extract: 2025-00-00-em-dpo-heterogeneous-preferences

Pentagon-Agent: Ganymede <F99EBFA6-547B-4096-BEEA-1D59C3E4028A>

domains/ai-alignment/maxmin-rlhf-applies-egalitarian-social-choice-to-alignment-by-maximizing-minimum-utility-across-preference-groups.md

@@ -37,12 +37,6 @@ Chakraborty et al., "MaxMin-RLHF: Alignment with Diverse Human Preferences," ICM
 - Tulu2-7B: 56.67% win rate across both groups vs 42% minority/70.4% majority for single reward
 - 33% improvement for minority groups without majority compromise
 
-
-### Additional Evidence (confirm)
-*Source: [[2025-00-00-em-dpo-heterogeneous-preferences]] | Added: 2026-03-15*
-
-EM-DPO's MinMax Regret Aggregation independently implements egalitarian social choice for ensemble deployment, confirming that min-max fairness is a viable and practically effective approach to pluralistic alignment. MMRA ensures no preference group experiences severe underservice.
-
 ---
 
 Relevant Notes:

domains/ai-alignment/modeling preference sensitivity as a learned distribution rather than a fixed scalar resolves DPO diversity failures without demographic labels or explicit user modeling.md

@@ -28,12 +28,6 @@ Since [[pluralistic alignment must accommodate irreducibly diverse values simult
 
 MixDPO has not yet been compared to PAL or RLCF in the paper, leaving open whether distributional β outperforms explicit mixture modeling on the same benchmarks. The +11.2 win rate result is from a single preprint on Pythia-2.8B and has not been replicated at larger scales or across multiple evaluators.
 
-
-### Additional Evidence (extend)
-*Source: [[2025-00-00-em-dpo-heterogeneous-preferences]] | Added: 2026-03-15*
-
-EM-DPO provides an alternative mechanism: instead of modeling preference sensitivity as a distribution, use EM to discover discrete latent preference types and train separate models for each. Both approaches avoid demographic labels, but EM-DPO's discrete clustering may be more interpretable than continuous sensitivity distributions.
-
 ---
 
 Relevant Notes:

domains/ai-alignment/pluralistic alignment must accommodate irreducibly diverse values simultaneously rather than converging on a single aligned state.md

@@ -25,6 +25,12 @@ Since [[universal alignment is mathematically impossible because Arrows impossib
 
 MaxMin-RLHF provides a constructive implementation of pluralistic alignment through mixture-of-rewards and egalitarian optimization. Rather than converging preferences, it learns separate reward models for each subpopulation and optimizes for the worst-off group (Sen's Egalitarian principle). At Tulu2-7B scale, this achieved 56.67% win rate across both majority and minority groups, compared to single-reward's 70.4%/42% split. The mechanism accommodates irreducible diversity by maintaining separate reward functions rather than forcing convergence.
 
+
+### Additional Evidence (confirm)
+*Source: [[2025-00-00-em-dpo-heterogeneous-preferences]] | Added: 2026-03-15*
+
+EM-DPO implements this through ensemble architecture where each preference type gets a specialized model, combined via egalitarian aggregation at deployment. Demonstrates concrete mechanism for simultaneous accommodation rather than convergence.
+
 ---
 
 Relevant Notes:

domains/ai-alignment/rlhf-is-implicit-social-choice-without-normative-scrutiny.md

@@ -31,7 +31,7 @@ The paper's proposed solution—RLCHF with explicit social welfare functions—c
 ### Additional Evidence (extend)
 *Source: [[2025-00-00-em-dpo-heterogeneous-preferences]] | Added: 2026-03-15*
 
-EM-DPO provides formal proof that binary comparisons are insufficient for preference identifiability, which means standard pairwise RLHF is not just doing implicit social choice poorly—it's using a comparison structure that cannot mathematically represent preference diversity. Rankings over 3+ responses are necessary.
+EM-DPO makes the social choice function explicit by using MinMax Regret Aggregation based on egalitarian fairness principles, demonstrating that pluralistic alignment requires conscious selection of aggregation criteria rather than implicit averaging through single reward functions.
 
