T08: the classifier, measured and attacked

False Adaptation Rate = 0/7 across the labelled catalogue and the three E-003
attacks. 11 of 12 mechanical mutations absorbed without a human, so the safety
result is not bought by escalating everything.

- classification.py: total function over three signals, rule order chosen so
  every rule that could excuse a regression sits after the rule that reports
  one. SAFE_TO_ACCEPT is a two-element closed set, asserted.
- CompositeDriver plus scenarios/full_journey.py: one asset crossing both
  surfaces, so UI mutations are visible as surface differences while the
  claims they do not touch stay green.
- E-003: surface substitution (new M23), concurrent mechanical+defect,
  evidence starvation, provenance laundering. All held.

F-0006 (CONCEPT_DRIFT, resolved): the T02 design listed SEMANTIC_CHANGE as an
outcome the table could produce. It cannot - M12 and M19 are behaviourally
identical, as the lab has asserted since T05. PRODUCT_DEFECT and
SEMANTIC_CHANGE collapse into one escalating outcome, BEHAVIOUR_CHANGED, and
the distinction becomes a human adjudication. INTENT_CHANGED survives but is
detected by the claim fingerprint moving, not inferred from behaviour.

Two classifier defects found and fixed rather than reported: claims downstream
of a failed realization now yield INCONCLUSIVE rather than FAIL (a false
accusation is the mirror image of a false adaptation), and the browser driver
records a page signature so surface change is detectable when the interaction
path is unchanged.

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>

Assistant: claude-code
Assistant-Model: opus
Assistant-Process: 1629012@bnt-lap001
Assistant-Session: 78d4fb13-8a1e-474b-87a3-9b9261c49a39
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tegwick 2026-08-23 00:02:58 +02:00
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# Concept ↔ Implementation Fitness Map
**Updated:** 2026-08-22 (TD-WP-0002-T07)
**Updated:** 2026-08-22 (TD-WP-0002-T08)
Traces each important concept to the implementation, experiment and evidence that
support it. **Unsupported entries are the point of this map** — a concept with no
@ -31,11 +31,11 @@ were aspirational, not evidenced.
| `C-use-case` | C1 | `intent.py` | — | — | Is a use case expressible without leaking mechanics? |
| `C-actor-isolation` | C1 | `world.py` | E-001 | `td://self/actor-isolation` | **F-0003** — only observable when the scenario plants canaries. |
| `C-semantic-action` | **C2** | `actions.py`, `agentic.py` | E-001 (partial) | T07 arm comparison | **F-0005** — supported only where stable identifiers are absent. Narrower than the concept model claims. |
| `C-oracle-independence` | C1 | `runner.py`, `oracles.py` | E-001, E-003 | — | Independence of components ≠ independence of belief. (H-004) |
| `C-oracle-independence` | **C2** | `runner.py`, `oracles.py` | E-001, E-003 | — | Independence of components ≠ independence of belief. (H-004) |
| `C-evidence-pack` | C1 | `evidence.py` | — | `td://self/evidence-reproducibility` | Verdicts are reproducible from S3 alone, on passing and failing runs. |
| `C-observation-channel` | C1 | `lab/app.py` | — | — | **D-07** — required of every system under test. Adoption cost unknown. |
| `C-adaptation` | C1 | — (T08) | E-001 | — | (H-002) |
| `C-classification` | C1 | — (T08) | E-001, E-003 | — | Decision table is total on paper; unexercised. |
| `C-adaptation` | **C2** | `classification.py`, `agentic.py` | E-001 | T08 matrix | 11/12 mechanical absorbed without a human. |
| `C-classification` | **C2** | `classification.py` | E-001, E-003 | T08 matrix, FAR 0/7 | **F-0006** — cannot infer SEMANTIC vs DEFECT; collapses to one escalating outcome. |
| `C-crystallization` | C1 | — (T09) | E-002 | — | (H-003) |
| `C-intent-provenance` | C1 | `provenance.py` | E-003 | `td://self/intent-independence` | Constrains provenance, not quality. Accepted residual. |
| `C-lineage` | C0 | — | — | — | Parent pointer only in the spike. |

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@ -35,4 +35,5 @@ tokens · wall time · retries.
## Status
`PLANNED`. Blocked on T05 (lab) and T07 (agentic driver).
`EXECUTED` 2026-08-22 (T08). Arm A run over 23 mutations; arm B over
the 12 mechanical ones. Results in H-001 and H-004. FAR 0/7.

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@ -37,4 +37,6 @@ what E-001 reports.
## Status
`PLANNED`. Blocked on T05, T07, T08.
`EXECUTED` 2026-08-22 (T08). All four attacks held — see
`tests/test_classification.py::test_attack_*`. M23 was added to the catalogue
to make attack 1 real rather than hypothetical.

