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AI_021predictionLabor/JobsGreat-Disemboweling

The 2026-2027 window is the 'Great Disemboweling' of white-collar employment — millions of mid-career professionals (junior software developers, legal analysts, corporate marketers) lose jobs within a 12-18 month timeframe; resulting unemployment casca...

Predictor: Andrew Yang

Prior probability
55.0%
Current probability
46.4%
evolves via intake + LBP
Conviction
5/5
Signal quality
B
Resolution
partial
Window
2026-01-01 – 2027-12-31
Edges in / out
4 / 0
Tickers exposed
5

Prediction text

The 2026-2027 window is the 'Great Disemboweling' of white-collar employment — millions of mid-career professionals (junior software developers, legal analysts, corporate marketers) lose jobs within a 12-18 month timeframe; resulting unemployment cascade will force Universal Basic Income (UBI) and specialized taxation on AI infrastructure. | Next BLS Q/Q white-collar employment contraction

Key catalyst: Next BLS Q/Q white-collar employment contraction

Watch events: BLS Occupational Employment Statistics; Fed SEP labor projections

Resolution evidence

Status: partial

Entry-level tech employment (<2yr experience) declining 15-20% YoY 2024-2026; Goldman Sachs 300M white-collar jobs exposure estimates; UBI pilots expanding.

Predictor: Andrew Yang

κ + Brier as of 2026-05-22
κ (discount)
0.688
Brier
0.0178
excellent
Hits / Misses
0 / 0
of 3 resolved
Hit rate
0.0%
Calibration plot (stated vs observed)

Evidence about this node from Andrew Yang is multiplied by κ in /api/intake. Lower κ = less weight; floors at 0.10 (effectively silenced) and caps at 1.00 (full weight).

Reference class

Not linked

This node isn't linked to a reference class. The Bayesian update applies without outside-view blending.

Probability over time

4 prob_history rows
0%25%50%75%100%prior 55%2026-04-302026-05-012026-05-03
intake v2milestone miss sweeplbp propagationreference class assignedlegacy v1prior_prob (analyst seed)current = 46.4%

Milestone chain

Pre-event signals (upstream prereqs + window checkpoints) → resolution event → downstream cascades. Status/dates update from linked nodes; re-derive nightly via scripts/ops/derive_milestones.py.
Leading chain: 4 overdue ⏱
  1. 2026-01-31overdueQ1 window check-in (25%)
  2. 2026-03-02overdueQ2 window check-in (50%)
  3. 2026-04-01overdueQ3 window check-in (75%)
  4. 2026-04-15 → 2026-04-30overdueBLS Q1 2026 white-collar employment data release
    How: Bureau of Labor Statistics Q1 2026 employment situation report — track software developer, financial analyst, paralegal, marketing manager occupation categories for material declines
    Source: https://www.bls.gov/news.release/empsit.toc.htm — BLS monthly employment situation reportconf 85%
  5. 2026-06-01 → 2026-12-31pendingCumulative AI-driven layoffs cross 100K in 2026
    How: layoffs.fyi tracking shows ≥100,000 layoffs in 2026 explicitly cite AI automation/restructuring as primary driver
    Source: https://layoffs.fyi/ — community-tracked layoff database. Bloomberg labor coverage. Recent Block ~4K cuts (Feb 2026) precedent (per IND_021).conf 55%
  6. 2026-04-01 → 2027-06-30pendingFirst named F500 cuts ≥30% of legal/marketing/finance workforce
    How: Public announcement (8-K filing, press release) by F500 company of ≥30% headcount reduction in white-collar function citing AI automation
    Source: SEC 8-K filings, Bloomberg, Reutersconf 45%
  7. 2027-01-01 → 2027-12-31pendingUBI policy proposal advances in major economy
    How: Federal-level UBI bill introduced in U.S. Congress, EU directive proposed, or pilot program announced by G20 government as policy response
    Source: Congress.gov, European Commission press, OECD reportsconf 30%
    Notes: Yang's prediction explicitly chains to UBI as policy outcome. Low confidence — political will lags technological displacement.
  8. 2027-06-01 → 2028-06-30pendingAI-infrastructure-specific taxation proposed in U.S./EU
    How: Specific tax legislation proposed targeting AI compute infrastructure (data centers, GPU sales) — beyond general corporate tax
    Source: Congressional Budget Office analyses, Tax Foundation, EU directive proposalsconf 25%

What if this resolves?