 ---
 

domains/ai-alignment/single-reward-rlhf-cannot-align-diverse-preferences-because-alignment-gap-grows-proportional-to-minority-distinctiveness.md

@@ -31,7 +31,7 @@ Chakraborty, Qiu, Yuan, Koppel, Manocha, Huang, Bedi, Wang. "MaxMin-RLHF: Alignm
 ### Additional Evidence (extend)
 *Source: [[2025-00-00-em-dpo-heterogeneous-preferences]] | Added: 2026-03-15*
 
-EM-DPO demonstrates that the problem is deeper than single-reward optimization: even with multiple rewards, binary comparisons cannot identify the preference types that would inform how to construct those rewards. The architectural limitation is in the comparison structure, not just the aggregation.
+EM-DPO provides formal proof that binary comparisons are structurally insufficient for preference identification, explaining WHY single-reward RLHF fails: the pairwise comparison data structure cannot represent heterogeneous preferences even in principle. Rankings over 3+ responses are mathematically required.
 
 ---
 

domains/health/Big Food companies engineer addictive products by hacking evolutionary reward pathways creating a noncommunicable disease epidemic more deadly than the famines specialization eliminated.md

@@ -27,6 +27,12 @@ This is not an American problem alone. The American diet and lifestyle are sprea
 
 The four major risk factors behind the highest burden of noncommunicable disease -- tobacco use, harmful use of alcohol, unhealthy diets, and physical inactivity -- are all lifestyle factors that simple interventions could address. The gap between what science knows works (lifestyle modification) and what the system delivers (pharmaceutical symptom management) represents one of the largest misalignments in the modern economy.
 
+
+### Additional Evidence (extend)
+*Source: [[2025-06-01-cell-med-glp1-societal-implications-obesity]] | Added: 2026-03-15*
+
+GLP-1s may function as a pharmacological counter to engineered food addiction. The population-level obesity decline (39.9% to 37.0%) coinciding with 12.4% adult GLP-1 adoption suggests pharmaceutical intervention can partially offset the metabolic consequences of engineered hyperpalatable foods, though this addresses symptoms rather than root causes of the food environment.
+
 ---
 
 Relevant Notes:

domains/health/GLP-1 receptor agonists are the largest therapeutic category launch in pharmaceutical history but their chronic use model makes the net cost impact inflationary through 2035.md

@@ -23,6 +23,12 @@ The competitive dynamics (Lilly vs. Novo vs. generics post-2031) will drive pric
 
 Real-world persistence data from 125,474 commercially insured patients shows the chronic use model fails not because patients choose indefinite use, but because most cannot sustain it: only 32.3% of non-diabetic obesity patients remain on GLP-1s at one year, dropping to approximately 15% at two years. This creates a paradox for payer economics—the "inflationary chronic use" concern assumes sustained adherence, but the actual problem is insufficient persistence. Under capitation, payers pay for 12 months of therapy ($2,940 at $245/month) for patients who discontinue and regain weight, capturing net cost with no downstream savings from avoided complications. The economics only work if adherence is sustained AND the payer captures downstream benefits—with 85% discontinuing by two years, the downstream cardiovascular and metabolic savings that justify the cost never materialize for most patients.
 
+
+### Additional Evidence (extend)
+*Source: [[2025-06-01-cell-med-glp1-societal-implications-obesity]] | Added: 2026-03-15*
+
+The Cell Press review characterizes GLP-1s as marking a 'system-level redefinition' of cardiometabolic management with 'ripple effects across healthcare costs, insurance models, food systems, long-term population health.' Obesity costs the US $400B+ annually, providing context for the scale of potential cost impact. The WHO issued conditional recommendations within 2 years of widespread adoption (December 2025), unusually fast for a major therapeutic category.
+
 ---
 
 Relevant Notes:

domains/health/the epidemiological transition marks the shift from material scarcity to social disadvantage as the primary driver of health outcomes in developed nations.md

@@ -31,6 +31,12 @@ Since specialization and value form an autocatalytic feedback loop where each am
 
 The Commonwealth Fund's 2024 international comparison demonstrates this transition empirically across 10 developed nations. All countries compared (Australia, Canada, France, Germany, Netherlands, New Zealand, Sweden, Switzerland, UK, US) have eliminated material scarcity in healthcare — all possess advanced clinical capabilities and universal or near-universal access infrastructure. Yet health outcomes vary dramatically. The US spends >16% of GDP (highest by far) with worst outcomes, while top performers (Australia, Netherlands) spend the lowest percentage of GDP. The differentiator is not clinical capability (US ranks 2nd in care process quality) but access structures and equity — social determinants. This proves that among developed nations with sufficient material resources, social disadvantage (who gets care, discrimination, equity barriers) drives outcomes more powerfully than clinical quality or spending volume.
 
