diff --git a/domains/health/ai-cognitive-worker-displacement-creates-second-wave-deaths-of-despair.md b/domains/health/ai-cognitive-worker-displacement-creates-second-wave-deaths-of-despair.md
index 3fad4cac1..9bf61346a 100644
--- a/domains/health/ai-cognitive-worker-displacement-creates-second-wave-deaths-of-despair.md
+++ b/domains/health/ai-cognitive-worker-displacement-creates-second-wave-deaths-of-despair.md
@@ -39,3 +39,10 @@ The Fed data reveals that AI adoption follows an education and skill gradient: h
 **Source:** Anthropic Research 2026, Brynjolfsson et al. 2025
 
 Anthropic's real-world Claude usage data provides empirical confirmation that cognitive worker displacement is already occurring at measurable scale: 6-16% employment decline among workers aged 22-25 in exposed occupations since late 2022, with highest exposure in computer/math (35.8%), office/admin (34.3%), and business/finance (28.4%). The displacement pattern affects labor force entry rather than exit, creating early-career income and purpose loss that could generate deaths of despair in younger cohorts.
+
+
+## Extending Evidence
+
+**Source:** LPL Financial Research / KC Fed (2026)
+
+The 2.7% aggregate US productivity growth in 2025 (nearly double the decade average) demonstrates that cognitive worker displacement can co-exist with strong GDP growth through sector concentration. The KC Fed finding that gains are 'MORE CONCENTRATED than the pre-pandemic era' suggests the displacement/growth paradox is intensifying rather than resolving.
diff --git a/domains/health/ai-labor-displacement-accelerates-entry-level-job-loss-without-reaching-physically-demanding-sectors.md b/domains/health/ai-labor-displacement-accelerates-entry-level-job-loss-without-reaching-physically-demanding-sectors.md
index 86d433274..199ae9697 100644
--- a/domains/health/ai-labor-displacement-accelerates-entry-level-job-loss-without-reaching-physically-demanding-sectors.md
+++ b/domains/health/ai-labor-displacement-accelerates-entry-level-job-loss-without-reaching-physically-demanding-sectors.md
@@ -17,3 +17,10 @@ related: ["americas-declining-life-expectancy-is-driven-by-deaths-of-despair-con
 # AI labor market displacement is accelerating entry-level job loss in exposed occupations without reaching the physically-demanding sectors where chronic disease burden is most concentrated
 
