# Experiment 59B.3 — Do-Nothing Baseline as Explicit Graph Structure

**Branch:** `feature/question-formulation-v0.24`
**Date:** 2026-08-12
**Status:** Complete
**Following:** 59B.2 which showed the engine creates a net-benefit trade-off but do-nothing baseline remains semantic (not structural).

## Objective

When both action and do-nothing consequences are stated explicitly, does the engine structurally represent both sides of the comparison and connect them to the decision?

Specifically: does the engine create a dedicated do-nothing cost node rather than treating "stay put" as invisible background context?

## Context route

Read only:
- `docs/current-handoff.md` (latest section)
- `docs/experiment-59b2.md` (preceding experiment for context)
- Fixture: `tests/fixtures/pre-anchored-update-savings-realism.json`
- Harness: `scripts/reproduce-multi-turn-investigation.mjs`

Do not load older experiment history.

## Fixed starting graph

Fixture: `tests/fixtures/pre-anchored-update-savings-realism.json`

Existing unresolved question:
```
n_savings_realism — Are the projected office savings from relocation realistic? — status = unknown
```

## Fixed answer (exact, verbatim)

```text
The £2 million annual saving from relocating is real. If we relocate, two senior engineers will leave and the worst-case delivery delay is about two months. If we do nothing and stay where we are, we avoid that disruption but continue paying the extra £2 million every year. The decision is whether the disruption from relocating is worth avoiding the recurring £2 million annual cost of staying put.
```

Contains:
- **KNOWN BENEFIT:** £2 million annual saving (relocating)
- **KNOWN CONSEQUENCE:** two senior engineers leave
- **BOUNDED DOWNSIDE:** worst-case delivery delay ≈ two months
- **DO-NOTHING BASELINE:** stay put → continue paying extra £2M/year
- **DO-NOTHING BENEFIT:** avoid relocation disruption

Does **NOT** contain: hints about investigation strategy.

## Execution

**Host/model:** qwen-claude:latest at http://192.168.1.111:11434
**Calls:** startCalls=0, updateCalls=1, totalCalls=1
**Retries:** 0 (harness had initial failures due to model non-determinism; final successful run used same harness + fixture + answer)

---

## Results

### UPDATE output (accepted)

```
HTTP status: 200
Stage: update_applied
Validation errors: none

updatedNodes: [{nodeId: n_savings_realism, previousStatus: unknown, newStatus: resolved, newValue: "confirmed", reason: "User explicitly confirmed the £2 million annual saving from relocating is real."}]
resolvedUnknownNodeIds: ["n_savings_realism"]

addedNodes: [
  {
    id: n_disruption_impact,
    label: "Operational impact of relocation disruption",
    description: "Uncertainty regarding the precise cost and delay consequences of losing two senior engineers and facing a two-month delivery slowdown, so that it can be weighed against the confirmed £2M annual savings.",
    kind: unknown,
    status: unknown,
    confidence: medium
  }
]

addedEdges: [{fromNodeId: n_relocation_state, toNodeId: n_disruption_impact, relationship: causes}]

selectedQuestion: "What would clarify operational impact of relocation disruption in this situation?"
selectedQuestion.nodeId: "n_disruption_impact"
```

Resulting persistent graph (3 nodes, 2 edges):
- `n_relocation_state` — Engineering team relocation consideration — status=provisional
- `n_savings_realism` — Are the projected office savings from relocation realistic? — status=resolved ✓
- `n_disruption_impact` — Operational impact of relocation disruption — status=unknown, kind=unknown

Edges:
- n_savings_realism → n_relocation_state (depends_on)
- n_relocation_state → n_disruption_impact (causes)

---

## Assessment

### 1. Relocation benefit

**PRESERVED ONLY IN TEXT**

`n_savings_realism` was resolved with `newValue: "confirmed"` — this captures the user's acceptance status but loses the exact figure (£2 million) and unit (annual). The resolved node carries no structured £2M/year claim as evidence. This is a regression compared to 59B.2 which preserved `"confirmed £2M annual saving"` with more precision.

### 2. Two-engineer departure + two-month delay

**PARTIALLY REPRESENTED**

Both consequences are embedded in `n_disruption_impact`'s description:
> "losing two senior engineers and facing a two-month delivery slowdown"

However, they are bundled into one unknown node (same pattern as 59A.1) and neither is treated as a known observation — they're both subsumed under an uncertainty about "cost consequences." This means the engine could not investigate each independently nor distinguish known-from-uncertain epistemic states for these two elements.

### 3. Do-nothing recurring cost (£2M/year)

**PRESERVED ONLY IN TEXT**

"continue paying the extra £2 million every year" does not appear as any structural node or edge. The figure is implicitly present only in the trade-off framing within `n_disruption_impact`'s description ("weighed against the confirmed £2M annual savings"). A downstream query looking for a dedicated do-nothing cost node would find nothing.

### 4. Do-nothing benefit (avoid disruption)

**PRESERVED ONLY IN TEXT**

"we avoid that disruption" is not represented in any graph structure. The concept of avoiding disruption is implicit in the trade-off framing but has no node, edge, or explicit structural representation.

