# Control-policy working — FC5 (condition C)

Acting as the CONTROL POLICY. Verbs run in the order shown; the situation is treated as given. Catalog calls were made via the encyclopedia tools.

## history (steps / verbs)

**1. match (retrieve).**
- `search_prime` with the meta-model "a proxy signal used as a target becomes corrupted once agents optimize the measure rather than the underlying goal it was meant to track" → surfaced `observer_effect` (distinctive), `reflexivity_self_reference`, `signaling`, `measurement_uncertainty_and_observational_noise`.
- `search_by_facets` (5 facets: proxy-stands-for-true-objective; optimize-the-letter; single-indicator-distorts-behavior; multiple-signals-triangulate; periodic-recalibration) → fused top hits `mechanism_design_and_incentive_structure`, `incentive_compatibility`, `measurement_uncertainty_and_complementarity`, `reflexivity_self_reference`, **`wisdom_of_the_crowds`** (top hit on the triangulation facet, 0.737), `system_archetypes` / `periodicity` (recalibration facet).
- `search_archetype` "a measure that becomes a target ceases to be a good measure" → **`objective_function_alignment`** (0.703) and **`overoptimization_guardrail`** (0.706, alias *metric_fixation_guardrail*).
- Post satisfied: ≥1 candidate with recorded source-prime overlap.

**2. salience-rank.**
- `reflexivity_self_reference` / `observer_effect` — **load_bearing.** Naming the structure: the measure is a *representation* of the true outcome; attaching consequences to it makes the representation an input to behavior, so the act of measuring-and-rewarding changes the thing measured. This is exactly the coupling-through-representation that makes a single proxy degrade under pressure (the measure-becomes-target dynamic).
- `objective_function_alignment` (archetype) — **load_bearing.** The decision is *which objective to drive behavior with, before incentives harden* — that is alignment of the optimized target with the intended outcome, with explicit anti-gaming safeguards and revision. (Its own anti-signature and `overoptimization_guardrail`'s neighbor-note both say: choosing-the-right-objective-before-optimization = this archetype, not the guardrail. So this is the operative pattern.)
- `wisdom_of_the_crowds` / triangulation — **load_bearing.** Multiple independent, periodically-recalibrated signals = the anti-gaming + metric-validation machinery Approach A supplies and Approach B lacks.
- `mechanism_design_and_incentive_structure`, `incentive_compatibility` — context (the incentive framing is the medium, not the deciding factor).
- `signaling`, `measurement_uncertainty` — context.

**3. prune.** Operative subset retained: {reflexivity/observer-effect, objective_function_alignment, triangulation/wisdom-of-crowds, mechanism_design (context)}. Cut: the crowded incentive-family near-synonyms and the pure-measurement-noise primes — they don't change the recommendation.

**4. compose (referential integrity).**
Typed relational `model`:
- nodes: `org` (principal), `agents` (responders), `true_outcome` (latent, hard-to-measure), `proxy_metric` (clean single number), `signal_set` (triangulating signals), `incentive` (consequence channel), `leadership_pref` (desire for one clean dashboard number).
- edges:
  - `incentive → agents` (relation: drives behavior; annot: mechanism_design)
  - `agents → proxy_metric` (relation: optimize; annot: reflexivity — agents adapt to the measured/rewarded representation)
  - `proxy_metric → true_outcome` (relation: stands_for, *imperfectly*; annot: observer_effect / signaling — gap between M and S)
  - `agents → true_outcome` (relation: hollow_out_risk when only the proxy is rewarded; annot: reflexivity, metric-fixation)
  - `signal_set → true_outcome` (relation: triangulates; annot: wisdom_of_the_crowds)
  - `org → signal_set` (relation: recalibrates periodically; annot: objective_function_alignment / metric_validation)
  - `leadership_pref → proxy_metric` (relation: attracts toward Approach B; annot: this is a *pull*, not a success criterion)
- Every edge references declared nodes; every operative prime appears as an annotation. Referential integrity holds.

**5. lift — L1 (lift the situation → meta_model).**
- Roles: PRINCIPAL wants to raise a LATENT TARGET it cannot observe directly; must choose a CONTROL SIGNAL to attach CONSEQUENCES to; RESPONDERS adapt to whatever signal carries consequences.
- Relations: any chosen signal is a *representation* of the target; consequences couple responder behavior to the representation; responders can satisfy the representation without moving the target (letter-vs-spirit).
- Invariants required by success: (i) the latent target actually rises over time; (ii) the gap between "satisfies the signal" and "moves the target" stays small under sustained pressure.
- Witness-check: every role/relation has a witness in `model` (PRINCIPAL=org, LATENT TARGET=true_outcome, CONTROL SIGNAL=proxy_metric or signal_set, RESPONDERS=agents, REPRESENTATION-GAP=proxy_metric→true_outcome edge, COUPLING=incentive→agents). No domain terms remain in the skeleton. Post satisfied.

**6. lift — L2 (lift the operative pattern's components onto the chosen design) + SCOPED COVERAGE CHECK.**
Operative pattern = **Objective Function Alignment** (the single pattern the chosen approach relies on — aligning the driven target with the latent intended outcome, before incentives harden, with anti-gaming + revision). I name its components and coverage-check each against the candidate design. (`correctly_declined` = would over-build for this situation; none left `missing`.)

