, and interdependent.

The numbering of the modules does not mean that the phenomenon operates as a rigid sequence.

When relationships such as:

Perception → Interpretation → Representation

are used, the arrow must initially be understood as a tool for explanatory decomposition.

Recursive relationships will be made explicit as each module is formalized.


5. Central hypothesis

Hypothesis of Representational Singularity

For distinct individuals (i) and (j), the following is proposed:

Rᵢ(t) ≢ Rⱼ(t)

Where:

Rᵢ(t) = representation produced by individual i at time t

Rⱼ(t) = representation produced by individual j at time t

≢ = absence of absolute identity

The hypothesis states that representations produced by distinct individuals are necessarily singular.

The proposition will not be considered demonstrated at this point.

Its support must emerge progressively from the demonstrations concerning:

individual trajectory;

statistical configuration;

circumstance;

state;

perception;

interpretation;

representation;

encoding;

message;

and reconstruction.

At the end, it will be necessary to verify whether the adopted premises and evidence actually support:

Rᵢ(t) ≢ Rⱼ(t)

If they do not, the hypothesis must be modified or rejected.


6. Correspondence will not be treated as an absolute magnitude

Expressions such as:

“much correspondence”;

“little correspondence”;

“large difference”;

“small difference”;

will not be used as though they had an absolute meaning.

All correspondence must be associated with a criterion or purpose.

Formally:

C(X,Y | Q)

Where:

C = correspondence

X and Y = elements being compared

Q = criterion or purpose of the comparison

Thus, two representations may have sufficient correspondence according to Q₁ and insufficient correspondence according to Q₂.

Correspondence does not mean identity.


7. General architecture

Development will be divided into modules.

Each module will provide the elements needed by the next.

Module 0 — Transgenerational continuity of information
Module 1 — Statistical configuration, circumstance, and state
Module 2 — Perception
Module 3 — Interpretation
Module 4 — Representation
Module 5 — Encoding and message
Module 6 — Communication between sender and receiver
Module 7 — Drift and correspondence
Module 8 — Feedback

8. Module 0 — Transgenerational continuity of information

Question

With what antecedent conditions does a human individual begin their trajectory?

Objective

To demonstrate that an individual does not begin their informational existence from zero.

Scientific basis to investigate

Biological inheritance;

prenatal development;

language;

social learning;

cultural transmission;

accumulated knowledge;

education;

social practices;

informational continuity across generations.

Minimal proposition

The individual begins their trajectory within conditions that precede their individual existence.

Generations do not simply copy an informational base.

There is:

transmission;

selection;

transformation;

loss;

recombination;

and production of information.

Module 0 establishes the antecedent conditions.

It does not need to participate directly in every subsequent equation.


9. Module 1 — Statistical configuration, circumstance, and state

This module establishes dynamic variables that will accompany all subsequent demonstrations.

They do not constitute isolated stages preceding perception.

They participate in perception, interpretation, and representation and are simultaneously updated by the dynamics of experience.

9.1 Statistical configuration

Provisional definition:

Statistical configuration is the internalized history of previous interactions and experiences that probabilistically conditions future responses.

Provisional symbol:

Cᵢ(t)

Statistical configuration:

is not a simple count of experiences;

is not static;

is trajectory-dependent;

can be continuously updated;

and participates in the individual's subsequent responses.

An initial abstract representation may take the form:

Cᵢ(t+1) = U(Cᵢ(t), Xₜ, ...)

The function U must be developed later.

9.2 Circumstance

Provisional definition:

Circumstance is the set of current conditions of the individual's relationships with themselves and with the environment, at the time under consideration. The environment includes other individuals.

Provisional symbol:

Kᵢ(t)

The individual's relationship with themselves includes present conditions such as:

pain;

hunger;

fatigue;

emotions;

sensations;

physiological conditions;

and other relevant internal conditions.

The individual–environment relationship includes:

physical conditions;

stimuli;

objects;

social context;

other individuals;

and other elements present in the relationship at that moment.

The distinction between internal and external will be used as an explanatory device, not necessarily as an absolute boundary of the phenomenon.

9.3 State

The state represents the individual's effective configuration at the time under consideration.

An initial formalization will be:

Sᵢ(t) = F(Cᵢ(t), Kᵢ(t))

Where:

Sᵢ(t) = state

Cᵢ(t) = statistical configuration

Kᵢ(t) = circumstance

F = functional relationship to be specified later

The state participates in subsequent operations.

Those operations also participate in updating the state.

Therefore, the general dynamics must allow:

Sₜ → processesₜ → Sₜ₊₁

without assuming a simple linear chain.

Recursive dependence

Statistical configuration, circumstance, and state cannot be fully understood without perception, interpretation, and representation.

Likewise, perception, interpretation, and representation cannot be understood without statistical configuration, circumstance, and state.

This circularity does not constitute a logical error in the model.

It represents a recursive property of the phenomenon.

The modules will be separated only to make these dynamics explainable.


10. Module 2 — Perception

Question

How do differences available in an event become differences perceived by a particular individual?

Objective

To construct a scientifically supported definition of perception that can subsequently participate in the formalizations of interpretation and representation.

Scientific basis

Sensory systems;

psychophysics;

attention;

salience;

interoception;

perceptual processing;

physiological limits;

selection of information;

predictive processing, when relevant and supported.

