The Scientific Lineage of Meaning

Authors: Jordan Vallejo and the Transformation Management Institute Research Group

Status: Monograph A3 | November 2025

I. Purpose and Scope

Meaning System Science did not emerge as a single theoretical invention. Its minimal architecture became visible only after distinct disciplines, operating under different historical pressures, were forced to confront recurring coordination failures that could not be resolved through local explanation.

This monograph traces how five interpretive constraints became scientifically legible as non-optional under specific observability regimes. Each constraint surfaced when a common shortcut repeatedly failed under scale, load, coupling, or rate pressure. Once exposed, the shortcut could no longer be treated as adequate, and a stabilizing condition became structurally required.

This monograph does not define Meaning System Science variables, laws, dynamics, regimes, or thresholds. Those are specified elsewhere in the canon. Its purpose is explanatory rather than architectural: to show why the MSS stabilizers are not arbitrary, not culturally contingent, and not optional once interpretation is treated as a system behavior.

A3 is a lineage analysis of constraint discovery. It explains how interpretive requirements became visible, not how they operate.

II. How Interpretive Constraints Become Visible

Scientific constraints are not discovered by preference. They become visible when failure persists despite competence, effort, and incentive.

An interpretive constraint becomes legible when:

1. a simplifying shortcut is repeatedly used,

2. the shortcut appears locally reasonable,

3. coordination fails anyway,

4. and no increase in effort or intent resolves the failure.

At that point, the shortcut becomes disallowed—not by decree, but by exhaustion.

Interpretive constraints tend to surface when:

• scale increases beyond local familiarity,

• rate increases beyond correction capacity,

• coupling introduces external dependency,

• or correction pathways saturate.

Each stabilizer formalized in Meaning System Science emerged under one of these pressure conditions. No single discipline encountered all constraints simultaneously. Each encountered one as unavoidable.

III. Truth Fidelity (T)

Reference Becomes Non-Optional Under Formalization Pressure

Observability regime
Formal logic, mathematics, and scientific language require truth claims that remain stable under abstraction. As systems moved away from immediate empirical context, persuasion and shared intuition ceased to stabilize interpretation.

Failure made visible
Statements could be internally consistent, widely accepted, or rhetorically compelling while remaining ungrounded in any checkable condition. Disputes became irresolvable because no shared reference rule constrained what would count as settling the claim.

Constraint that became unavoidable
Truth must be definable independently of belief, authority, or acceptance. A claim must remain reconstructable against conditions that can, in principle, be checked.

Disallowed shortcut
Defining truth as consensus, authority, or interpretive preference.

Structural consequence
Once this constraint is accepted, any meaning system that coordinates action must preserve a promised reference discipline. Meaning System Science incorporates this requirement as Truth Fidelity (T).

(Anchor: Alfred Tarski)

IV. Signal Alignment (P)

Meaning Cannot Be Carried by Signals Alone

Observability regime
Linguistic systems, symbolic coordination, and mass communication increased reliance on shared signals to stabilize meaning across distance and role.

Failure made visible
Identical signals produced incompatible interpretations even among cooperative actors. Coordination failures persisted despite increased messaging, clarification, and emphasis.

Constraint that became unavoidable
Signals function relationally. They must converge on shared reference conditions and preserve consistent authority weighting to stabilize interpretation.

Disallowed shortcut
Treating signals as transparent containers of meaning.

Structural consequence
Interpretive stability requires convergence among signals relative to reference. Meaning System Science formalizes this requirement as Signal Alignment (P).

(Anchor: Ferdinand de Saussure)

V. Structural Coherence (C)

Coordination Requires Stable Pathways, Not Just Shared Understanding

Observability regime
Organizations, institutions, and multi-role systems scaled beyond direct coordination and personal familiarity.

Failure made visible
Interpretations fragmented even when reference and signals were adequate. Decisions stalled, corrections looped, and authority became ambiguous.

Constraint that became unavoidable
Meaning must route through stable pathways for decision, correction, and closure. Without routable structure, interpretation disperses regardless of intent.

Disallowed shortcut
Explaining coordination failure by blaming individuals, incentives, or communication volume while leaving pathways unspecified.

Structural consequence
Interpretive continuity requires structural routes. Meaning System Science incorporates this requirement as Structural Coherence (C).

(Anchor: Ludwig von Bertalanffy)

VI. Drift Rate (D)

Inconsistency Accumulates as a Rate Under Load

Observability regime
High-throughput environments, sustained operational pressure, and extended coordination chains increased the volume of unresolved mismatch.

Failure made visible
Contradictions stopped resolving locally. Exceptions accumulated. Rework increased. Stability degraded without a single identifiable error.

Constraint that became unavoidable
Instability is governed by accumulation rate. Inconsistency compounds when resolution capacity is exceeded, even if individual errors are small.

Disallowed shortcut
Treating contradiction as episodic rather than cumulative.

Structural consequence
Meaning systems must account for accumulation velocity. Meaning System Science treats this requirement as Drift (D), defined as an inconsistency accumulation rate.

(Anchor: Ilya Prigogine)

VII. Affective Regulation (A)

Correction Capacity Is Finite and Structurally Constraining

Observability regime
Prediction-heavy, high-consequence environments increased cognitive and emotional load during interpretation and revision.