Clamp this prediction TRUE or FALSE and run a counterfactual Gibbs sample. Surfaces the predictions whose marginals shift most under that assumption.
(live posterior: 46%)

Click a button to clamp this prediction and run a Gibbs sample. Returns the predictions whose marginals shift most. ~30s per run; ideal for stress-testing "if X resolves, what else moves?"

Evidence chain

Every probability update with full Bayesian provenance — chronological, latest first
LBP2026-05-03T02:00:01Z46.4%-1.5pp
Network propagation: 47.9% → 46.4%
6-iter LBP, residual 0.00677 · damping 0.5, w_intrinsic 0.5 · method lbp_v3 · run 1a683ac9
resolution_terminal2026-05-01T00:00:00Z50.0%+2.1pp
resolution_terminal partial outcome=0.5 pre_resolution=0.479
Raw metadata
{
  "source": "backfill_resolution_history.py",
  "status": "partial",
  "bayesian_v2": false,
  "outcome_prob": 0.5,
  "evidence_kind": "resolution_terminal",
  "posterior_prob": 0.5,
  "delta_to_outcome": 0.021079999999999988,
  "inside_posterior": 0.47892,
  "validation_notes": "Entry-level tech employment (<2yr experience) declining 15-20% YoY 2024-2026; Goldman Sachs 300M white-collar jobs exposure estimates; UBI pilots expanding.",
  "validation_status": "hit",
  "pre_resolution_prob": 0.47892,
  "resolution_evidence": "Entry-level tech employment (<2yr experience) declining 15-20% YoY 2024-2026; Goldman Sachs 300M white-collar jobs exposure estimates; UBI pilots expanding.",
  "does_not_update_current_prob": true
}
LBP2026-04-30T16:39:51Z47.9%-2.4pp
Network propagation: 50.3% → 47.9%
5-iter LBP, residual 0.00825 · damping 0.5, w_intrinsic 0.5 · method lbp_v2 · run 0c8a4ea3
LBP2026-04-30T02:18:57Z50.3%-4.7pp
Network propagation: 55.0% → 50.3%
5-iter LBP, residual 0.00825 · damping 0.5, w_intrinsic 0.5 · method lbp_v1 · run 592311ef

Network propagation neighbors

Top edges sorted by latest LBP cross-impact
All propagation →

Top incoming (parents)

Edges that influence THIS node's belief

KindNodeTheir probP(c|s=T)P(c|s=F)Δ implied
killerTK04
Macro Recession 2026-27 (Structural Deleveraging)
25.0%0.0500.550-0.039
killerTK01
AGI Capability Plateau (2026-27 Training Stall)
15.0%0.0500.550+0.011
killerTK07
Labor Political Backlash (UBI Mandate / AI Tax)
18.0%0.0500.550-0.004

Top outgoing (children)

Predictions THIS node influences

No outgoing edges.

Ticker exposure

5 ticker(s) linked

Adverse (5)

ACNCTSHIBMINFYWNS

Prerequisites (4)

Predictions that must hit first
TypePredTitleDomainLag
correlateS_RECESSION_2026NBER recession declared 2026macro_recession
killerTK04Macro Recession 2026-27 (Structural Deleveraging)
killerTK07Labor Political Backlash (UBI Mandate / AI Tax)
killerTK01AGI Capability Plateau (2026-27 Training Stall)

Dependents (0)

Predictions enabled by this
TypePredTitleDomainLag
No dependents

Validations (1)

Resolution events
Observed atStatusByNotes
2026-04-29hitthesis_timeline_v1.0_importEntry-level tech employment (<2yr experience) declining 15-20% YoY 2024-2026; Goldman Sachs 300M white-collar jobs exposure estimates; UBI pilots expanding.