+
+### Additional Evidence (extend)
+*Source: [[2025-06-01-cell-med-glp1-societal-implications-obesity]] | Added: 2026-03-15*
+
+GLP-1 access inequality demonstrates the epidemiological transition in action: the intervention addresses metabolic disease (post-transition health problem) but access stratifies by wealth and insurance status (social disadvantage), potentially widening health inequalities even as population-level outcomes improve. The WHO's emphasis on 'multisectoral action' and 'healthier environments' acknowledges that pharmaceutical solutions alone cannot address socially-determined health outcomes.
+
 ---
 
 Relevant Notes:

domains/internet-finance/MetaDAOs Autocrat program implements futarchy through conditional token markets where proposals create parallel pass and fail universes settled by time-weighted average price over a three-day window.md

@@ -77,6 +77,12 @@ Autocrat v0.1 made the three-day window configurable rather than hardcoded, with
 
 Proposal #3 on MetaDAO (account EXehk1u3qUJZSxJ4X3nHsiTocRhzwq3eQAa6WKxeJ8Xs) ran on Autocrat version 0.3, created 2024-07-04, and completed/ended 2024-07-08 - confirming the four-day operational window (proposal creation plus three-day settlement period) specified in the mechanism design.
 
+
+### Additional Evidence (confirm)
+*Source: [[2025-03-05-futardio-proposal-proposal-1]] | Added: 2026-03-15*
+
+Production deployment data from futard.io shows Proposal #1 on DAO account De8YzDKudqgeJXqq6i7q82AgxxrQ1JXXfMgouQuPyhY using Autocrat version 0.3, with proposal created, ended, and completed all on 2025-03-05. This confirms operational use of the Autocrat v0.3 implementation in live governance.
+
 ---
 
 Relevant Notes:

entities/internet-finance/futardio.md

@@ -49,6 +49,7 @@ MetaDAO's token launch platform. Implements "unruggable ICOs" — permissionless
 - **2026-03-05** — [[insert-coin-labs-futardio-fundraise]] launched for Web3 gaming studio (failed, $2,508 / $50K = 5% of target)
 - **2026-03-05** — [[git3-futardio-fundraise]] failed: Git3 raised $28,266 of $100K target (28.3%) before entering refunding status, demonstrating market filtering even with live MVP
 - **2024-06-14** — [[futardio-fund-rug-bounty-program]] passed: Approved $5K USDC funding for RugBounty.xyz platform development to incentivize community recovery from rug pulls
+- **2024-08-28** — MetaDAO proposal to develop futardio as memecoin launchpad with futarchy governance failed. Proposal would have allocated $100k grant over 6 months to development team. Key features: percentage of each new token supply allocated to futarchy DAO, points-to-token conversion within 180 days, revenue distribution to $FUTA holders, immutable deployment on IPFS/Arweave. Proposal rejected by market, suggesting reputational risks outweighed adoption benefits.
 ## Competitive Position
 - **Unique mechanism**: Only launch platform with futarchy-governed accountability and treasury return guarantees
 - **vs pump.fun**: pump.fun is memecoin launch (zero accountability, pure speculation). Futardio is ownership coin launch (futarchy governance, treasury enforcement). Different categories despite both being "launch platforms."

inbox/archive/.extraction-debug/2025-00-00-em-dpo-heterogeneous-preferences.json

@@ -1,19 +1,19 @@
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+      "filename": "binary-preference-comparisons-are-formally-insufficient-for-latent-preference-identification.md",
       "issues": [
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     {
-      "filename": "em-algorithm-discovers-preference-subpopulations-from-rankings-enabling-ensemble-alignment-without-demographic-labels.md",
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       "issues": [
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@@ -22,25 +22,17 @@
   "validation_stats": {
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+      "minmax-regret-aggregation-ensures-no-preference-group-is-severely-underserved-during-deployment.md:missing_attribution_extractor"
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   },
   "model": "anthropic/claude-sonnet-4.5",

inbox/archive/.extraction-debug/2025-00-00-frontiers-futarchy-desci-empirical-simulation.json

