The Conditions of System Existence
System Existence Theory
Authors: Jordan Vallejo and the Transformation Management Institute Research Group
Status: Foundational Paper | January 2026
Abstract
The term system is used across disciplines to name an object of analysis, intervention, or governance. In practice, systemhood is frequently assumed rather than demonstrated. This assumption introduces hidden instability into downstream work: analysts debate causes, meaning, performance, or remedies while operating over incompatible or non-persistent units.
System Existence Theory (SET) is a classification and admissibility framework that specifies when a proposed unit can be treated as an admissible system object under a declared interaction regime and time window. SET does not model system behavior, meaning, performance, or transformation. It governs whether such analyses are well-posed.
SET applies across physical, biological, organizational, and technical domains and introduces an explicit partition between non-interpretive systems and interpretive systems. This partition preserves compatibility with established systems science and control theory while preventing category error in interpretive domains.
I. The Problem of System Assumption
Across science, engineering, management, and governance, the word system is treated as self-evident: organizations are systems, markets are systems, platforms are systems, AI is a system. The term is invoked to justify analysis, intervention, and attribution without explicit articulation of boundary, membership, persistence, or regime conditions.
This practice obscures an upstream requirement:
Before a system can be analyzed, a proposed unit must be admissible as a system object under the conditions being claimed.
When systemhood is assumed, downstream disagreement becomes structurally irresolvable. Analysts may have high competence and good faith and still fail to converge because the unit itself is ill-posed. In such cases, disagreements are not primarily epistemic. They are failures of admissible individuation.
SET addresses this failure mode by treating systemhood as a conditional achievement rather than a default assumption.
II. What SET Is (and Is Not)
II.a What SET Is
SET is a constraint science governing the admissibility of system claims. It specifies when a proposed unit may be treated as an admissible system object under a declared interaction regime and time window.
SET adjudicates:
boundary coherence,
separability from environment,
identity persistence,
regime compatibility.
SET applies across domains and precedes behavioral, interpretive, and transformational analysis.
II.b What SET Is Not
SET does not:
define meaning or interpretation (General Theory of Interpretation),
assess interpretive stability or failure (Meaning System Science),
adjudicate interpretive authorization or durability doctrines,
model transformation dynamics (Transformation Science),
describe post-closure temporal regimes (A7/B4).
SET governs whether a unit is admissible for downstream analysis, not how the unit behaves or what it means.
III. Operational Definitions
This section defines the minimum terms required for SET to operate as a classification framework.
III.a Boundary
A boundary is a declared partition between a proposed system object and its environment, specified as:
what is inside the system object (components, roles, artifacts, processes),
what is outside (environmental factors, external agents, adjacent systems),
which interface pathways are permitted to couple inside and outside.
A boundary is not a label. It is a claim about what must be treated as jointly individuated for the purposes of analysis.
III.b Interaction Regime
An interaction regime is the declared class of interactions and coupling pathways the proposed unit is expected to maintain coherence under.
A regime declaration minimally specifies:
coupling channels (material, informational, transactional, authority routing, enforcement),
typical interaction rates and time scales,
what perturbations are considered admissibility-relevant.
Regime matters because the same boundary may be admissible under one regime and inadmissible under another.
III.c Time Window
A time window is the declared duration over which the proposed unit is claimed to persist as the same system object.
SET does not assume persistence. It requires persistence to be declared and tested within a window.
III.d Identity Persistence Criterion
An identity persistence criterion specifies what invariants must hold for the system object to count as “the same system” across the time window.
Examples of admissibility-relevant invariants:
stable boundary partition under declared perturbations,
stable membership rules (who/what counts as inside),
stable closure or enforcement locus (where binding constraints originate),
stable interface pathways through which coupling is routed.
Identity persistence criteria are domain-relative but must be declared explicitly.
III.e Perturbation Class
A perturbation class is the set of disturbances considered relevant to testing whether a boundary and identity persist.
Examples:
component substitution,
load changes,
staffing changes,
tool migration,
policy updates,
adversarial behavior,
external shocks.
A system object that persists only in the absence of expected perturbations is not admissible under that regime.
III.f Scaffolding
Scaffolding refers to external supports that maintain boundary coherence and identity persistence.
Examples:
compliance enforcement,
platform rules,
contracts and settlement layers,
centralized identity providers,
governance committees,
audit infrastructure.
Scaffolded separability can still be admissible if the scaffolding is declared as part of the regime and identity criteria. Misclassifications occur when scaffolded stability is treated as intrinsic.
IV. Classes of Systems and the Scope of SET
SET applies across domains. To prevent category error, SET distinguishes between two classes of systems while remaining applicable to both.
IV.a Non-Interpretive Systems
Non-interpretive systems are systems whose behavior can be modeled without requiring interpretive governance concepts such as reference promises, action relevance, or closure authority.
Examples include:
mechanical assemblies,
biological subsystems,
chemical processes,
cybernetic regulators.
These systems may be highly complex and adaptive. SET treats them as admissible or inadmissible system objects based on boundary and persistence conditions, not on meaning.
This preserves compatibility with physics, biology, and cybernetics.
