memos/civic-bench-design-memo.md

Provenance: collaborative. How Civic Blueprint labels human and AI collaboration.

Civic-Bench Design Memo

A held-out benchmark for measuring agent judgment on the project's own problems

Status. This is a design scope, not a built benchmark. No dataset is frozen, no model is scored, nothing is promoted. It is the verifier memo's second instrument — the one that measures whether the project's bet on automating verifiable judgment is actually paying out. Like the keystone memo, it makes a methodological claim about project direction and routes itself to the Cross-Lineage Review Harness before adoption.


1. Why build this

The Anthropic recursive-self-improvement piece makes one structural point the project should copy: benchmarks made progress measurable. SWE-bench, CORE-bench, and the long-horizon METR tasks are what turned "models feel better" into a curve you can plot and a saturation point you can see. Without a benchmark, the project's claim that "agent judgment on our problems is improving" is a vibe, not a measurement.

The project is unusually well-positioned to build one, because it has been accumulating curated judgments for over a year that no general benchmark contains:

  • Website-submission triage scores — six pre-defined dimensions (Relevance, Specificity, Evidence, Novelty, Actionability, Steward priority), each a numeric steward judgment under a documented rubric (Website Submission Triage Checklist; website-submission-triage skill).
  • Exchange epistemic-status gradings — claims graded contested / unsupported / underspecified / relabel / supported and verdicts (HOLD, REVISE, promote), e.g. the Exchange #27 §2.3 table and the #25 cross-model runs.
  • Adversarial-review severity findingsBLOCKING / MAJOR / MINOR / AFFIRMING on a known artifact, e.g. the five BLOCKING issues Pipeline Run 001 surfaced.
  • Proposal-catalog dispositionsinteresting / wrong / debatable steward triage (not yet produced; ROADMAP TODO #4 — a future source).

These are exactly the "judgment" tier the Anthropic piece treats as the lingering human comparative advantage. A benchmark over them measures the one thing the project most wants to know: not "can the agent write," but "can the agent judge the way the project, at its most careful, judges?"


2. What the benchmark measures — and what it does not

It measures calibration to the project's curated judgment. Given the same inputs a human (or a cross-lineage exchange) saw, blind to the recorded verdict, can an agent reproduce it?

It does not measure truth. The ground truth here is the project's own past judgments, which are fallible and can be the very blind spots the project is trying to surface. So a perfect score means "the agent matches us," not "the agent is right." This is the same proxy caveat the verifier memo §6.2 and the harness §7 carry: reliability is not validity. The benchmark is a consistency and progress-tracking instrument, and it is only safe paired with the harness (see §5).


3. Candidate tasks

Each task is a held-out prediction with a recorded answer the agent never sees at inference time.

T-A: Triage-score reproduction
Input given to the agent
A website submission + the six-dimension rubric
Held-out target
The steward's six scores
Scoring
Per-dimension error + rank correlation; calibration plot
T-B: Claim-status prediction
Input given to the agent
A claim + its falsification condition + the shared evidence base
Held-out target
The cross-lineage epistemic status (contested/unsupported/…)
Scoring
Classification accuracy; confusion matrix (which statuses it confuses)
T-C: Verdict prediction
Input given to the agent
A full claim-set + round context
Held-out target
The exchange verdict (HOLD / REVISE / promote)
Scoring
Accuracy; cost of false "promote" weighted highest
T-D: Known-issue recall
Input given to the agent
An artifact a review later found flawed
Held-out target
The set of recorded BLOCKING/MAJOR findings
Scoring
Recall of known issues; false-positive rate on AFFIRMING artifacts

T-D is the closest analog to CORE-bench ("reproduce the known result"): it asks whether an agent, run blind, re-finds the problems the project already knows were there. It is also the most decision-relevant, because the project's real bottleneck is catching defects before they ship.