Initial variables

Xₜ = event or set of available conditions

Sᵢ(t) = individual's state

Pᵢ(t) = perception

An initial representation may take the form:

Pᵢ(t) = F_P(Xₜ, Sᵢ(t))

This formula will not be considered definitive before the scientific analysis.

Rule

Perception will be treated as dynamic and updatable.

It participates in recursive relationships with subsequent processes.

The scientific research in this module must determine how to represent this recursiveness, not decide whether it exists.


11. Module 3 — Interpretation

Question

How is what has been perceived processed in a singular way by a particular individual?

Dependencies

This module will use concepts already formalized:

statistical configuration;

circumstance;

state;

perception.

Initial formalization

Iᵢ(t) = F_I(Pᵢ(t), Sᵢ(t))

Where:

Iᵢ(t) = interpretation.

The formula will subsequently be refined to represent recursive relationships.

Objective

To define:

what will be called interpretation;

how interpretation differs from perception;

how it depends on trajectory and state;

how it participates in subsequent updating;

and how it relates to representation.


12. Module 4 — Representation

Question

What is a representation, and how does it emerge from the dynamics involving perception, interpretation, and state?

Objective

To produce a sufficiently precise definition of representation so that it can subsequently be used in the formalization of communication.

Initial formalization

Rᵢ(t) = F_R(Iᵢ(t), Sᵢ(t))

This relationship is provisional.

The research must examine how perception, interpretation, and representation relate recursively according to contemporary scientific knowledge.

Required result

To define:

representation;

representational singularity;

representational updating;

the relationship between representation and statistical configuration;

and the limits of what can be scientifically inferred about internal representations.


13. Module 5 — Encoding and message

Question

How is part of a representation transformed into a communicable message?

Elements

R_E = sender's representation

Q_E = content selected for communication

Γ_E = encoding operation

L = code used

M = message

Initial structure:

R_E → Q_E → Γ_E → M

Hypothesis

Encoding is transformation.

Therefore:

Q_E ≢ M

The message is neither the representation nor the representational content that gave rise to it.

Topics

language;

symbols;

semantics;

pragmatics;

compression;

selection;

multimodal communication;

mathematics as code;

images;

gestures;

sound.


14. Module 6 — Communication between sender and receiver

Only at this point will the complete model of communication be constructed.

All elements used must have been defined previously.

Sender

State
→ Perception
→ Interpretation
→ Representation
→ Selection
→ Encoding
→ Message

Receiver

Message
→ Perception
→ Interpretation
→ Representation

The complete mathematical representation must incorporate the recursiveness established in the preceding modules.

Proposition to examine

The representation reconstructed by the receiver does not have absolute identity with what the sender sought to communicate.

This proposition must follow from the preceding formalizations, rather than simply being declared.


15. Module 7 — Drift and correspondence

Objective

To formalize the differences produced during communication without resorting to absolute qualifications such as:

much;

little;

large;

small.

Drift

Provisional symbol:

δ(X,Y | Q)

Drift must be defined according to a particular criterion Q.

Correspondence

C(X,Y | Q)

Where:

Q = criterion or purpose of the comparison.

The relationship between drift and correspondence will be formalized only after both concepts have been defined.


16. Module 8 — Feedback

Question

How do successive cycles of communication alter representations and correspondence between participants?

Initial structure:

E → M₁ → D

D → M₂ → E

E → M₃ → D

...

Each cycle constitutes a new event for the participants and can therefore update:

statistical configuration;

circumstance;

state;

perception;

interpretation;

representation;

and subsequent messages.

Hypothesis

Feedback does not guarantee an increase in correspondence.

It can:

increase it;

reduce it;

or reorganize it.

Therefore, we will not assume:

Cₙ₊₁ > Cₙ

as a rule.

The behavior must be analyzed as a function of the process.


17. Required structure of each module

Each module must have the same methodological architecture.

17.1 Specific question

What exactly does the module intend to explain?

17.2 Definitions

All necessary technical terms.

17.3 Current state of science

What has empirical support?

What remains controversial?

What competing models exist?

17.4 Model assumptions

What needs to be assumed for the formalization to be constructed?

17.5 Hypothesis or hypotheses

Which propositions will be examined?

17.6 Variables and symbols

Each variable must have a single, stable meaning.

17.7 Mathematical formalization

Representation of the proposed relationships.

17.8 Derivations

What follows logically from the formalization?

17.9 Examples

Applications intended to make the model understandable.

17.10 Counterexamples and adversarial tests

Explicit attempts to find situations that contradict the model or expose ambiguities in it.

17.11 Testability

What observations would be compatible with the model?

What observations could contradict it?

17.12 Limitations

What conclusions does the module not allow?

17.13 Exportable result

Which definitions, variables, equations, and conclusions become available to the next module?


18. Central symbol registry

A single symbol registry will be maintained throughout the project.

Initial example:

i = individual

t = time under consideration

Cᵢ(t) = statistical configuration

Kᵢ(t) = circumstance

Sᵢ(t) = state

Xₜ = event or available conditions

Pᵢ(t) = perception

Iᵢ(t) = interpretation

Rᵢ(t) = representation

Q_E = content selected for communication

M = message

δ = drift according to a specified criterion

C(X,Y | Q) = correspondence according to criterion Q

No symbol may change