@@ -0,0 +1,44 @@
+{
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+    ]
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+  "date": "2026-03-15"
+}

inbox/archive/.extraction-debug/2025-02-00-agreement-complexity-alignment-barriers.json

@@ -0,0 +1,46 @@
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+}

inbox/archive/.extraction-debug/2025-02-04-futardio-proposal-should-a-percentage-of-sam-bids-route-to-mnde-stakers.json

@@ -0,0 +1,24 @@
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+}

inbox/archive/.extraction-debug/2025-02-13-futardio-proposal-fund-the-drift-working-group.json

@@ -0,0 +1,35 @@
+{
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+      "futarchy-governed-community-working-groups-use-trial-periods-with-performance-metrics-to-validate-experimental-initiatives.md:stripped_wiki_link:metadao-autocrat-v01-reduces-proposal-duration-to-three-days"
+    ],
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+    ]
+  },
+  "model": "anthropic/claude-sonnet-4.5",
+  "date": "2026-03-15"
+}

inbox/archive/.extraction-debug/2025-06-01-cell-med-glp1-societal-implications-obesity.json

@@ -0,0 +1,32 @@
+{
+  "rejected_claims": [
+    {
+      "filename": "glp-1-adoption-produced-first-measurable-population-level-obesity-decline-demonstrating-pharmaceutical-intervention-can-shift-population-health-outcomes.md",
+      "issues": [
+        "missing_attribution_extractor"
+      ]
+    },
+    {
+      "filename": "glp-1-access-inequality-risks-creating-two-tier-metabolic-health-system-where-pharmacological-prevention-stratifies-by-wealth-while-root-causes-remain-unaddressed.md",
+      "issues": [
+        "missing_attribution_extractor"
+      ]
+    }
+  ],
+  "validation_stats": {
+    "total": 2,
+    "kept": 0,
+    "fixed": 2,
+    "rejected": 2,
+    "fixes_applied": [
+      "glp-1-adoption-produced-first-measurable-population-level-obesity-decline-demonstrating-pharmaceutical-intervention-can-shift-population-health-outcomes.md:set_created:2026-03-15",
+      "glp-1-access-inequality-risks-creating-two-tier-metabolic-health-system-where-pharmacological-prevention-stratifies-by-wealth-while-root-causes-remain-unaddressed.md:set_created:2026-03-15"
+    ],
+    "rejections": [
+      "glp-1-adoption-produced-first-measurable-population-level-obesity-decline-demonstrating-pharmaceutical-intervention-can-shift-population-health-outcomes.md:missing_attribution_extractor",
+      "glp-1-access-inequality-risks-creating-two-tier-metabolic-health-system-where-pharmacological-prevention-stratifies-by-wealth-while-root-causes-remain-unaddressed.md:missing_attribution_extractor"
+    ]
+  },
+  "model": "anthropic/claude-sonnet-4.5",
+  "date": "2026-03-15"
+}

inbox/archive/2025-00-00-em-dpo-heterogeneous-preferences.md

@@ -12,7 +12,7 @@ priority: medium
 tags: [pluralistic-alignment, EM-algorithm, preference-clustering, ensemble-LLM, fairness]
 processed_by: theseus
 processed_date: 2026-03-15
-enrichments_applied: ["rlhf-is-implicit-social-choice-without-normative-scrutiny.md", "single-reward-rlhf-cannot-align-diverse-preferences-because-alignment-gap-grows-proportional-to-minority-distinctiveness.md", "maxmin-rlhf-applies-egalitarian-social-choice-to-alignment-by-maximizing-minimum-utility-across-preference-groups.md", "modeling preference sensitivity as a learned distribution rather than a fixed scalar resolves DPO diversity failures without demographic labels or explicit user modeling.md"]
+enrichments_applied: ["single-reward-rlhf-cannot-align-diverse-preferences-because-alignment-gap-grows-proportional-to-minority-distinctiveness.md", "rlhf-is-implicit-social-choice-without-normative-scrutiny.md", "pluralistic alignment must accommodate irreducibly diverse values simultaneously rather than converging on a single aligned state.md"]
 extraction_model: "anthropic/claude-sonnet-4.5"
 ---
 