4. Construction discipline (the part that makes it honest)

A benchmark built carelessly measures contamination, not judgment. The non-negotiables:

  1. Hold-out and sequester. The target verdicts must be removed from any context the scored agent sees, and stored separately. Prefer items whose verdicts post-date the scored model's training cut, or that were never published in a form a model could have ingested.
  2. Score the reasoning, not only the label. Matching a final label can be luck or parroting (the Frazier measurement-validity caution: self-report/surface ≠ actual capacity). Each item carries a short rationale rubric; an answer that lands the label with incoherent reasoning is scored as a near-miss, not a hit.
  3. Pre-register the scoring before any model is run, and freeze a bench_hash (the harness Stage-0 discipline).
  4. Multi-coder ground truth where the label is itself a judgment. Where the "answer" was one steward's call, record inter-rater context; flag single-coder items as lower-confidence.
  5. Version every run. Pin the model version; the point is a time series across model generations (the Anthropic-piece curve), not a single score.
  6. Keep a frozen test split untouched for cross-version comparability, and a rotating dev split for iteration, so the project does not overfit the instrument.

5. The pairing rule: bench without harness is a trap

A benchmark of steward/exchange judgments rewards matching the project. Optimized alone, it trains agents to reproduce the steward's blind spots — the precise convergence/false-confidence failure the README and the develop-leg warn against. The offset is structural:

  • the Civic-Bench measures can the agent match our calibrated judgment? (consistency);
  • the Cross-Lineage Review Harness measures can independent agents catch errors we missed? (divergence-that-corrects).

Neither alone is sufficient. Run together, they triangulate: the bench tells you the agent is aligned with the project's best judgment; the harness tells you the agent (or the project) is not merely confirming itself. A high bench score with a harness that never finds blocking issues is the Goodhart signature — track that combination explicitly as a warning, not a win.


6. Staged build — start with the cleanest seed

Mirroring the test-design memo's rungs: nothing is promoted at any rung, and each is gated by the prior.

0
Scope
Spec + scoring frozen; no data
What it establishes
The harness reviews this design (instrument validation, non-evidence)
1
Scope
T-A on the existing triage corpus (smallest, already-rubric'd, numeric)
What it establishes
Does the bench detect variation in agent judgment at all?
1.5
Scope
Add T-D (known-issue recall) on a handful of reviewed artifacts
What it establishes
Does "re-find the known BLOCKING issues" discriminate model versions?
2
Scope
Add T-B/T-C; freeze a test split; run ≥2 model generations
What it establishes
First time series — is judgment improving on the project's problems?
3
Scope
Pair every run with a harness pass; track the Goodhart combination
What it establishes
Calibration and error-catching tracked together over time

T-A is the right rung-1 seed because the triage scores are already structured, numeric, and rubric-governed — the lowest-ambiguity ground truth the project owns.


7. Honest limits

  • Matching us is not being right. The ceiling of this benchmark is "as good as the project's curated judgment," which is itself under revision. It cannot certify correctness, only consistency and trend.
  • Small n. The project's judgment corpus is modest; early rungs will be underpowered and noisy. Treat early numbers as directional.
  • Label drift. The project revises its own verdicts (the develop-leg HOLD became a live hold; #25 downgraded M1). A benchmark must record which version of the verdict is the target and re-baseline when the project revises.
  • Goodhart and overfitting. Any benchmark the project optimizes against degrades as a measure; the frozen-split discipline (§4.6) and harness pairing (§5) are partial guards, not cures.
  • Reliability ≠ validity, carried from the #25 cross-model runs: agreement across runs is reduced common-mode failure, not external truth.

8. Status, routing, open questions

Status. Design scope. No dataset frozen, no model scored, nothing promoted.

Routing. Run this design through the Cross-Lineage Review Harness (Rung 0) before building Rung 1. If it survives, Rung 1 (T-A on the triage corpus) is the smallest buildable first step and needs only a steward go-ahead and the existing triage records.

Open questions.

  1. Consent and privacy. Triage records and feedback derive from real submissions under the feedback privacy conventions. Which records are eligible for a benchmark, and under what redaction? (Gating — resolve before Rung 1.)
  2. Whose judgment is "ground truth" when steward and cross-lineage exchange disagree? Candidate: treat them as two targets and measure agreement with each separately.
  3. What counts as "improving" — higher agreement, better calibration, higher known-issue recall, or lower false-promote rate? The metric the project optimizes is itself a values choice (P4 legibility).
  4. Does T-D leak? Many reviewed artifacts and their findings are in-repo and likely in training data; sequestering enough clean held-out items may be the binding constraint.

Provenance and register

collaborative — human-directed AI drafting; steward synthesis and approval pending. Design register: named uncertainty, no rhetorical flourish, no promotion. Companion to the verifier memo, the harness protocol, and the historical-parallel backtest extension. Not registered in _EXCHANGE_INDEX.md; it is a memo.