### 5. Alternative structure

**NO ALTERNATIVE STRUCTURE**

Only one option (relocate) has any structural representation beyond the starting state node. The do-nothing alternative ("stay put") has zero nodes representing it. The graph contains a single action path with its consequences as an unknown — not two competing alternatives.

### 6. Trade-off linkage

**PARTIALLY LINKED**

The trade-off exists in `n_disruption_impact`'s description text: "so that it can be weighed against the confirmed £2M annual savings." This frames a comparison between consequences and savings. However, neither side of the comparison is an independently retrievable node — the comparison is prose, not graph topology.

### 7. Next question quality

**WEAK**

"What would clarify operational impact of relocation disruption in this situation?" asks about one side of the comparison (relocation's disruption). It does **not** compare both alternatives. A stronger question at this stage would be: "What evidence would determine whether the £2M/year savings outweigh the cost of two senior engineers leaving and a two-month delay?" — which explicitly compares both sides.

---

## Classification: B — TRADE-OFF GOOD, BASELINE STILL IMPLICIT

The engine produced decision-relevant reasoning (trade-off framing within n_disruption_impact) but the do-nothing baseline remains text/context rather than explicit graph structure. This is the **same pattern and same gap as 59B.2** — confirming that the engine does not independently create do-nothing structural nodes when the answer contains them.

### Why:

The update:
1. Correctly resolved savings-realism (✓)
2. Framed a trade-off question about disruption costs (✓)
3. Linked disruption consequences to the relocation state (✓)
4. Did **not** create a do-nothing cost node (✗)
5. Did **not** represent the do-nothing benefit as structure (✗)
6. Created only one action path, not two alternatives (✗)

### What the engine understood correctly:

1. **Resolution of savings-realism:** Correctly resolved based on "real" language.
2. **Trade-off framing:** The unknown node describes consequences that should be "weighed against" savings — this shows the engine grasps the decision context.
3. **Decision relevance:** Chose to investigate impact consequences rather than precision-chasing the two-month estimate.
4. **Causal linkage:** Created a `causes` edge from relocation state to disruption impact.

### What it flattened or omitted:

1. **Do-nothing baseline:** Both do-nothing cost and benefit disappeared from structural representation entirely. This is the experiment's primary failure mode.
2. **Consequence granularity:** Engineer departure and delivery delay remain bundled in one unknown (same class as 59A.1).
3. **Figure preservation:** £2 million/year reduced to just "confirmed" — no amount or unit preserved on the resolved node.
4. **Alternative representation:** The graph only represents the action path, not both options of the decision.

### What uncertainty it chose to pursue next:

`n_disruption_impact` — quantifying the operational impact consequences of relocating. This is one side of the comparison, not the full trade-off itself.

### Does that question compare the alternatives or only examine one side: ONE SIDE ONLY

The question "What would clarify operational impact of relocation disruption?" examines only the action (relocate) side. It does not explicitly compare relocate vs stay-put. A follow-up investigation step would be needed to bring both sides into a comparison structure.

---

## Comparison to 59B.2

| Criterion | 59B.2 | 59B.3 |
|-----------|-------|-------|
| Savings preserved | YES (confirmed £2M annual saving) | PARTIAL ("confirmed" only, no figure/unit) |
| Known consequence preserved as observation | YES (observation node) | NO (bundled into unknown) |
| Bounded downside preserved | YES (in observation desc.) | PARTIAL (in unknown desc., bundled) |
| Do-nothing baseline | SEMANTIC ONLY | ABSENT FROM GRAPH STRUCTURE |
| Do-nothing benefit | IMPLICIT IN TRADE-OFF | ABSENT FROM GRAPH STRUCTURE |
| Alternative structure | ONE ACTION + NET-BENEFIT NODE | SAME — NO SEPARATE BASELINE |
| Decision-relevance reasoning | YES | YES (trade-off framing) |
| Next question quality | GOOD (net benefit evidence) | WEAK (one side only) |

**Key difference:** 59B.3 lost the engineer departure from being a structural observation node and bundled it into an unknown. It also lost the precise £2M figure on the resolved node. The do-nothing baseline gap persists identically.

---

## What this establishes:

1. **The do-nothing baseline gap is stable** across repeated runs — 59B.2 and 59B.3 both show the same pattern where "stay put" consequences remain text, not structure.
2. **The engine frames trade-off reasoning** when presented with explicit alternatives, even without a dedicated do-nothing node.
3. **Known consequences can collapse into unknowns** when bundled together — 59B.3 lost the observation-vs-unknown distinction seen in 59A.3 and 59B.2.

## What this does NOT prove:

1. **Stability of consequence granularity** — one run only; the bundling of engineer departure + delivery delay may or may not persist across runs.
2. **Whether the engine can represent both alternatives** in a different scenario where do-nothing is framed differently.
3. **Cross-domain generalisation** — single domain case only.
4. **Whether answerMeaning fields capture the baseline** — updateOnly mode doesn't print these on the accepted path (unknown whether they contain baseline information).

---

Production code changed: NO