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Executive Summary
Across scientific, medical, and policy domains, systems that fail rarely do so gradually. Instead, collapse is often sudden, following long periods of apparent stability. This pattern reflects a fundamental limitation of performance-based metrics, which track present outputs while overlooking structural conditions required for continued existence.
This paper proposes a unifying framework that treats life as viability under constraint. Rather than defining life by complexity, function, or optimization, it asks a more basic question: what conditions must be continuously satisfied for a system to persist at all?
The framework proceeds from widely accepted physical principles. Because living systems operate far from equilibrium, they require continuous energy throughput. Because they exist under constant disturbance, they require regulation and control. Because regulation is costly and environments are variable, they require information, memory, and prediction. These necessities lead naturally to a geometric conception of viability: a bounded region of state space within which recovery remains possible, surrounded by absorbing boundaries corresponding to irreversible failure.
From this geometry follow several universal results. Persistence depends on a small set of invariant capacities — such as flux adequacy, boundary integrity, regulatory capacity, informational continuity, adaptive plasticity, and preservation of future option space. These capacities are not independent; they are coupled through conjugate pairings that enforce trade-offs. Survival is conjunctive rather than compensatory, giving rise to a multiplicative viability structure dominated by weakest-link dynamics. As a consequence, collapse often appears abrupt even when underlying degradation has been gradual.
A central contribution of the framework is the distinction between stability and intrinsic health. Systems may remain stable while silently consuming reserves and narrowing future options, a condition termed compensated fragility. Recognizing this distinction allows earlier detection of collapse risk and more effective intervention timing across domains, from intensive care medicine to institutional governance and ecological management.
Finally, the framework shows that once action is admitted, a minimal notion of responsibility follows inevitably. Actions differ in whether they preserve or undermine viability across relevant scales and time horizons. This ordering is not moral or ideological; it is imposed by the geometry of persistence itself.
By making explicit the constraints implicit in many existing theories, this work offers a shared grammar for understanding life, fragility, and responsibility across scales. Its value lies not in replacing domain-specific models, but in clarifying what no living system can afford to violate if it is to endure.
Universal Invariants and Viability Factors of Living Systems
Please scroll horizontally to see right columns| Factor Name | Capacity Description | Biological Examples | Institutional Examples | Example Indicators | Conjugate Pairing |
|---|---|---|---|---|---|
| Flux | Continuous throughput of energy and matter sufficient to offset dissipation and component turnover. | Metabolism, respiration, photosynthesis, nutrient exchange. | Resource throughput, cash flow, supply-chain reliability. | Energy balance, supply continuity, metabolic adequacy. | Structure  Flux |
| Boundary | Maintenance of selective permeability to distinguish system from environment while permitting regulated exchange. | Membranes, skins, immune systems. | Rules, norms, legal/regulatory boundaries, institutional identity. | Leakage rates, permeability, integrity of interfaces. | Boundary Exchange |
| Control | Ability to detect deviations from viable ranges and enact corrective responses (regulatory capacity). | Homeostasis, autonomic control, biochemical feedback networks. | Governance, regulation, quality-loop closure. | Response time, regulatory effort, crisis frequency. | Control Variance |
| Memory | Preservation of information-bearing structures across time to reduce future regulatory cost. | Genome, immune memory, neural states. | Institutional knowledge, procedures, standards, records. | Learning retention, protocol persistence. | Memory Plasticity |
| Plasticity | Capacity to modify internal organization and strategies in response to changing conditions. | Developmental canalization, neuronal plasticity, adaptive behavior. | Policy flexibility, organizational reconfiguration. | Reconfiguration speed without breakdown. | Memory Plasticity |
| Option Space | Preservation of future degrees of freedom and the volume of viable trajectories accessible for recovery. | Physiological reserve, redundancy, metabolic buffers. | Fiscal buffers, surge capacity, diversification. | Reserves, redundancy, recovery time after perturbation. | Commitment Option Space |