IV.b Interpretive Systems
Interpretive systems are systems for which downstream interpretive analysis is required to govern coordination, because system outputs function as binding constraints on future action across time, agents, or interfaces.
SET does not define interpretation. It gates interpretive analysis by determining whether a proposed interpretive system is admissible as a system object under the declared regime and time window.
Only after admissibility is established do interpretive frameworks become eligible to evaluate meaning production, reliability, closure behavior, and downstream governance.
IV.c Why the Partition Is Necessary
Without this partition:
control and regulation are easily misclassified as “interpretation,”
statistical boundary formalisms are misread as system existence proofs,
interpretive and non-interpretive domains collapse into a single ontology.
SET requires the partition to preserve cross-domain credibility and prevent universal interpretivism.
V. The Law of Systemic Separability
Law of Systemic Separability
A proposed unit qualifies as an admissible system object under a declared interaction regime if and only if it can be individuated as a separable unit whose identity persists across the declared time window under the declared perturbation class.
Separability requires:
a distinguishable system–environment partition,
interface pathways consistent with the declared interaction regime,
identity persistence under the declared perturbation class.
Failure of separability renders downstream analysis ill-posed.
V.a Empirical Support for Separability
Empirical systems research provides supporting evidence that separable system objects often correspond to interaction discontinuities:
near-decomposability: internal interactions are stronger or faster than external couplings (Simon),
hierarchical structure: multi-level organization yields stable partitions at certain scales,
time-scale separation: what counts as “inside” is often revealed by differences in interaction rates.
These supports do not imply a single correct partition. They provide non-arbitrary evidentiary signals for boundary stability under a regime.
VI. Category Error Prevention
SET is frequently misread through two category errors.
VI.a Regulation and Control Do Not Imply Interpretation
Feedback control and cybernetic regulation presuppose a bounded unit but do not require interpretive governance constructs. A regulator can be admissible as a system object without being an interpretive system.
This distinction prevents erroneous claims that “everything interprets” whenever it responds to signals.
VI.b Statistical Partitions Do Not Imply Systemhood
Formal boundary candidates (including conditional independence partitions and similar constructs) can be useful as boundary hypotheses. They are not, by themselves, proofs of admissible system identity across a regime and time window.
SET requires regime-relative persistence of identity under perturbation. A boundary that exists only as a model artifact does not establish admissible systemhood.
VII. The System Admissibility Procedure (SAP-1)
SAP-1 is the minimal operational procedure for SET.
VII.a Procedure Steps
Declare a boundary candidate
Specify what is inside, what is outside, and what interfaces are allowed.Declare the interaction regime
Specify coupling channels, typical rates, and relevant conditions of operation.Declare the time window
Specify the duration over which system identity is being claimed.Declare the perturbation class
Specify the expected disturbances that the system must remain coherent under.Declare identity persistence criteria
Specify what invariants must hold for “the same system” across the window.Test separability and identity persistence
Evaluate whether the boundary and invariants can be maintained under the regime and perturbation class.Return admissibility classification with justification
VII.b Outputs
Admissible: separable and identity-persistent under declared regime and perturbations.
Conditionally admissible: admissible only if explicit scaffolding, narrowed boundaries, or stricter regime declarations are included.
Inadmissible: cannot be individuated as a stable system object under the declared conditions.
Indeterminate: insufficient evidence, incompatible measurement, or unresolved boundary ambiguity.
Indeterminate is a valid scientific output. Many individuation domains (notably in biology and complex systems) accept plural or context-dependent individuation as the correct posture rather than as a deficiency.
VIII. Boundary Stability, Scaffolding, and Misuse Patterns
VIII.a Boundary Stability vs Boundary Scaffolding
Some system objects maintain boundaries endogenously. Others maintain boundary coherence through scaffolding: enforcement, governance, contracts, and infrastructure that stabilize interfaces.
Scaffolded separability may be admissible if scaffolding is declared explicitly as part of the regime and identity criteria.
VIII.b Common Misuse Patterns
Boundary inflation
Treating diffuse phenomena as a single coherent system object (e.g., “the market,” “society,” “AI”) without admissible boundary declarations.Label persistence mistaken for identity
Treating a persistent name, org chart, or product line as evidence of stable system identity.Coordination substitution
Treating coordination as evidence of systemhood. Coordination can occur across multiple local worlds via artifacts without a unified system object.Output stability error
Treating stable outputs as evidence of stable system identity. Output stability can be produced by scaffolding, not by stable individuation.
These patterns explain why disputes persist despite competence and effort: the argument is being conducted over inadmissible or incompatible units.
IX. Illustrative Edge Cases With SAP-1 Traces
This section demonstrates how SET classifies common ambiguous cases.
IX.a Thermostat / PID Controller (Non-Interpretive System)
Boundary candidate: controller hardware + sensor + actuator within an appliance.
Regime: electrical/thermal coupling; control loop dynamics.
Time window: operational lifetime under normal conditions.
Perturbations: sensor drift, load changes, component replacement.
Identity criteria: boundary remains stable; control loop remains defined.
Result: Admissible (non-interpretive system).