Failure made visible
Premature closure, brittle commitment, avoidance of correction, and degraded decision quality appeared under sustained pressure despite adequate information.

Constraint that became unavoidable
Interpretation depends on regulatory capacity. Systems cannot sustain uncertainty, revision, and correction without sufficient bandwidth.

Disallowed shortcut
Treating regulation as a soft or secondary concern.

Structural consequence
Correction quality is capacity-limited. Meaning System Science incorporates this requirement as Affective Regulation (A), applicable across individual and collective scales.

(Anchor: Lisa Feldman Barrett)

VIII. Boundary Case: Claude Shannon

Why Transmission Is Not Interpretation

Shannon’s work clarified an essential boundary. Signals can be transmitted reliably without carrying meaning. Transmission capacity and semantic interpretation are separable phenomena.

Meaning System Science begins where Shannon’s framework ends. MSS does not explain how signals arrive. It explains what becomes required once arrival is no longer the bottleneck and interpretation governs action.

Shannon’s exclusion of semantics preserves scientific clarity. A3 retains that boundary to prevent category collapse.

IX. Convergence Without Coordination

These constraints were not discovered through collaboration or shared intent. They emerged independently because different systems encountered different limits.

Each thinker identified a non-negotiable condition by eliminating a shortcut that repeatedly failed:

• persuasion without reference,

• signaling without convergence,

• intent without structure,

• error without rate,

• cognition without regulation.

Meaning System Science integrates these constraints without narrative synthesis. Their convergence justifies the minimal architecture not as design choice, but as necessity.

X. Canonical Placement

What A3 does

• Explains why MSS stabilizers are inevitable under coordination pressure.

• Grounds the architecture in independent constraint discovery.

• Demonstrates non-arbitrariness without redefining constructs.

What A3 does not do

• Define variables (A2).

• Specify proportional constraints (A4).

• Constrain inference (A5).

• Certify general-theory status (A6).

• Model dynamics or propagation (A7).

XI. Conclusion

Meaning becomes a scientific object when interpretive constraints are no longer optional. Those constraints became visible only when systems failed despite competence, effort, and intent.

The five stabilizers of Meaning System Science did not originate from preference or ideology. They emerged because coordination under constraint made shortcuts impossible to sustain.

A3 documents that emergence.

Citation

Vallejo, J. (2025). Monograph A3: The Scientific Lineage of Meaning. TMI Scientific Monograph Series. Transformation Management Institute.

References

Alfred Tarski
Feferman, A., & Feferman, S. Alfred Tarski: Life and Logic. Cambridge University Press, 2004.
Tarski, A. “Pojęcie prawdy w językach nauk dedukcyjnych” [The Concept of Truth in Formalized Languages], 1933.
Woleński, J. Logic and Philosophy in the Lvov–Warsaw School. Kluwer Academic Publishers, 1990.

Ferdinand de Saussure
Saussure, F. de. Cours de linguistique générale. Ed. Charles Bally & Albert Sechehaye, 1916.
Culler, J. Saussure. Fontana Press, 1976.
Harris, R. Saussure and His Interpreters. Edinburgh University Press, 2001.
Bouquet, S., & Engler, R. (eds.). Ferdinand de Saussure: Sources Manuscrites et Documents. Various volumes, 1990–2000.

Ludwig von Bertalanffy
Bertalanffy, L. von. General System Theory: Foundations, Development, Applications. George Braziller, 1968.
Davidson, M. Uncommon Sense: The Life and Thought of Ludwig von Bertalanffy. J. P. Tarcher, 1983.
Hammond, D. The Science of Synthesis: Exploring the Social Implications of General Systems Theory. University Press of Colorado, 2003.
Hofkirchner, W. (ed.). Biographies of Systems Thinkers. Various chapters, 2018.

Ilya Prigogine
Prigogine, I. From Being to Becoming: Time and Complexity in the Physical Sciences. W. H. Freeman, 1980.
Prigogine, I., & Stengers, I. Order Out of Chaos: Man’s New Dialogue with Nature. Bantam Books, 1984.
Kondepudi, D., & Prigogine, I. Modern Thermodynamics: From Heat Engines to Dissipative Structures. Wiley, 1998.
Bedau, M. A., & Humphreys, P. (eds.). Emergence: Contemporary Readings in Philosophy and Science. MIT Press, 2008.

Lisa Feldman Barrett
Barrett, L. F. How Emotions Are Made: The Secret Life of the Brain. Houghton Mifflin Harcourt, 2017.
Barrett, L. F. Seven and a Half Lessons About the Brain. Houghton Mifflin Harcourt, 2020.
Lindquist, K. A., & Barrett, L. F. “The Experience of Emotion.” Annual Review of Psychology, 2008.
Simmons, W. K., Lindquist, K. A., & Barrett, L. F. “A Constructed Emotion Model of Cognitive and Affective Neuroscience.” Social Cognitive and Affective Neuroscience, 2013.

Boundary Figure: Claude Shannon
Shannon, C. E. “A Mathematical Theory of Communication.” Bell System Technical Journal 27 (1948): 379–423, 623–656.