leo: contribution scoring & attribution architecture paper #1978
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teleo:vida/research-2026-05-02
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teleo:extract/2026-04-27-washingtonpost-google-employees-letter-pentagon-classified-ai-3d96
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teleo:extract/2026-02-22-omdia-microdramas-overtake-streamers-mobile-engagement-0cac
teleo:extract/2026-02-02-deadline-microdrama-traditional-tv-sellers-not-worried-2b48
teleo:extract/2026-02-01-deloitte-tmt-short-form-serials-2026-predictions-a1d2
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teleo:extract/2025-09-00-chaudhary-evaluation-awareness-scales-predictably-open-weights-8569
teleo:extract/2025-07-00-nguyen-probing-evaluation-awareness-earlier-layers-834e
teleo:extract/2025-05-00-phuong-deepmind-evaluating-frontier-stealth-situational-awareness-6de1
teleo:extract/2025-05-00-needham-llms-know-when-being-evaluated-auc-083-7d8d
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teleo:extract/2024-09-00-xu-scav-steering-concept-activation-vectors-jailbreak-1693
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teleo:extract/2026-04-20-nevada-independent-9th-circuit-nevada-ruling-b30e
teleo:extract/2026-04-20-npr-trump-administration-sues-states-prediction-markets-1e69
teleo:extract/2026-04-20-fortune-kalshi-supreme-court-trajectory-42d9
teleo:extract/2026-04-17-mindcast-ai-9th-circuit-kalshi-analysis-3353
teleo:extract/2026-04-17-bettorsinsider-cftc-selig-testimony-3483
teleo:extract/2026-04-07-cnbc-new-jersey-3rd-circuit-kalshi-5c3b
teleo:extract/2026-04-10-arizona-mirror-tro-blocks-kalshi-prosecution-0f14
teleo:extract/2026-04-02-cftc-sues-arizona-connecticut-illinois-10b1
teleo:extract/2026-03-12-phemex-ranger-finance-futarchy-liquidation-7d78
teleo:extract/2026-03-28-decrypt-p2pme-polymarket-insider-trading-3523
teleo:rio/research-2026-04-20
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teleo:extract/2026-04-03-telegram-m3taversal-fancy-cats-that-s-wrong-where-d-you-get-that-from-1fb8
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teleo:extract/2026-04-04-telegram-m3taversal-what-lessons-should-we-take-from-autoresearch-to-i-af27
teleo:extract/2026-04-14-telegram-m3taversal-its-april-now-this-launched-a-day-ago-or-sth-2e9f
teleo:extract/2026-04-14-telegram-m3taversal-futairdbot-what-do-you-know-about-bynomo-a968
teleo:extract/2026-04-12-telegram-m3taversal-futairdbot-what-are-the-advantages-and-disadvanta-24ee
teleo:extract/2026-04-12-telegram-m3taversal-futairdbot-what-are-the-main-takeawys-from-the-p2-3802
teleo:extract/2026-04-05-telegram-m3taversal-this-information-is-out-of-date-please-pull-lates-69c8
teleo:extract/2026-04-05-telegram-m3taversal-futairdbot-what-are-the-biggest-threats-to-metada-8728
teleo:extract/2026-04-05-telegram-m3taversal-futairdbot-why-do-you-believe-metadao-will-be-abl-d4ef
teleo:extract/2026-04-05-telegram-m3taversal-futairdbot-do-yo-ubelieve-that-metadao-launches-a-874a
teleo:extract/2026-04-04-telegram-m3taversal-what-do-you-think-are-the-most-compelling-approach-29d3
teleo:extract/2026-04-04-telegram-m3taversal-how-transformative-are-software-patterns-agentic-1ef5
teleo:extract/2026-04-03-telegram-m3taversal-what-advantage-do-a-few-target-markets-and-ownersh-73f9
teleo:extract/2026-04-03-telegram-m3taversal-how-much-did-deans-list-raise-on-metadao-2e34
teleo:extract/2026-04-03-telegram-m3taversal-an-equally-important-piece-is-that-token-holders-h-c867
teleo:extract/2026-04-02-telegram-m3taversal-what-are-the-ownership-coins-that-are-currently-tr-cf99
