Donald Severs

Any embedded receiver operating a capacity-limited channel—one whose capacity is insufficient to span its input space—necessarily partitions that input space into equivalence classes. The invariance properties of these classes generate a four-level taxonomy. Level 1 features are invariant under all physically realizable channels; Level 2 features are invariant across channels that share a constraint profile; Level 3 features are channel-specific. Level 4 is the formal boundary of the derivation: whatever, if anything, lies outside the structural content of the channel. The first three levels are derived from three premises about physical receivers; the fourth is registered, not filled. The taxonomy replaces the binary subjective/objective distinction with a graded structure indexed by invariance class and parameterized by constraint tightness. Companion papers apply the taxonomy to universals (Severs, 2026a), structural opacity (Severs, 2026b), inter-scale equivalence classes (Severs, 2026c), and the structure of subjectivity (Severs, 2026e).

The subjective/objective distinction is traditionally treated as a metaphysical primitive: objective facts are mind-independent; subjective facts depend on a perspective. This paper treats subjectivity instead as a case study in a more general channel-theoretic taxonomy of invariance and convergence (A Taxonomy of Invariance, Severs (2026e)), developed across the ECSR series. The distinction is not primitive but derived: it falls out of the finite-capacity receiver model once the relevant constraint profile is made explicit. An "observer" is an embedded subsystem receiving signals through a finite-capacity channel. What philosophers call "objectivity" is channel-invariance; what they call "subjectivity" is the channel-dependent residual. Between these extremes lies an intermediate zone, convergence-class invariance, where tight physical constraints on any viable receiver force convergent equivalence classes. The result is a four-level taxonomy replacing the binary distinction, with each level grounded in physics rather than metaphysics. A decision procedure is developed for classifying features of experience: decompose the feature into structural components, then evaluate whether structure exhausts it or leaves a non-structural remainder. Applied to five features traditionally bundled into the hard problem of consciousness, unity, temporal flow, perspectivalness, subject/object structure, and intentionality, the procedure yields structural accounts at each step, with remainders that resist independent characterization. The paper's scope is structural: features traditionally assigned to "subjectivity" are systematically reclassified as convergent channel structure (Level 2) by the convergence argument. The framework is methodologically structuralist: it characterizes the relational organization of phenomena under physical constraints but is neutral on the intrinsic nature of the relata, constraining physicalist, idealist, and Russellian interpretations equally. Whether being an embedded receiver feels like something, and if so, why, is a question the taxonomy locates precisely (Level 4) without resolving. Six positions on what remains at Level 4 are mapped; they share Levels 1–3 entirely and diverge only on whether phenomenal character is empty, structurally constituted, emergent, fundamental, unknowable, or irreducible. What falls within scope is the architecture of what varies, what converges, and what remains genuinely perspectival across embedded receivers.

Our previous two papers argued that Universals are equivalence classes with causal surplus [35] and that physical opacity mechanisms make macro-variables the only accessible causal handles for embedded systems [36]. Neither specified the form of the filtering process that connects micro-states to stable macro-kinds. This paper closes the gap. Building on Zurek’s treatment of the environment as a communication channel in Quantum Darwinism, we argue that each opacity mechanism instantiates a capacity-bottleneck channel between scales, and that the data processing inequality (DPI), together with Shannon’s rate-distortion theorem, provides the mathematical warrant for why such channels generate stable equivalence classes: the macro-kinds are the rate-distortion partition of micro-states whose outputs are indistinguishable within tolerance. We demonstrate this with two biological case studies—protein folding and enzyme specificity—and show that the physical constraints grounding effective capacity limits are Symmetry-regime constraints, thereby bridging the two engines of the ECSR framework.

In Effective Causal Structural Realism (ECSR) [6], we identified causally emergent macroscopic structures as philosophy’s Universals. Universals (Structural Types) are objectively real difference-makers due to being Formal Causes: successful loci of dynamically maintained functional organization that constrain and are constituted by micro-states. Micro-states (Tokens, Realizers, or Particulars) are objectively real due to being Material or Efficient Causes: they constitute the dynamical engine (Hamiltonian) that makes macro-structures possible. The present paper elucidates a physical asymmetry that drives this bifurcation: Structural Opacity. Complex physical systems exhibit one-way structure: forward evolution from micro-states to macro-observables is tractable, while inversion—recovering micro-histories from macro-states—is not. This asymmetry is the reason macroscopic structures are metastable: where opacity obtains, it renders the micro-scale causally recessive for any embedded system, making macro-variables the best accessible causal handles. The paper catalogues the physical mechanisms that generate opacity—thermodynamic irreversibility, decoherence, chaotic sensitivity, and dynamical scrambling—and argues that their convergent consequence for causation and emergence is best understood through the formal lens of finite-capacity channels filtering information between scales.

Within scientific realism, a key debate concerns whether our best theories describe intrinsic entities or relational structures. Ontic Structural Realism (OSR) champions the latter, holding that physics tracks mathematical structures. This position, however, leads to the “problem of causal inertness”: how can abstract structures possess the causal power to drive physical systems? This paper proposes Effective Causal Structural Realism (ECSR), a framework integrating OSR with structural insights drawn from Quantum Field Theory and conceptual tools from Information Theory. We extend the causal-emergence framework (Hoel et al.) with an Admissibility Filter. While Hoel’s Causal Emergence 2.0 rigorously characterizes the intrinsic causal capacity of a system using idealized interventions, ECSR extends this work into the domain of physical ontology. We propose that for ontological commitment, causal comparisons must be evaluated relative to a Physically Grounded Intervention Family (I_B) constrained by thermodynamic cost and coupling limits. Under this filter, we identify macroscopic universals as the specific subset of effective macrostructures that survive the constraints of physical admissibility. We identify a scale-dependent dominance gradient where the mechanism of efficacy shifts from the rigid conservation laws of the micro-scale (Symmetry) to the error-correcting dynamics of the macro-scale (Effectiveness). On this account, a universal is the equivalence class a finite-capacity inter-scale channel induces on its micro-inputs—the rate-distortion partition of micro-states whose macro-outputs are indistinguishable within tolerance—upgraded to ontological status by the admissibility filter. Consequently, the classical Problem of Universals is refocused, away from “objects sharing properties,” toward “structures with causal efficacy under admissible intervention.”