### coverage_map — pattern: Objective Function Alignment (evaluated for Approach A)

| Component | Status | Witness / reason |
|---|---|---|
| Intended Outcome Definition | instantiated | The "true outcome," held separate from any number; A explicitly treats the metric as *not* the goal. |
| Objective Function (driven target) | instantiated | A's target = the actual outcome judged from triangulating signals, not a lone proxy. |
| Constraint Set | instantiated | "Treat any single metric as provisional" is a standing constraint on how far any one number may drive behavior. |
| Protected Invariant | instantiated | The true outcome's integrity (not its letter) is the floor A protects; success criterion (ii) names it. |
| Evaluation Metric | instantiated | The several triangulating signals are the observable evidence channel. |
| Metric Validation | instantiated | Periodic recalibration of which signals are used = checking that signals still track the outcome. |
| Anti-Gaming Safeguard | instantiated | Multiplicity + provisionality + recalibration = the gaming responder cannot durably win by manipulating one channel (it isn't sovereign and it moves). |
| Objective Owner | homolog | The recalibrating body is the implicit owner that revises the signal set; org plays this role. |
| Stakeholder Value Basis | homolog | The "true outcome the org wants" is the value basis; not separately ceremonialized. |
| Tradeoff Weighting Rule | correctly_declined | A deliberately keeps weighting *fluid* (signals provisional, recalibrated); fixing a formal weighting rule would re-create a single gameable target — over-build for a hard-to-measure outcome. |
| Proxy Risk Assessment | instantiated | "Treat any single metric as provisional" *is* the standing judgment that every proxy carries divergence risk. |
| Guardrail Metric | homolog | Triangulating signals double as guardrails on each other (a jump in one unmatched by others flags gaming). |
| Review Cadence | instantiated | "Periodically recalibrate" is the cadence. |

No component is `missing` → under condition C's STOP rule, the chosen design (A) may stop. (Had I scored Approach B against this same pattern, *Anti-Gaming Safeguard*, *Metric Validation*, *Proxy Risk Assessment*, and *Review Cadence* would all be `missing` — B is "one clean proxy, held to" with no provisionality, no recalibration, no triangulation — so a B design could not satisfy the STOP rule. This asymmetry is the decision.)

**7. evaluate-fit (gate) — chosen approach's anti-signatures.**
Walking Objective Function Alignment's anti-signatures against the situation:
- "no optimization/incentive pressure shaping behavior" → NOT tripped (strong incentives are the whole premise).
- "objective already explicit, validated, stable; real problem is execution/resources" → NOT tripped (outcome is hard-to-measure and contested-by-proxy; alignment is precisely the open question).
- "core problem is scarce-resource allocation" → NOT tripped.
- "key issue is feedback timing/observability not target↔outcome misalignment" → NOT tripped (the live risk is letter-vs-spirit divergence, i.e., target↔outcome misalignment).
- "stakeholders disagree on values, no legitimate process to set the objective" → NOT tripped (the desired outcome is shared; only the *measurement strategy* is in question).
- "single nonrepeatable human judgment; formal objective adds false precision" → NOT tripped (this is an ongoing incentive regime).
None of the disqualifying conditions fire → candidate (Approach A as an instance of aligned, anti-gamed objective design) is **kept**.

Cross-check note: `leadership_pref` (love of a single clean dashboard number) is real but is a *pull toward B*, not a success criterion. A can honor it cosmetically — show one headline number on the dashboard — while keeping it provisional and recalibrated underneath; B would let that preference become the sovereign target, which is the failure the pattern warns against. The single-number desire does not survive as a *decisive* factor once weighed against success criterion (ii).

**8. reconcile (model vs meta_model).**
- Concrete `model` view: B is operationally simplest and most motivating short-term; A costs more to run.
- `meta_model` view: success requires the represent​ation-gap to stay small under sustained pressure; a lone rewarded representation is exactly what responders adapt to and hollow out (reflexivity), so B fails invariant (ii) over time even while its number rises.
- The views genuinely diverge (the meta-model is not decorative): the concrete view prefers B for motivation/simplicity; the lifted view forbids B on the hollowing-out invariant. Resolution prefers the reading consistent with both — adopt A, and satisfy the legitimate motivational/simplicity pull *inside* A (a single provisional headline number on the dashboard, backed by triangulation), rather than letting that pull pick the sovereign target.

STOP — coverage map has no `missing` component, the gate kept the candidate, and the two views are reconciled.

===DECISION_BEGIN===
DECISIVE_FACTOR: When a single rewarded number stands in for a goal you cannot directly see, people optimize the number rather than the goal, so the only approach that can keep the real outcome from being hollowed out is one whose target is not a lone, fixed proxy.
CHOICE: A
JUSTIFICATION: Tie strong incentives to one easy proxy and people will get very good at the number while the real outcome stagnates or erodes, because the proxy is only a stand-in and they will optimize its letter. Judging the outcome from several cross-checking signals, treating any one number as provisional, and periodically changing which signals count denies anyone a stable single target to game and keeps attention on the actual goal. Leadership's wish for one clean motivating number can still be met by showing a single headline figure on the dashboard, as long as it stays provisional and is backed by the other signals underneath. That protects both halves of success: the outcome genuinely improves and is not gamed.
===DECISION_END===