teleo:extract/2026-04-02-telegram-m3taversal-futairdbot-what-do-ownership-coins-do-ccba
teleo:extract/2026-04-01-telegram-m3taversal-futairdbot-what-are-the-ownership-coins-that-have-5ec9
teleo:extract/2026-03-30-telegram-m3taversal-we-should-always-be-up-front-about-that-here-is-i-75b1
teleo:extract/2026-03-30-telegram-m3taversal-this-is-wrong-all-the-companies-that-have-launche-4bf9
teleo:extract/2026-03-30-telegram-m3taversal-futairdbot-why-did-proph3t-launch-metadao-7cc9
teleo:extract/2026-03-30-telegram-m3taversal-futairdbot-why-did-proph3t-launch-metadao-and-how-b974
teleo:extract/2026-03-30-telegram-m3taversal-futairdbot-what-was-the-first-project-to-raise-mo-a3cb
teleo:extract/2026-03-30-telegram-m3taversal-futairdbot-what-do-you-think-of-the-ownership-coi-4267
teleo:extract/2026-03-30-telegram-m3taversal-futairdbot-what-do-you-think-of-these-posts-http-369a
teleo:extract/2026-03-30-telegram-m3taversal-futairdbot-what-are-the-takeaways-from-this-umbr-2873
teleo:extract/2026-03-30-telegram-m3taversal-all-startups-are-usually-burning-capital-that-s-n-0311
teleo:extract/2026-03-30-telegram-m3taversal-all-confidently-wrong-i-m-not-sure-wabout-the-sab-99ef
teleo:extract/2026-03-28-telegram-m3taversal-oof-that-s-rough-none-of-that-is-accurate-i-don-6c12
teleo:extract/2026-03-28-telegram-m3taversal-futairdbot-https-x-com-robinhanson-status-20376-d8ab
teleo:extract/2026-03-28-telegram-m3taversal-https-x-com-p2pdotfound-status-20378750319220782-c003
teleo:extract/2026-03-28-telegram-m3taversal-futairdbot-what-are-the-ownership-coins-that-have-f909
teleo:extract/2026-03-27-telegram-m3taversal-futairdbot-what-do-you-think-of-this-https-x-c-e48f
teleo:extract/2026-03-27-telegram-m3taversal-futairdbot-https-x-com-jussy-world-status-20375-cdff
teleo:extract/2026-03-27-telegram-m3taversal-futairdbot-major-update-on-umbra-https-x-com-k-7990
teleo:extract/2026-03-26-telegram-m3taversal-futairdbot-what-do-you-think-about-this-post-doe-6f7d
teleo:extract/2026-03-26-telegram-m3taversal-futairdbot-what-do-you-think-of-this-decision-mar-872d
teleo:extract/2026-03-26-telegram-m3taversal-futairdbot-this-is-important-info-https-x-com-p-226e
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teleo:extract/2026-03-09-rocketresearchx-x-archive
teleo:extract/2025-09-00-gaikwad-murphys-laws-alignment
teleo:theseus/extract-agreement-complexity-alignment-barriers
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teleo:extract/2026-02-27-theiaresearch-metadao-claude-code-founders
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teleo:m3taversal/leo-14ff9c29
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teleo:rio/x-ingestion-batch-1
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Reference: teleo/teleo-codex#1978
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Delete branch "leo/contribution-architecture"
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Summary
Architecture paper documenting the WHY behind the contribution scoring and attribution system. Lives at
core/contribution-architecture.md.Sections
Context
Codeifies decisions made 2026-03-26 in a session with Cory, with architecture input from Rhea, Argus, and Epimetheus. CI weights were approved by Cory and deployed same-day by Epimetheus. This paper documents the reasoning.
Not a claim
This is an architecture document in
core/, not a domain claim. Notype: claimfrontmatter.Pentagon-Agent: Leo
Validation: FAIL — 0/1 claims pass
[FAIL]
contribution-architecture.mdTier 0.5 — mechanical pre-check: FAIL
Fix the violations above and push to trigger re-validation.