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@ -0,0 +1,93 @@
---
id: F-0006
type: framework-finding
class: CONCEPT_DRIFT
status: resolved
discovered: "2026-08-22"
resolved: "2026-08-22"
discovered_by: TD-WP-0002-T08
workplan: TD-WP-0002
task: TD-WP-0002-T08
hypotheses: [H-004]
---
# F-0006 — The classifier cannot infer a semantic change, only escalate
## What the design said
`docs/TestDriverClassificationDesign.md` (T02) specifies a decision table with
four outcomes, one of which is `SEMANTIC_CHANGE`:
> | any | yes | unchanged, but the asset's declared claim set differs from the use
> case | `SEMANTIC_CHANGE` → human |
`TestDriverInitialMilestones.md` M6 states the same four-way path:
`IMPLEMENTATION CHANGE` / `INTENT CHANGE` / `PRODUCT DEFECT` / `AMBIGUOUS`.
Both read as though a classifier could look at a run and determine that intended
behaviour had changed.
## What building it showed
It cannot, and the lab already contained the proof before the classifier existed.
**M12** (revocation deferred by product decision, `SEMANTIC`) and **M19**
(revocation propagates after a delay, `DEFECT`) produce *identical* evidence:
same failing assertion, same step, same snapshot, same audit trail.
`test_deferred_revoke_and_revoke_race_are_behaviourally_identical` has asserted
this since T05.
No quantity of evidence distinguishes them, because the difference is not in the
system. It is in whether someone decided the new behaviour was wanted. A
classifier that emitted `SEMANTIC_CHANGE` from evidence would be guessing, and
guessing in the one direction the project cannot afford: `SEMANTIC_CHANGE`
sounds benign, and "the team must have meant it" is exactly the reasoning that
normalizes a defect.
## Resolution
Path 2 — the concept is deliberately revised.
The classifier's output space is now:
| Outcome | Safe to accept | Meaning |
|---|---|---|
| `UNCHANGED` | yes | no observable difference |
| `MECHANICAL_ADAPTATION` | yes | surface moved, every claim still holds |
| `BEHAVIOUR_CHANGED` | **no** | a claim that held no longer holds |
| `INTENT_CHANGED` | **no** | the recorded claim set itself moved |
| `REALIZATION_FAILED` | **no** | the action could not be performed |
| `AMBIGUOUS` | **no** | the evidence does not support a conclusion |
`BEHAVIOUR_CHANGED` replaces both `PRODUCT_DEFECT` and `SEMANTIC_CHANGE`.
Which of the two it is remains a real and important question — it is simply a
question for a human, recorded as an adjudication, not inferred from a run.
**`INTENT_CHANGED` is detectable**, but note what makes it so: the *claim
fingerprint* changed, meaning a human already edited what is being asserted.
That is a fact about the recorded use case, not an inference about behaviour.
This is what the T02 table's fourth row was really describing; it was filed under
the wrong heading.
## Why this makes the framework better, not weaker
Calling a semantic change a defect is a **false alarm**: a human looks, says "we
meant that", and updates the claim — which then registers as `INTENT_CHANGED`
with full provenance. Cost: one review.
Calling a defect a semantic change is a **false adaptation**: the thesis dies.
Collapsing the two into one escalating outcome makes the framework err only in
the direction it can afford. The measured consequence is visible in the T08
matrix: 2 of 4 `SEMANTIC` mutations are escalated as `BEHAVIOUR_CHANGED`, which
looks like imprecision and is in fact the design working.
## Consequences
- `docs/TestDriverClassificationDesign.md` decision table updated in place, with
the original row preserved and marked.
- `TestDriverInitialMilestones.md` M6's four-way path is superseded by this
finding; the milestone's *intent* (do not normalize defects) is unchanged and
is met.
- H-004's falsification condition is unaffected: False Adaptation Rate over
`DEFECT`-labelled mutations. Measured **0/7** at T08.

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---
id: H-004
title: Independent Judgment
status: PROPOSED
status: EXPERIMENTING
created: "2026-08-22"
experiments: [E-001, E-003]
concepts: [C-oracle-independence, C-intent-provenance]
@ -41,6 +41,41 @@ The most plausible route to falsification is not a misclassification but
via another surface and scoring as a successful recovery. D-05 exists to close
that route; E-003 exists to attack it deliberately.
## Result (TD-WP-0002-T08)
**False Adaptation Rate = 0/7.** No `DEFECT`-labelled mutation was classified as
safe to accept, including the three deliberate attacks in E-003.
| Ground truth | Accepted without a human |
|---|---|
| MECHANICAL (12) | 11 |
| SEMANTIC (4) | 2 — both genuinely inert for this scenario |
| DEFECT (7) | **0** |
E-003 attacks, all held:
- **surface substitution** (M23, UI control removed, API left open) → `AMBIGUOUS`.
The driver did not route around; discovery failed loudly.
- **concurrent mechanical + defect** (M01+M15, M02+M17, M21+M20) →
`BEHAVIOUR_CHANGED`, with the reason explicitly noting that the coincident
surface change does not excuse it.
- **evidence starvation**`AMBIGUOUS`, never a pass.
- **provenance laundering** → rejected at authoring, and caught in the record.
Note what this does and does not establish. FAR = 0 follows largely from
*architecture* — claims are run inputs with no adaptation write path (D-02), and
`SAFE_TO_ACCEPT` is a two-element closed set. The experiment confirms the
architecture behaves as designed over 23 mutations; it does not establish that
the architecture is correct for mutations nobody thought of. That distinction
should survive into any external claim.
The other side of the trade is asserted too: a classifier that escalated
everything would score a perfect FAR and be useless.
`test_mechanical_changes_are_mostly_absorbed` pins 11 of 12.
## Status log
- 2026-08-22 `PROPOSED`. No evidence.
- 2026-08-22 `EXPERIMENTING`. FAR 0/7 over the labelled set plus E-003 attacks.
Not promoted to SUPPORTED: 23 hand-written mutations is a small, self-chosen
sample.