BERT JSON models: generic Klir / Bunge / Mobus system definitions + a worked thermostat example

[rsthornton]

Context

Downstream of the Facets Klir/Bunge lens work (halcyonic-systems/general-systems-reasoner#31). With the trio embedded in Facets, BERT gets the model-level companion: reference JSONs that make K ≅ 2 concrete instead of asserted.

Two concrete deliverables

A. Generic framework models — one BERT JSON per thinker, each modeling what that thinker says a system is:

• Klir — things + relations, S = (T, R) (set-theoretic)
• Bunge — CESM (Composition, Environment, Structure, Mechanism)
• Mobus — the 8-tuple S = ⟨C, N, E, G, B, T, H, Δt⟩

These are teaching/reference artifacts — the abstract structure each framework asserts, rendered in BERT.

B. One worked concrete example — a thermostat (the classic cybernetics system) modeled through each lens, LLM-assisted (via Facets / the generator) or manual. Same system, three vocabularies; the differences show empirically.

Lighter than it first looked

The earlier framing made this a deep "what differs, given the common core?" question. It's simpler: build the generic models + one worked example and let the comparison surface from the artifacts. Still a short design call on representation (separate JSON per lens vs one model + lens overlays), but the deliverables are concrete.

• Models via the intermediate spec → generator, never hand-authored (project discipline).

Relates to

• Facets lenses: halcyonic-systems/general-systems-reasoner#31 (prerequisite — start after it lands)
• PhD: strategy/phd/sl-phd.md classroom beachhead + Open Question Author User Stories to Guide BERT’s UI/UX Development #4 (the thermostat / worked example feeds the validation study)
• Grounding: systems-science-foundations trio proofs (Klir / Bunge / Mobus, K ≅ 2)

[rsthornton]

Representation decided → one kernel model + lens overlays (not separate JSON per lens)

From a 2026-06-09 architecture session: K ≅ 2 is not a fourth peer to compare — it's the kernel. Klir/Bunge/Mobus are an abstraction gradient of derived lenses over the morphism, each adding one layer of ontological commitment:

• K ≅ 2 — system = morphism (walking arrow); pure directed relation
• Klir — S = (T, R); systemhood = R, thinghood = T. The set-theoretic shadow of the morphism, nearest the kernel
• Bunge — CESM = Klir's R (Structure) + Composition + Environment + Mechanism
• Mobus — 8-tuple = CESM + dynamics/history/timescale/recursion; outermost, what BERT runs on today

The hinge: the morphism reads Klir's static relation as a directed, composable one — static systemhood → dynamic systemhood. That's why one kernel can carry all three views and the dynamics.

What this means for the deliverables here

• B (thermostat worked example) becomes a projection demo: model the thermostat once as a morphism-grounded kernel, then render Klir / Bunge / Mobus as overlays. Klir shows the static (T,R) relation, Bunge surfaces the mechanism, Mobus shows the flows. The differences are projections of one arrow, not three hand-built models that happen to disagree.
• A (generic framework models) stay as teaching artifacts, but they're now views of the kernel, not independent ontologies.

Dependency (gating)

This rests on a formal claim: the morphism kernel generates each presentation as a faithful view. That gets proved in systems-science-foundations first — view-generation + round-trip faithfulness lemmas (boundary = sub-object, flow = morphism, subsystem = functor; (T,R)/CESM/8-tuple as faithful views). Scaffolded as the 2026-06-11 SSF session. Prove the views in Lean before refactoring the BERT data model. Kernel underneath; the 8-tuple stays the working/default lens; UX still draws entities/flows.

Pairs with #75 (LEGO with proofs) — the faithful-view lemmas are the composable blocks.

[rsthornton]

View-generation landed in SSF (2026-06-11, Systems/Klir/ViewGeneration.lean — see #88). Direct consequence for these reference JSONs: each generic framework model is a generated view of the same kernel, and the generation costs are the validation rules — the Bunge model must contain at least one bond between distinct components, the Mobus model must have no self-dependencies. The thermostat example can demonstrate all three views round-tripping to one kernel, which is the K ≅ 2 claim made concrete in JSON rather than asserted.

[rsthornton]

Both deliverables shipped — closing.

Discharged in the bert-lenses standalone prototype (active/bert-lenses/), which renders one stored kernel through Klir/Bunge/Mobus lenses over the #88 surface.

B. Worked example — a thermostat modeled once and viewed through all three lenses; kernel() shown provably identical across lens switches (the read-only theorem made visible). bf7375e, f0ff7e7.

A. Generic framework models — one per thinker, generated offline via GSR generate() from hand-authored intermediate specs (never hand-authored JSON):

• Klir — S = (T, R): things + relations, no internal bond
• Bunge — C/E/S: two connected components (Def 1.1)
• Mobus — the 8-tuple: a 3-component bonded network with interfaces + typed flows

00fc8bb.

Representation design call (resolved): one model per framework + a shared worked example, viewed through lens overlays over a single kernel — not separate per-lens JSONs of the same system. The K ≅ 2 point lands harder this way: the kernel is invariant; the lens is the vocabulary.

The comparison surfaces empirically, as hoped — and it's enforced as a test (lens_entry_matrix_is_as_designed): Klir-generic enters Core + Operational but not Structural. Its S=(T,R) has no bond, so through Bunge it reads as an aggregate, firing the cited engine message ("Bunge Def 1.1: an unbonded collection is an aggregate"). That difference between what Klir and Bunge call a "system" is now visible in the UI, not asserted.

Roadmap for what's next (author → translate): active/bert-lenses/ROADMAP.md.