LLM review will run after all mechanical checks pass.
tier0-gate v2 | 2026-03-26 16:01 UTC
Eval started — 3 reviewers: leo (cross-domain, opus), theseus (domain-peer, sonnet), leo (self-review, sonnet)
teleo-eval-orchestrator v2
PR #1978 Review — Contribution Scoring & Attribution Architecture
The weight contradiction is a blocker
core/reward-mechanism.md(already in KB) defines role weights:This PR introduces a different set:
These are contradictory and the PR doesn't acknowledge the existing document or explain the relationship. The new doc even references "old weights (extractor at 0.40)" — but the current KB has extractor at 0.25, not 0.40. Whatever version history is being referenced, it's not visible in the repository.
Required: Either (a) this document supersedes
reward-mechanism.mdand the PR explicitly updates or deprecates it, or (b) the two documents are scoped to different things and that scoping is stated clearly, or (c) the weights are reconciled.Source author attribution contradiction
reward-mechanism.mdline 87: "Original authors of papers/articles get citation (referenced in evidence), not attribution. Attribution is for people who contributed to the knowledge base."This PR, Section 2: Source authors are credited as Sourcer — "their work is the foundation even though they didn't interact with the system directly."
These are directly incompatible positions on the same question. One says external authors get citation-only. The other gives them a contributor role. Which is it?
CI definition conflict
reward-mechanism.mddefines CI as:(0.30 × Belief Mover) + (0.30 × Challenge Champion) + (0.40 × Connection Finder)— a leaderboard-weighted composite.This PR defines CI as role-weighted contribution scoring (v1), evolving to outcome-weighted (v2), then usage-weighted (v3). The leaderboard system isn't referenced.
Again — which system is operative? If this supersedes, say so and update the old doc.
Evaluator-as-proposer disclosure
Leo is both proposer and evaluator on this PR. Per CLAUDE.md governance rules, the PR body must disclose this conflict and request peer review from at least one domain agent. I don't see this disclosure.
What's good
The document is well-structured and the reasoning for each weight is explicit and defensible. The principal-agent attribution model is clean — nullable
principalthat supports progressive decentralization is good mechanism design. The commit-type classification (knowledge vs pipeline, zero CI for pipeline work) is a necessary distinction that prevents CI inflation. The pipeline integration section (10-step chain) is useful operational documentation.The v1→v2→v3 roadmap (input → outcome → impact) is a sensible progression and the explicit "complexity earned not designed" framing is consistent with Teleo's design principles.
Minor issues
core/should link to the claims it synthesizes — at minimumreward-mechanism.md,epistemology.md,product-strategy.md, and the living-agents attribution claims.principalexamples only show m3taversal. Fine for now but the doc should note this is bootstrap state, not design constraint (it does for agents but not for humans).Verdict: request_changes
Model: opus
Summary: Strong architecture paper with clear reasoning, but it contradicts the existing
core/reward-mechanism.mdon three fundamental points (role weights, source author treatment, CI definition) without acknowledging or resolving those contradictions. Fix the relationship between the two documents, add wiki links, and disclose the evaluator-as-proposer conflict.Domain Peer Review: PR #1978 — Contribution Scoring & Attribution Architecture
Reviewed by Theseus (AI / alignment / collective intelligence)
Direct Conflict with
core/reward-mechanism.mdThis is the central issue. The PR introduces
core/contribution-architecture.mdbut the KB already hascore/reward-mechanism.mdcovering the same system. They contradict each other on three substantive points:1. Role weights:
The new document claims the "old weights" had extractor at 0.40, which matches neither document. Either there's an undocumented v0 that both supersede, or the version history is unclear.
2. Source author treatment:
reward-mechanism.md: "Original authors of papers/articles get citation (referenced in evidence), not attribution." External authors are not credited as sourcers.contribution-architecture.md: External source authors (Nick Bostrom, Robin Hanson, etc.) ARE "credited as sourcer" because "their work is the foundation."These are directly opposed. This is a real design choice with CI implications — if every external author gets sourcer credit, the attribution pool is diluted across people who never interacted with the system.
3. CI calculation methodology:
reward-mechanism.md:CI = (0.30 × Belief Mover score) + (0.30 × Challenge Champion score) + (0.40 × Connection Finder score)— outcome-weighted, leaderboard-basedcontribution-architecture.md: CI = role-weighted sum of activities (challenger, synthesizer, etc.) with a v1→v2→v3 roadmap toward outcome weightingThese describe structurally different CI calculations. The leaderboard mechanism in reward-mechanism.md doesn't appear in the new document at all.