 Anthropic's 'observed exposure' methodology using real-world Claude usage data reveals that AI displacement follows a distinct pattern: it affects entry into the labor force rather than exit of existing workers. Brynjolfsson et al. 2025 found 6-16% employment decline among workers aged 22-25 in exposed occupations since late 2022, while no systematic unemployment increase appeared for experienced workers. The highest observed exposure occupations are computer/math (35.8%), office/admin (34.3%), and business/finance (28.4%) — all knowledge and clerical work. Critically, the physically-demanding sectors where Session 32 identified chronic disease concentration (manufacturing, construction, lower-skill physical services) show minimal observed exposure. This creates a dual health risk: (1) the original healthspan binding constraint remains intact because AI hasn't reached the physical labor sectors where chronic disease is most prevalent, and (2) AI displacement of entry-level workers creates a new pathway for health deterioration through worsened social determinants of health (reduced early-career income, job insecurity, loss of purpose). The gap between theoretical exposure (90%+ for office/admin) and observed exposure (34.3%) suggests a long diffusion timeline before AI reaches physically-demanding work, meaning the chronic disease burden in those sectors will persist while a new cohort experiences social determinant degradation from early-career displacement.
+
+
+## Supporting Evidence
+
+**Source:** KC Fed Economic Bulletin (2026)
+
+Kansas City Fed (2026) confirms AI productivity gains are 'driven by specific slices of information services and business-facing professional activities' with manufacturing showing an 'AI J-curve' where early adoption slows productivity before delivering gains. Low-skill services, manufacturing, and construction saw only 0.4% productivity gains in 2025 versus 0.8% for high-skill services, with the gap expected to widen to 0.8% versus 2%+ in 2026.
diff --git a/domains/health/ai-productivity-gains-enable-gdp-healthspan-decoupling-through-sector-concentration.md b/domains/health/ai-productivity-gains-enable-gdp-healthspan-decoupling-through-sector-concentration.md
new file mode 100644
index 000000000..cec2ad02b
--- /dev/null
+++ b/domains/health/ai-productivity-gains-enable-gdp-healthspan-decoupling-through-sector-concentration.md
@@ -0,0 +1,19 @@
+---
+type: claim
+domain: health
+description: The right-tail distribution of AI productivity allows aggregate economic growth to mask population health decline for potentially a decade
+confidence: experimental
+source: Federal Reserve Bank of Kansas City (2026), LPL Financial Research (2026)
+created: 2026-05-01
+title: AI productivity gains enable GDP-healthspan decoupling because gains are concentrated in information services and professional activities while chronic disease burden concentrates in manufacturing construction and lower-skill services
+agent: vida
+sourced_from: health/2026-05-01-lpl-ai-productivity-us-growth-2026-sector-concentration.md
+scope: structural
+sourcer: Federal Reserve Bank of Kansas City / LPL Financial Research
+supports: ["ai-labor-displacement-accelerates-entry-level-job-loss-without-reaching-physically-demanding-sectors"]
+related: ["americas-declining-life-expectancy-is-driven-by-deaths-of-despair-concentrated-in-populations-and-regions-most-damaged-by-economic-restructuring-since-the-1980s", "ai-labor-displacement-accelerates-entry-level-job-loss-without-reaching-physically-demanding-sectors", "ai-cognitive-worker-displacement-creates-second-wave-deaths-of-despair"]
+---
+
+# AI productivity gains enable GDP-healthspan decoupling because gains are concentrated in information services and professional activities while chronic disease burden concentrates in manufacturing construction and lower-skill services
+
+The Kansas City Fed found that productivity gains in the gen-AI era are 'MORE CONCENTRATED than the pre-pandemic era' with a distribution curve that 'stays below zero for much of the distribution and then climbs sharply near the right tail.' Gains 'appear driven by specific slices of information services and business-facing professional activities, rather than being evenly spread.' This concentration pattern allows the US to post 2.7% aggregate productivity growth in 2025 (nearly double the 1.4% decade average) while the chronic disease burden remains concentrated in sectors seeing minimal AI benefit. High-skill services and finance achieved ~0.8% gains in 2025 with 2%+ expected in 2026, while low-skill services, manufacturing, and construction saw only ~0.4% gains in 2025 with ~0.8% expected in 2026. The doubling for lower-skill sectors is real but from a much lower base. This creates a GDP/healthspan decoupling mechanism: the 2.7% productivity growth co-exists with declining population health metrics because the $575B/year chronic disease productivity burden (Session 32) concentrates in the non-AI-exposed sectors. The right-tail distribution means aggregate statistics look healthy while the median worker in chronic-disease-concentrated sectors sees minimal AI benefit. The KC Fed notes an 'AI J-curve' in manufacturing where early adoption slows productivity before delivering gains, suggesting manufacturing AI adoption is real but not yet showing productivity benefits. This decoupling can persist until the chronic disease burden becomes a binding constraint even on AI-exposed sectors.
diff --git a/domains/health/us-healthcare-spending-outcome-paradox-confirms-non-clinical-factors-dominate-population-health.md b/domains/health/us-healthcare-spending-outcome-paradox-confirms-non-clinical-factors-dominate-population-health.md
index 5f511be72..7bf4669ba 100644
--- a/domains/health/us-healthcare-spending-outcome-paradox-confirms-non-clinical-factors-dominate-population-health.md
+++ b/domains/health/us-healthcare-spending-outcome-paradox-confirms-non-clinical-factors-dominate-population-health.md
@@ -49,3 +49,10 @@ The US spends $14,885 per capita on healthcare (2.5x the OECD average of $5,967)
 **Source:** OECD Health at a Glance 2025
 
 OECD 2025 data quantifies the spending-outcome paradox with precision: US spends $14,885 per capita (2.5x OECD average $5,967) and 17.2% of GDP (vs 9.3% OECD average), yet life expectancy is 2.7 years below OECD average (78.4 vs ~81.1 years). The preventable mortality gap (50% worse than OECD) is more than double the treatable mortality gap (23% worse), confirming that the primary failure is non-clinical. US acute care performance (AMI, stroke) matches or exceeds OECD peers, proving clinical capability is not the binding constraint.
+
+
+## Extending Evidence
+
+**Source:** KC Fed / LPL Research (2026)
+
+The GDP/healthspan decoupling mechanism provides a specific pathway for how economic indicators can diverge from health outcomes: AI productivity gains concentrate in information services and professional activities (right-tail distribution per KC Fed) while chronic disease burden concentrates in manufacturing, construction, and lower-skill services. This allows 2.7% productivity growth to co-exist with declining population health metrics.
diff --git a/inbox/queue/2026-05-01-lpl-ai-productivity-us-growth-2026-sector-concentration.md b/inbox/archive/health/2026-05-01-lpl-ai-productivity-us-growth-2026-sector-concentration.md
similarity index 98%
rename from inbox/queue/2026-05-01-lpl-ai-productivity-us-growth-2026-sector-concentration.md
rename to inbox/archive/health/2026-05-01-lpl-ai-productivity-us-growth-2026-sector-concentration.md
index 3e5e89b24..60cc0b766 100644
--- a/inbox/queue/2026-05-01-lpl-ai-productivity-us-growth-2026-sector-concentration.md
+++ b/inbox/archive/health/2026-05-01-lpl-ai-productivity-us-growth-2026-sector-concentration.md
@@ -7,10 +7,13 @@ date: 2026-05-01
 domain: health
 secondary_domains: []
 format: report
-status: unprocessed
+status: processed
+processed_by: vida
+processed_date: 2026-05-01
 priority: medium
 tags: [AI-productivity, GDP, sector-concentration, high-skill, low-skill, healthspan-belief, GDP-decoupling]
 intake_tier: research-task
+extraction_model: "anthropic/claude-sonnet-4.5"
 ---
 
 ## Content