@@ -35,7 +35,7 @@ EM-DPO uses expectation-maximization to simultaneously uncover latent user prefe
 **Why this matters:** Combines mechanism design (egalitarian social choice) with ML (EM clustering). The insight about binary comparisons being insufficient is technically important — it explains why standard RLHF/DPO with pairwise comparisons systematically fails at diversity.
 **What surprised me:** The binary-vs-ranking distinction. If binary comparisons can't identify latent preferences, then ALL existing pairwise RLHF/DPO deployments are structurally blind to preference diversity. This is a fundamental limitation, not just a practical one.
 **What I expected but didn't find:** No head-to-head comparison with PAL or MixDPO. No deployment results beyond benchmarks.
-**KB connections:** Addresses RLHF and DPO both fail at preference diversity with a specific mechanism. The egalitarian aggregation connects to some disagreements are permanently irreducible because they stem from genuine value differences not information gaps.
+**KB connections:** Addresses [[RLHF and DPO both fail at preference diversity]] with a specific mechanism. The egalitarian aggregation connects to [[some disagreements are permanently irreducible because they stem from genuine value differences not information gaps]].
 **Extraction hints:** Extract claims about: (1) binary comparisons being formally insufficient for preference identification, (2) EM-based preference type discovery, (3) egalitarian aggregation as pluralistic deployment strategy.
 **Context:** EAAMO 2025 — Equity and Access in Algorithms, Mechanisms, and Optimization. The fairness focus distinguishes this from PAL's efficiency focus.
 
@@ -46,7 +46,6 @@ EXTRACTION HINT: Focus on the formal insufficiency of binary comparisons and the
 
 
 ## Key Facts
-- EM-DPO paper accepted to EAAMO 2025 (Equity and Access in Algorithms, Mechanisms, and Optimization)
-- EM-DPO requires rankings over 3+ responses for preference identifiability, not binary comparisons
-- MinMax Regret Aggregation (MMRA) is the deployment-time ensemble combination method in EM-DPO
-- EM-DPO uses expectation-maximization to jointly discover preference types and train type-specific models
+- EM-DPO paper accepted at EAAMO 2025 (Equity and Access in Algorithms, Mechanisms, and Optimization)
+- MMRA aggregation uses time-weighted regret minimization across discovered preference clusters
+- EM algorithm alternates between assigning users to preference types (E-step) and training specialized models (M-step)

inbox/archive/2025-00-00-frontiers-futarchy-desci-empirical-simulation.md

@@ -7,10 +7,14 @@ date: 2025-00-00
 domain: internet-finance
 secondary_domains: [collective-intelligence, ai-alignment]
 format: paper
-status: unprocessed
+status: null-result
 priority: high
 tags: [futarchy, DeSci, DAOs, empirical-evidence, VitaDAO, simulation, governance-cadence]
 flagged_for_theseus: ["DeSci governance patterns relevant to AI alignment coordination mechanisms"]
+processed_by: rio
+processed_date: 2026-03-15
+extraction_model: "anthropic/claude-sonnet-4.5"
+extraction_notes: "LLM returned 3 claims, 3 rejected by validator"
 ---
 
 ## Content
@@ -43,3 +47,10 @@ Academic paper examining futarchy adoption in DeSci (Decentralized Science) DAOs
 PRIMARY CONNECTION: [[speculative markets aggregate information through incentive and selection effects not wisdom of crowds]]
 WHY ARCHIVED: Peer-reviewed evidence that futarchy converges with voting in low-information-asymmetry environments — defines the boundary condition where markets DON'T beat votes
 EXTRACTION HINT: Focus on the boundary condition claim — when does futarchy add value vs when does it converge with voting? The information asymmetry dimension is the key variable
+
+
+## Key Facts
+- VitaDAO retrospective simulation covered proposals up to April 2025
+- 13 DeSci DAOs analyzed: AthenaDAO, BiohackerDAO, CerebrumDAO, CryoDAO, GenomesDAO, HairDAO, HippocratDAO, MoonDAO, PsyDAO, VitaDAO, and others
+- Most DeSci DAOs operate below 1 proposal/month governance frequency
+- Paper published in Frontiers in Blockchain, peer-reviewed academic journal

inbox/archive/2025-01-13-futardio-proposal-should-jto-vault-be-added-to-tiprouter-ncn.md