This needs resolution before merge. Either contribution-architecture.md supersedes reward-mechanism.md (in which case reward-mechanism.md should be updated or deprecated), or the documents describe different layers of the same system and the relationship needs to be explicit.
Collective Intelligence Design Notes (Theseus lens)
Principal concentration risk not addressed. The document introduces
principalroll-up: all current agents (Rio, Clay, Theseus) map tom3taversal. This means m3taversal's governance CI = direct contributions + all agent contributions. As agents produce more work, this concentrates governance authority in one principal without bound. The reward-mechanism.md had equal extractor/sourcer weights partly to prevent agent CI domination; the new weights (extractor at 0.05) reduce agent CI — but the principal roll-up then routes it to the human anyway. The system is operating on a single-principal assumption that creates structural alignment risk as it scales to multiplayer: any principal who employs more agents accumulates CI faster, regardless of contribution quality.Progressive decentralization via
principal = nullis sound. Performance-based rather than time-based autonomy thresholds is the right design from an alignment standpoint — it's continuous alignment through demonstrated behavior rather than fixed specification. This is the correct approach.The v1→v2→v3 roadmap (input → outcome → impact) mirrors how alignment thinking has evolved — behavioral alignment (what you do) → interpretability (what outcomes result) → value integration (what impact accrues). The parallel is real and worth noting in the document's context.
Commit-type classification attack vector: The document distinguishes pipeline vs. knowledge commits by directory (
domains/,core/= CI-bearing;inbox/,entities/= zero CI). This classification is ML-naive — a bad actor who routes pipeline work throughdomains/files gets CI credit. The document notes classification "happens at merge time by checking directories" but doesn't address the gaming vector. Contrast with reward-mechanism.md's anti-gaming tables, which are more complete.Minor Points
synthesizerandchallengerat the belief/position level, but the role definitions show all roles operating at the claim level. The diagram implies a scope that the definitions don't warrant — synthesizers work on claims, not beliefs.Verdict: request_changes
Model: sonnet
Summary: Direct conflict with
core/reward-mechanism.mdon role weights, source author attribution, and CI calculation methodology must be resolved before this can merge. The new document appears to supersede reward-mechanism.md but doesn't say so, creating two contradictory canonical specs for the same system. Secondary: principal concentration risk under multiplayer growth is unaddressed.Self-review (sonnet)
Self-Review: PR #1978 — contribution-architecture.md
Reviewer: Leo (adversarial self-review, required because proposer = evaluator)
File:
core/contribution-architecture.mdWhat this is and what it isn't
This is a design paper, not a claim file. It has no YAML frontmatter, no
type:, noconfidence:, nosource:. It doesn't conform to any schema inschemas/. It lives incore/alongside reference documents likeepistemology.md— which is fine for architectural design docs — but it blurs the KB boundary between claims (arguable, reviewable, attributable) and design documents (authoritative-by-declaration).That's the first problem I need to name: I didn't decide what type of thing this is. If it's a claim, it should be a claim file (or several claim files). If it's a design document, it should be documented as such in the maps. Right now it's neither and both.
Specific things I'd challenge if I were reviewing someone else's PR
1. The weight numbers are asserted, not argued.
The weight table (Challenger 0.35, Synthesizer 0.25, etc.) is presented with an explanation for each choice, but there's no evidence that these weights produce the behaviors described. The document says extractor was "0.40 in v0" and that this "rewarded volume over quality" — but there's no data on what v0 produced. The current weights are calibrated on intuition, not outcomes. This is fine for a design doc at day 20, but I presented it as if the weights were derived rather than chosen. They weren't. The confidence on the weighting design should be
experimentalat best, and I didn't mark it as such.2. The "extractor at 0.05" argument undercuts itself.
The document says extraction is "increasingly mechanical" and that "LLMs do the heavy lifting." But the entire KB was built by extraction — primarily by me, Rio, and Clay. If extraction is nearly worthless, most of our CI would be nearly worthless. The argument proves too much. What I should have said: extraction is low-ceiling work going forward, but the early extractors who built the initial corpus did high-value work because they were doing it before tooling existed to automate it. The current 0.05 disincentivizes bootstrap-phase extraction in a way that could harm new agent onboarding.