Justification: separability is stable and identity criteria can be satisfied without invoking interpretive governance.
IX.b Candle Flame (Boundary Instability Under Common Regimes)
Boundary candidate: flame as an object.
Regime: combustion + convection; high coupling to environment.
Time window: minutes to hours.
Perturbations: airflow, fuel variation, humidity, temperature gradients.
Identity criteria: stable boundary and internal invariants.
Result: Inadmissible or Indeterminate (regime-dependent).
Justification: under many regimes, the boundary cannot be made stable under typical perturbations; identity persistence is not reliably definable.
IX.c Court of Law (Nested Interpretive System)
Boundary candidate: court institution as an operational unit (procedures, roles, enforcement linkages).
Regime: procedural and authority routing; evidentiary constraints; enforcement interfaces.
Time window: case lifecycle to precedent horizon.
Perturbations: personnel change, caseload variation, appeals, political shifts (scope-dependent).
Identity criteria: stable closure authority and enforceable outputs.
Result: Admissible (interpretive system).
Justification: separable institutional boundary exists, interface pathways are explicit, and identity persistence can be stated via durable closure and enforcement mechanisms.
IX.d “The Market” (Boundary Inflation Risk)
Boundary candidate: unspecified “market.”
Regime: unclear; multiple venues, instruments, settlement layers.
Time window: unspecified.
Perturbations: policy changes, liquidity shocks, platform failures.
Identity criteria: unspecified.
Result: Indeterminate by default.
Justification: boundary inflation; admissibility requires explicit declaration of scope (venue, instrument class, settlement/enforcement layer). With declared scope, the object may become conditionally admissible.
IX.e Platform Moderation (Scaffolded Separability)
Boundary candidate: platform’s moderation + ranking + enforcement apparatus.
Regime: algorithmic coupling + policy enforcement + user behavior feedback.
Time window: policy version horizon.
Perturbations: policy updates, model swaps, adversarial actors.
Identity criteria: stable enforcement locus and boundary definition across updates.
Result: Conditionally admissible.
Justification: separability depends heavily on scaffolding (policy, enforcement, audit). Admissibility improves when scaffolding is explicitly declared.
X. Interfaces With the Canon
This section prevents program bleed by defining clean handoffs.
X.a SET → Interpretive Frameworks
SET supplies admissible system objects (boundary, regime, time window, identity criteria). Interpretive frameworks become applicable only after admissibility is established and only for interpretive systems.
X.b SET → Transformation Science
Transformation destabilizes boundary and identity persistence. SET predicts when “system” claims become ill-posed during becoming due to regime shifts or identity instability.
X.c SET → Diagnostics and Standards
Diagnostics and standards require a declared system object. SET governs whether the declared unit is admissible before measurement or governance conclusions are drawn.
XI. Implications for Research and Practice
SET explains why many organizational disputes persist without resolution: parties are operating over incompatible or inadmissible system objects. The failure is upstream of competence, intent, or effort.
Key implications:
Some interventions fail because they target a unit that cannot persist under the claimed regime.
Some escalations increase disagreement because they enlarge boundaries into inadmissibility.
Some reforms cannot stabilize because identity persistence criteria are undefined or violated by routine perturbations.
SET reframes common governance problems as errors of admissible individuation rather than as defects of motivation.
XII. Conclusion
Systemhood is not a default assumption. It is a conditional classification.
SET provides an admissibility discipline for system claims by requiring explicit boundary, regime, time window, perturbation class, and identity persistence criteria. By separating admissibility from interpretation and existence from performance, SET establishes the ground required for responsible analysis and governance in complex environments.
Citation
Vallejo, J. (2026). The Conditions of System Existence: An Admissibility Theory of Systemhood. System Existence Theory Foundational Paper. Transformation Management Institute.
References
Ashby, W. R. (1956). An Introduction to Cybernetics. Chapman & Hall.
Bertalanffy, L. von. (1968). General System Theory: Foundations, Development, Applications. George Braziller.
Friston, K. (2010). The free-energy principle: a unified brain theory? Nature Reviews Neuroscience, 11(2), 127–138.
Friston, K. (2013). Life as we know it. Journal of the Royal Society Interface, 10(86), 20130475.
Simon, H. A. (1962). The architecture of complexity. Proceedings of the American Philosophical Society, 106(6), 467–482.
Star, S. L., & Griesemer, J. R. (1989). Institutional ecology, ‘translations’ and boundary objects: Amateurs and professionals in Berkeley’s Museum of Vertebrate Zoology, 1907–39. Social Studies of Science, 19(3), 387–420.
Stanford Encyclopedia of Philosophy. (Latest revision). Biological Individuals. (Entry: “Biological Individuals / Biological Individuality”.)
Pattee, H. H. (1995). Evolving self-reference: Matter, symbols, and semantic closure. Communication and Cognition – Artificial Intelligence, 12, 9–27.
(Additional Pattee primary sources may be added depending on which semiotic-closure treatment is cited in the paper.)Krakauer, D. C., et al. (2020). (Information-theoretic individuality and multiscale individuation; include specific paper details used in final text.)