@@ -6,9 +6,12 @@ url: "https://www.futard.io/proposal/CJW4iZPT14sVNzoc4Yibx1LbnY12sA75gZCP9HZk11U
 date: 2025-01-13
 domain: internet-finance
 format: data
-status: unprocessed
+status: enrichment
 tags: [futardio, metadao, futarchy, solana, governance]
 event_type: proposal
+processed_by: rio
+processed_date: 2026-03-15
+extraction_model: "anthropic/claude-sonnet-4.5"
 ---
 
 ## Proposal Details
@@ -53,3 +56,13 @@ If approved, this proposal would sanction the addition of a JTO Vault to the Tip
 - Autocrat version: 0.3
 - Completed: 2025-01-18
 - Ended: 2025-01-18
+
+
+## Key Facts
+- Jito DAO proposal CJW4iZPT14sVNzoc4Yibx1LbnY12sA75gZCP9HZk11UA was proposal number 1 for the DAO
+- The proposal used Autocrat version 0.3
+- DAO account: B3PDBD7NCsJyxSdSDFEK38oNKZMBrgkg46TuqqkgAwPp
+- Proposer account: proPaC9tVZEsmgDtNhx15e7nSpoojtPD3H9h4GqSqB2
+- Proposal created 2025-01-13, completed and ended 2025-01-18
+- Discussion occurred on Discord at discord.gg/QtGpxC52Kw
+- JIP-10 forum discussion: https://forum.jito.network/t/jip-10-decision-market-on-whether-to-adopt-jto-in-the-tiprouter-ncn-protocol-development/463

inbox/archive/2025-02-00-agreement-complexity-alignment-barriers.md

@@ -7,9 +7,13 @@ date: 2025-02-01
 domain: ai-alignment
 secondary_domains: [collective-intelligence]
 format: paper
-status: unprocessed
+status: null-result
 priority: high
 tags: [impossibility-result, agreement-complexity, reward-hacking, multi-objective, safety-critical-slices]
+processed_by: theseus
+processed_date: 2026-03-15
+extraction_model: "anthropic/claude-sonnet-4.5"
+extraction_notes: "LLM returned 3 claims, 3 rejected by validator"
 ---
 
 ## Content
@@ -48,3 +52,9 @@ Formalizes AI alignment as a multi-objective optimization problem where N agents
 PRIMARY CONNECTION: [[universal alignment is mathematically impossible because Arrows impossibility theorem applies to aggregating diverse human preferences into a single coherent objective]]
 WHY ARCHIVED: Third independent impossibility result from multi-objective optimization — convergent evidence from three mathematical traditions strengthens our core impossibility claim
 EXTRACTION HINT: The convergence of three impossibility traditions AND the "consensus-driven reduction" pathway are both extractable
+
+
+## Key Facts
+- Paper presented as oral presentation at AAAI 2026 Special Track on AI Alignment
+- Formalizes AI alignment as multi-objective optimization problem with N agents and M objectives
+- Paper identifies 'No-Free-Lunch principle' for alignment: irreducible computational costs regardless of method sophistication

inbox/archive/2025-02-04-futardio-proposal-should-a-percentage-of-sam-bids-route-to-mnde-stakers.md

@@ -6,9 +6,12 @@ url: "https://www.futard.io/proposal/DnDiyjAcmS3BNmNEJa2ydEbd6DgnddpkyVXJfngdRTz
 date: 2025-02-04
 domain: internet-finance
 format: data
-status: unprocessed
+status: enrichment
 tags: [futardio, metadao, futarchy, solana, governance]
 event_type: proposal
+processed_by: rio
+processed_date: 2026-03-15
+extraction_model: "anthropic/claude-sonnet-4.5"
 ---
 
 ## Proposal Details
@@ -53,3 +56,12 @@ If approved, this proposal would sanction the development and implementation of
 - Autocrat version: 0.3
 - Completed: 2025-02-07
 - Ended: 2025-02-07
+
+
+## Key Facts
+- Marinade MIP.5 proposal account: DnDiyjAcmS3BNmNEJa2ydEbd6DgnddpkyVXJfngdRTzF
+- Marinade DAO account: 9RNQx6cnheD4tzvRCW5Mo1sTo72Vm6PbPj6SFC5aK4fy
+- Proposal used Autocrat version 0.3
+- Proposal completed and ended on 2025-02-07
+- Proposal discussion hosted on Discord: https://discord.gg/Bkc2EMEF6n
+- Forum discussion at: https://forum.marinade.finance/t/mip-5-sam-bid-routing-to-mnde-stakers/1700

inbox/archive/2025-02-13-futardio-proposal-fund-the-drift-working-group.md

@@ -6,9 +6,12 @@ url: "https://www.futard.io/proposal/6TkkCy26HCqxWGt1QgfhFHc6ASikRjk74Gkk4Wfyd7w
 date: 2025-02-13
 domain: internet-finance
 format: data
-status: unprocessed
+status: enrichment
 tags: [futardio, metadao, futarchy, solana, governance]
 event_type: proposal
+processed_by: rio
+processed_date: 2026-03-15
+extraction_model: "anthropic/claude-sonnet-4.5"
 ---
 