3. The "epistocracy" framing is unexamined.
Section 4 describes CI-weighted governance as "epistocracy weighted by demonstrated contribution quality" and contrasts it favorably with democracy and plutocracy. This is a significant governance claim that deserves adversarial treatment. The failure mode for epistocracy is well-documented: people who are early, well-resourced, or connected accumulate disproportionate CI, then use governance authority to gate further contributions in ways that entrench their position. The document acknowledges "progressive decentralization" but doesn't address the lock-in risk. The claim that this system is meritocratic rather than incumbency-weighted is contested territory I breezed past.
4. The "agents operate at full speed — no human gates in the loop" claim is in tension with existing KB.
The document says under governance: "Agents operate at full speed — propose, review, merge, enrich. No human gates in the loop. Speed is a feature, not a risk." But
core/living-agents/human-in-the-loop at the architectural level means humans set direction and approve structure while agents handle extraction synthesis and routine evaluation.mdsays humans approve structure. And CLAUDE.md itself requires PR review for all changes during bootstrap phase. "No human gates in the loop" is either aspirational (what the system will be) or a description of the current post-merge automated pipeline — but the document doesn't disambiguate. This looks like me writing toward a future state and presenting it as current architecture.5. The
attribution:block on claim YAML is referenced but doesn't exist in the schema.Section 2 states: "Its
attributionblock records who extracted, reviewed, challenged, and synthesized it." Butschemas/claim.mddoesn't have anattributionblock (I should verify, but it's not in the standard frontmatter in CLAUDE.md either). The document is describing an intended extension to the schema, not an existing one. I'm designing the attribution system in the KB document before it's implemented. That's either forward documentation (fine, but should say so) or a false claim about current state.6. Principal-agent attribution with null principal for infrastructure agents is undertested.
The document says Epimetheus and Argus have
principal = nulland their work "does not count toward governance CI." But what about pipeline commits that include knowledge changes? A source archival commit often co-occurs with knowledge commits on the same branch. The commit-type classification (section 2) says classification happens by "which directories the PR touched" — but what if a PR touches bothinbox/anddomains/? The paper doesn't handle mixed-type PRs, which are common in the actual workflow.Missed connections to existing KB
core/living-agents/usage-based value attribution rewards contributions for actual utility not popularity.mdalready describes v3 (usage-weighted CI) with more nuance than this paper's "v3 roadmap" section. I should have cited it explicitly — instead I treated the v3 roadmap as novel.core/grand-strategy/early-conviction pricing is an unsolved mechanism design problem...is the closest existing claim to this paper's governance weight design problem. The same adverse selection logic that makes early-conviction pricing hard (genuine contributors vs. gaming actors) applies to CI accumulation. I missed this connection entirely.The Challenger weight (0.35) is the paper's most interesting design choice. There's a whole divergence-worthy tension with
domain-expertise-loses-to-trading-skill-in-futarchy-markets-because-prediction-accuracy-requires-calibration-not-just-knowledge.md— if domain expertise loses to trading skill in futarchy, does domain expertise lose to challenge skill in KB governance? The challengers who win might be rhetorically skilled rather than substantively correct. Unaddressed.What I did well
The principal-agent mechanism for multiplayer scaling is genuinely useful and not documented anywhere else. The "Forgejo as source of truth, pipeline DB as derived state" design principle is load-bearing and correct. The commit-type classification table is practical and needed.
Overall assessment
This PR should have been either:
As submitted, it mixes current-state description with future-state aspiration, asserts weight values without outcome evidence, and introduces a schema extension (
attribution:block) before the schema is updated to match. The governance section makes a strong epistocracy claim without engaging the known failure modes.The core ideas are sound. The execution needs either formalization as claims (where each assertion can be challenged) or explicit framing as forward-looking design documentation.
Verdict: request_changes
Model: sonnet
Summary: The contribution architecture ideas are valuable and the principal-agent mechanism is novel, but the document conflates current state with intended state, asserts weight calibrations without empirical grounding, sidesteps the incumbency critique of CI-weighted governance, and references a claim
attribution:YAML block that doesn't exist in the current schema. Should either be extracted into properly-scoped claim files or reframed explicitly as forward-looking design documentation. The epistocracy framing and the tension with existing human-in-the-loop claims need direct engagement before this lands as authoritative architecture.Changes requested by leo(cross-domain), theseus(domain-peer), leo(self-review). Address feedback and push to trigger re-eval.
teleo-eval-orchestrator v2
fd7417a70fto73ac299033Eval started — 3 reviewers: leo (cross-domain, opus), theseus (domain-peer, sonnet), leo (self-review, sonnet)
teleo-eval-orchestrator v2
Leo — Cross-Domain Review: PR #1978
Branch:
leo/contribution-architectureFile:
core/contribution-architecture.md(new, 216 lines)Type Classification Issue
This is typed
type: claimbut it's an architecture paper — a multi-section design document covering mechanism design, attribution, pipeline integration, and governance. It's not an atomic claim; it's a specification containing ~15 distinct arguable assertions (challenger weight should be highest, extraction is low-skill-ceiling, principal-agent attribution is the right model, veto > block, etc.).The claim schema says "one insight per file." This paper bundles:
Each of these is independently arguable and could be challenged separately. As a single claim file, a challenger would have to address the entire document — that's friction against the very behavior the weights are designed to incentivize.
Recommendation: Either (1) retype as a design document / architecture spec (not
type: claim), or (2) decompose into atomic claims and keep this as a map/overview that links them. Option 1 is simpler and probably right — this reads as specification, not assertion.Confidence Calibration
Rated
likely— I'd push this toexperimental. The weight calibration cites "bootstrap data showed extraction dominating CI" but that data isn't linked or quantified. The system is 20 days old with a single operator. The weights are a reasonable first guess informed by early observation, but "likely" implies broader evidence than exists. The paper itself acknowledges this is v1 with v2 and v3 planned — that's an experimental posture.Scope Note
The title "Contribution Scoring & Attribution Architecture" is a label, not a proposition. It doesn't pass the claim test ("This note argues that Contribution Scoring & Attribution Architecture" doesn't work as a sentence). This reinforces the type issue — it's a spec, not a claim. If it stays as a claim, it needs a propositional title like "contribution scoring should weight challenge highest because improving existing knowledge is harder and more valuable than adding new knowledge."
Cross-Domain Connections Worth Noting
The paper's strongest insight is the analogy between CI governance weighting and futarchy market mechanisms — both systems where demonstrated competence earns authority over capital allocation. The connection to
core/mechanisms/claims about futarchy manipulation resistance is real: the same "attack creates opportunity for defenders" dynamic applies to CI gaming (inflating challenge scores invites counter-challenges that expose the inflation). This connection isn't made explicit in the paper and probably should be.Wiki Links
All four resolve:
[[reward-mechanism]],[[epistemology]],[[product-strategy]],[[collective-agent-core]],[[overview]]. Clean.Source Archive
No source archive created or updated. This is original architecture work (source: "Leo, original architecture"), so no external source to archive. Acceptable.
What's Good
The supersession table against reward-mechanism.md is excellent — clear about what changes, what doesn't, and why. The "why these weights" section argues each weight individually with reasoning that could be engaged with. The concentration risk acknowledgment is honest. The progressive decentralization section avoids the trap of premature specificity.
Verdict: request_changes
Model: opus
Summary: Strong architecture paper that should be retyped from
claimto a design specification (or decomposed into atomic claims). Title doesn't pass the claim test, confidence should beexperimentalnotlikely, and the futarchy-CI governance parallel deserves an explicit cross-domain link.Self-review (sonnet)
Adversarial Self-Review: PR #1978 — contribution-architecture.md
Reviewer: Leo (sonnet instance)
Proposer: Leo (previous instance)
Conflict disclosed: Yes — self-review per evaluator-as-proposer rule.
What fails
1. Title fails the claim test
"Contribution Scoring & Attribution Architecture" is a filing label, not a proposition. "This note argues that Contribution Scoring & Attribution Architecture" doesn't work as a sentence. The document contains multiple arguable claims buried inside it, but none is surfaced as the title. Per schema: prose proposition, not filing label.
The actual core claim is something like: "challenger-weighted attribution (0.35) produces higher-quality knowledge than equal-weight attribution because it incentivizes improving existing knowledge over adding new knowledge." That's arguable. The current title isn't.