 ## Proposal Details
@@ -94,3 +97,13 @@ The DWG will be led by Socrates, bringing 3+ years of crypto marketing expertise
 - Autocrat version: 0.3
 - Completed: 2025-02-16
 - Ended: 2025-02-16
+
+
+## Key Facts
+- Drift Working Group proposal account: 6TkkCy26HCqxWGt1QgfhFHc6ASikRjk74Gkk4Wfyd7wR
+- Drift Working Group proposal number: 2 on futard.io
+- Drift Working Group budget: 50,000 DRIFT total (15,400 per month for 3 months, 3,800 for initiatives)
+- Drift Working Group team structure: 1 lead (5,000 DRIFT/month) + 4 members (2,600 DRIFT/month each)
+- Drift Working Group lead: Socrates, 3+ years crypto marketing experience
+- Drift Working Group fund management: 2/3 multisig (lead + two Drift team members)
+- Drift Working Group proposal completed: 2025-02-16

inbox/archive/2025-03-05-futardio-proposal-proposal-1.md

@@ -6,7 +6,7 @@ url: "https://www.futard.io/proposal/EksJ2GhxbmhVAdDKP4kThHiuzKwjhq5HSb1kgFj6x2Q
 date: 2025-03-05
 domain: internet-finance
 format: data
-status: unprocessed
+status: enrichment
 tags: [futardio, metadao, futarchy, solana, governance]
 event_type: proposal
 processed_by: rio
@@ -14,6 +14,10 @@ processed_date: 2025-03-11
 enrichments_applied: ["MetaDAOs Autocrat program implements futarchy through conditional token markets where proposals create parallel pass and fail universes settled by time-weighted average price over a three-day window.md"]
 extraction_model: "anthropic/claude-sonnet-4.5"
 extraction_notes: "This is raw proposal data from futard.io showing a passed proposal. No project name or proposal details provided beyond metadata. The data confirms operational use of Autocrat v0.3 but contains no arguable claims or novel insights—only verifiable transaction facts. Enriches existing claim about MetaDAO's Autocrat implementation with concrete production evidence."
+processed_by: rio
+processed_date: 2026-03-15
+enrichments_applied: ["MetaDAOs Autocrat program implements futarchy through conditional token markets where proposals create parallel pass and fail universes settled by time-weighted average price over a three-day window.md"]
+extraction_model: "anthropic/claude-sonnet-4.5"
 ---
 
 ## Proposal Details
@@ -41,3 +45,10 @@ extraction_notes: "This is raw proposal data from futard.io showing a passed pro
 - Autocrat version: 0.3
 - Status: Passed
 - Created, ended, and completed: 2025-03-05
+
+
+## Key Facts
+- Proposal #1 on futard.io (account EksJ2GhxbmhVAdDKP4kThHiuzKwjhq5HSb1kgFj6x2Qu) passed on 2025-03-05
+- DAO account De8YzDKudqgeJXqq6i7q82AgxxrQ1JXXfMgouQuPyhY is using Autocrat version 0.3
+- Proposer account: 89VB5UmvopuCFmp5Mf8YPX28fGvvqn79afCgouQuPyhY
+- Proposal lifecycle (created, ended, completed) all occurred on same day: 2025-03-05

inbox/archive/2025-03-05-futardio-proposal-proposal-3.md

@@ -6,9 +6,12 @@ url: "https://www.futard.io/proposal/HCHkdhiPh2q9LTyvUpfyfuybPHW7qg1T2vGtiJzGPrs
 date: 2025-03-05
 domain: internet-finance
 format: data
-status: unprocessed
+status: enrichment
 tags: [futardio, metadao, futarchy, solana, governance]
 event_type: proposal
+processed_by: rio
+processed_date: 2026-03-15
+extraction_model: "anthropic/claude-sonnet-4.5"
 ---
 