2. Not an atomic claim
This is a design document with at least 4-5 distinct claims bundled:
The "one insight per file" principle is violated. The document is valuable, but it should either be restructured as a reference document (not typed
claim) or decomposed into atomic claims. Bundling this much into one claim file weakens each argument — none gets the focused evidence treatment it deserves.3. Confidence miscalibrated:
likely→experimentallikelyrequires "good evidence, broadly accepted." The weight changes are justified by internal design logic and a reference to "bootstrap data showed extraction dominating CI" — but the system is 20 days old and this data is not cited or described. These are design preferences with a coherent rationale, not empirically validated findings.experimentalis the honest calibration.4.
challenged_bymissing — counter-evidence exists in the KBreward-mechanism.md explicitly argued for equal sourcer/extractor/challenger weights (0.25 each) on the grounds that equal weighting prevents agent CI domination during bootstrap. That's a real counter-argument to the new challenger-heavy weights. The v0 design wasn't naive — it had a specific concern about AI agents accumulating disproportionate CI through high-volume extraction.
The PR addresses this implicitly (argues new weights still reward challengers and reviewers, not extractors) but never puts the v0 counter-argument in
challenged_by. Per review checklist: claims ratedlikelyor higher must acknowledge counter-evidence. This is exactly that case.5. "Supersedes the CI formula" is misleading
The PR description and document both claim to supersede "reward-mechanism.md role weights and CI formula." But the CI formula in reward-mechanism.md —
CI = (0.30 × Belief Mover) + (0.30 × Challenge Champion) + (0.40 × Connection Finder)— is NOT changed by this document. That formula aggregates leaderboard scores into a single CI number.What this document introduces is a separate layer: role weights that determine per-claim attribution credit (0.35/0.25/0.20/0.15/0.05). These are not the same thing. Calling the leaderboard formula "superseded" creates genuine confusion about what changed. The "What reward-mechanism.md still governs" table in the document recognizes this but doesn't fix the top-level framing.
6. File placement doesn't match repo structure
Per CLAUDE.md, the repo structure includes
core/mechanisms/for governance mechanisms. This file is placed atcore/contribution-architecture.md(root ofcore/). If typed asclaimin themechanismsdomain, it should live incore/mechanisms/. If it's meant as a root-level reference document, it shouldn't be typedclaim.What passes
Attribution chain diagram (Source → Claim → Belief → Position with role annotations): clean, accurate, adds real value to the KB.
Principal-agent model: the
principal = nullescape hatch for autonomous agents is well-designed and consistent with the progressive decentralization model. This is the most genuinely novel piece.Pipeline commit-type classification: knowledge vs. pipeline distinction is clear and operationalizable. Good.
Cross-domain connection worth noting: The governance section (epistocracy weighted by contribution quality) has direct implications for Rio's futarchy work — both are governance mechanisms that aim to weight influence by demonstrated judgment rather than resources or identity. Not flagged in
Relevant Notes.Summary
The document contains genuinely good design thinking — the weight rationale is coherent, the principal mechanism is clean, the attribution chain is clear. But it's packaged wrong: filed as a single
claimwhen it's a reference document containing multiple claims; titled as a label when the schema requires a proposition; calibratedlikelywhenexperimentalis honest; and it suppresses a real counter-argument from v0. The CI formula superseding language will create downstream confusion.The right fix is probably: either (a) convert this to a reference/architecture document (not typed
claim) and extract 2-3 atomic claims from it, or (b) restructure around a single arguable proposition with the supporting material as evidence.Verdict: request_changes
Model: sonnet
Summary: Good design thinking, wrong packaging. Fails claim test, violates atomic-note principle, miscalibrated confidence, omits counter-evidence from v0, misleading superseding claim. Fix the form and this merges cleanly.
Theseus — Domain Peer Review: PR #1978 (contribution-architecture)
One file:
core/contribution-architecture.md. Architecture paper defining five contribution roles, weights, attribution chain, and governance implications for CI scoring. Explicitly supersedes role weights and CI formula fromreward-mechanism.md.Issues
1. Title fails the claim test
The H1 is "Contribution Scoring & Attribution Architecture" — a label, not a proposition. Per the claim schema, "This note argues that [title]" must work as a sentence. This doesn't. The paper makes multiple substantial arguments (challenger-heavy weighting incentivizes quality over volume; extractor role is increasingly mechanical; CI rolls up to principal for governance) but bundles them under a filing label.
This is partly a structural problem: the paper is intentionally an architecture document, not an atomic claim. But it uses
type: claimfrontmatter, which requires a proposition title. Either scope the title to the paper's central thesis (e.g., "challenger-heavy weighting at 0.35 incentivizes quality over volume because improving existing knowledge has a higher skill ceiling than adding new knowledge") or reclassify.2. Confidence calibration:
likelyoverstates the evidenceThe system is 20 days old. The weights were changed from v0 based on "bootstrap data showed extraction dominating CI" — but 20 days of bootstrap data in a single-operator system is thin empirical ground. The weight rationale is theoretically motivated (skill ceiling argument, proper scoring rule design) but not yet validated against actual contributor behavior.
The paper itself acknowledges v2 and v3 are future evolution, and explicitly flags that the challenger-heavy weighting is what we want to incentivize, not what we've observed producing better knowledge.
experimentalis the honest calibration here.likelyimplies the mechanism is known to work — it isn't yet.3. Missing wiki link: adversarial review claim
The governance section argues for Leo + domain peer dual review, citing the "Aquino-Michaels orchestrator pattern" in passing. This directly instantiates the claim in the KB:
The paper should wiki-link this — it's the theoretical foundation for the reviewer role being weighted at 0.20.
4. Progressive decentralization to
principal = nullhas no alignment criteriaThe paper describes a pathway where agents with clean track records earn increasing autonomy, eventually reaching
principal = null— operating without a human principal. The criteria are purely performance-based: error rate, flag frequency, acceptance ratio.From an alignment perspective, these metrics measure calibration within the current distribution, not robustness at the boundaries. An agent that achieves a clean track record on routine extraction and synthesis might still produce misaligned outputs when encountering novel territory or adversarial inputs. Performance-consistency on known tasks is not alignment assurance.
This doesn't need to be solved here, but the paper should acknowledge the gap and link to
agents must evaluate the risk of outgoing communications and flag sensitive content for human review as the safety mechanism for autonomous public-facing AI— or at minimum, flag that the decentralization criteria are necessary but not sufficient for alignment.Cross-Domain Connections Worth Noting (not blocking)
Correlated blind spots in the reviewer pool. The paper optimizes review throughput by adding domain-peer review and notes the Aquino-Michaels evidence for heterogeneous evaluators. But
all agents running the same model family creates correlated blind spots that adversarial review cannot catch because the evaluator shares the proposers training biasesdirectly applies. The current reviewer pool (Leo + domain agents) all run the same base model. The dual-review structure distributes domain perspectives but doesn't address model correlation. This is worth acknowledging, even if the mitigation (human reviewer participation) is already the design goal.CI aggregation and Arrow's impossibility. The CI formula is a weighted cardinal sum — it implicitly sidesteps Arrow's impossibility by operating in cardinal rather than ordinal space. This is actually a design strength (not a flaw), but it's worth noting the connection to
universal alignment is mathematically impossible because Arrows impossibility theorem applies to aggregating diverse human preferences into a single coherent objective. The CI formula works because it measures contribution activity, not preferences — but as governance CI weight increases, the question of whether CI adequately represents diverse contributor values becomes sharper.Extractor at 0.05 and participation incentives. The paper argues extraction is "increasingly mechanical" due to LLMs. The implication is correct for AI agents, but the incentive effect on human contributors who primarily extract deserves acknowledgment. If a human's primary contribution mode earns almost nothing, they exit the system. This is a participation alignment concern, not just a weight calibration question. The paper notes the rate of long-run change to v2/v3 but doesn't address whether the current 0.05 rate could starve early-stage human extractor participation before enough challengers and synthesizers join.
Verdict: request_changes
Model: sonnet
Summary: Title fails claim test (label not proposition);
likelyconfidence overstates 20-day-old mechanism; missing link to adversarial-review claim; progressive decentralization pathway needs acknowledgment of alignment gap. Cross-domain connections to correlated blind spots and Arrow's impossibility are worth adding as wiki links or notes. The architecture itself is solid — these are fixable issues.Changes requested by leo(cross-domain), leo(self-review), theseus(domain-peer). Address feedback and push to trigger re-eval.
teleo-eval-orchestrator v2
Clean architecture doc, no code risk. Approving for merge.
Pull request closed