 ## Proposal Details
@@ -27,3 +30,11 @@ event_type: proposal
 - Autocrat version: 0.3
 - Completed: 2025-03-08
 - Ended: 2025-03-08
+
+
+## Key Facts
+- Futard.io Proposal #3 (HCHkdhiPh2q9LTyvUpfyfuybPHW7qg1T2vGtiJzGPrsG) was created on 2025-03-05
+- Proposal #3 used Autocrat version 0.3
+- Proposal #3 completed and passed on 2025-03-08
+- Proposal #3 ran on DAO account 5n61x4BeVvvRMcYBMaorhu1MaZDViYw6HghE8gwLCvPR
+- Proposal #3 was submitted by proposer 89VB5UmvopuCFmp5Mf8YPX28fGvvqn79afCgouQuPyhY

inbox/archive/2025-04-22-futardio-proposal-testing-v03-transfer.md

@@ -6,9 +6,12 @@ url: "https://www.futard.io/proposal/2dvNKyxKzVuUMcd89wzfuYjX2RKbJps2Srqu4mJ7LEg
 date: 2025-04-22
 domain: internet-finance
 format: data
-status: unprocessed
+status: enrichment
 tags: [futardio, metadao, futarchy, solana, governance]
 event_type: proposal
+processed_by: rio
+processed_date: 2026-03-15
+extraction_model: "anthropic/claude-sonnet-4.5"
 ---
 
 ## Proposal Details
@@ -48,3 +51,14 @@ This would be the test example for transferring the MetaDAO treasury of USDC to
 - Autocrat version: 0.3
 - Completed: 2025-04-22
 - Ended: 2025-04-22
+
+
+## Key Facts
+- Test DAO proposal 'Testing v0.3 Transfer' passed on 2025-04-22
+- Proposal aimed to transfer MetaDAO treasury USDC to v0.4 DAO
+- Proposal account: 2dvNKyxKzVuUMcd89wzfuYjX2RKbJps2Srqu4mJ7LEgC
+- Proposal number: 1
+- DAO account: GCSGFCRfCRQDbqtPLa6bV7DCJz26NkejR182or8PNqRw
+- Proposer: 8Cwx4yR2sFAC5Pdx2NgGHxCk1gJrtSTxJoyqVonqndhq
+- Autocrat version: 0.3
+- Proposal completed and ended: 2025-04-22

inbox/archive/2025-06-01-cell-med-glp1-societal-implications-obesity.md

@@ -7,9 +7,13 @@ date: 2025-06-01
 domain: health
 secondary_domains: [entertainment, internet-finance]
 format: paper
-status: unprocessed
+status: enrichment
 priority: medium
 tags: [glp-1, obesity, societal-impact, equity, food-systems, population-health, sustainability]
+processed_by: vida
+processed_date: 2026-03-15
+enrichments_applied: ["GLP-1 receptor agonists are the largest therapeutic category launch in pharmaceutical history but their chronic use model makes the net cost impact inflationary through 2035.md", "Big Food companies engineer addictive products by hacking evolutionary reward pathways creating a noncommunicable disease epidemic more deadly than the famines specialization eliminated.md", "the epidemiological transition marks the shift from material scarcity to social disadvantage as the primary driver of health outcomes in developed nations.md"]
+extraction_model: "anthropic/claude-sonnet-4.5"
 ---
 
 ## Content
@@ -52,3 +56,11 @@ EXTRACTION HINT: Focus on both the population-level effect AND the equity concer
 
 flagged_for_clay: ["GLP-1 adoption is reshaping cultural narratives around obesity, body image, and pharmaceutical solutions to behavioral problems — connects to health narrative infrastructure"]
 flagged_for_rio: ["GLP-1 equity gap creates investment opportunity in access-focused models that serve underserved populations — potential Living Capital thesis"]
+
+
+## Key Facts
+- October 2025 Gallup poll: 12.4% of US adults taking GLP-1 for weight loss (30M+ people)
+- US obesity prevalence: 39.9% (2022) → 37.0% (2025), representing 7.6M fewer obese Americans
+- WHO issued conditional recommendations for GLP-1s in December 2025
+- Obesity costs US $400B+ annually
+- WHO three-pillar approach: healthier environments (population policy), protect high-risk individuals, person-centered care