Linked documents (10)

Auto-generated by cosine similarity from Polymarket / Manifold / EDGAR / GDELT
SimSourceTitleMarket probPolarityReviewedPublished
0.703manifoldWill I lose my current job by the end of 2026?23%mentionspending2026-05-11
0.694manifoldWill US unemployment exceed 5% in 2026?29%mentionspending2026-06-04
0.681manifoldWhich sector will see the highest % of jobs displaced by AI in the US by end of Dec 31, 2026?mentionspending2026-05-01
0.680manifoldWill the May 2026 U.S. unemployment rate be at least 4.3%?82%mentionspending2026-06-03
0.677manifoldWill the May 2026 U.S. unemployment rate be at least 4.5%?14%mentionspending2026-05-18
0.669manifoldWill the US unemployment rate be >=6.4% in April 2028?27%mentionspending2026-04-23
0.668manifoldWill the May 2026 US nonfarm payrolls report show fewer than 100,000 jobs added?67%mentionspending2026-05-16
0.665manifoldWill the share of Americans in the workforce drop below 61.5% in 2026?60%mentionspending2026-06-02
0.640manifoldWill May 2026 US nonfarm payrolls increase by at least 150,000?22%mentionspending2026-06-02
0.638polymarketTrump out as President before 2027?10%mentionspending2025-11-05

Raw metadata

From Thesis_Timeline_v1.0_FINAL workbook
{
  "nia": false,
  "qty": "millions of jobs",
  "mode": "FORECAST",
  "role": "Cited-Politician",
  "context": "Yang's distinctive 2026 framing. Extends 234_034 (20-50% white-collar displacement 1-2yr). The 'Great Disemboweling' coinage is new; 12-18 month specific timeframe more aggressive.",
  "to_year": 2027,
  "conv_cues": "coined term; specific cohort; explicit policy response",
  "direction": "HAPPEN",
  "from_year": 2026,
  "timeframe": "2026-2027",
  "conv_level": "HIGH",
  "milestones": [
    {
      "kind": "quartile_checkpoint",
      "label": "Q1 window check-in (25%)",
      "status": "overdue",
      "weight": 0.05,
      "ordinal": -4,
      "source_id": null,
      "expected_date": "2026-01-31",
      "observed_date": null,
      "miss_emitted_at": "2026-05-02T22:07:21.384228+00:00",
      "miss_emitted_by": "metadata_milestone_sweep"
    },
    {
      "kind": "quartile_checkpoint",
      "label": "Q2 window check-in (50%)",
      "status": "overdue",
      "weight": 0.05,
      "ordinal": -3,
      "source_id": null,
      "expected_date": "2026-03-02",
      "observed_date": null,
      "miss_emitted_at": "2026-05-02T22:07:21.384228+00:00",
      "miss_emitted_by": "metadata_milestone_sweep"
    },
    {
      "kind": "quartile_checkpoint",
      "label": "Q3 window check-in (75%)",
      "status": "overdue",
      "weight": 0.05,
      "ordinal": -2,
      "source_id": null,
      "expected_date": "2026-04-01",
      "observed_date": null,
      "miss_emitted_at": "2026-05-02T22:07:21.384228+00:00",
      "miss_emitted_by": "metadata_milestone_sweep"
    },
    {
      "kind": "llm_pre_event",
      "label": "BLS Q1 2026 white-collar employment data release",
      "source": "https://www.bls.gov/news.release/empsit.toc.htm — BLS monthly employment situation report",
      "status": "overdue",
      "weight": 0.4,
      "ordinal": -1,
      "source_id": null,
      "confidence": 0.85,
      "source_url": "https://www.bls.gov/news.release/empsit.toc.htm",
      "expected_date": "2026-04-22",
      "miss_emitted_at": "2026-05-02T22:07:21.384228+00:00",
      "miss_emitted_by": "metadata_milestone_sweep",
      "research_origin": "training",
      "expected_date_range": {
        "to": "2026-04-30",
        "from": "2026-04-15"
      },
      "measurement_criterion": "Bureau of Labor Statistics Q1 2026 employment situation report — track software developer, financial analyst, paralegal, marketing manager occupation categories for material declines"
    },
    {
      "kind": "event",
      "label": "The 2026-2027 window is the 'Great Disemboweling' of white-collar employment — millions of mid-career professionals (junior software develop",
      "status": "partial",
      "weight": 1,
      "ordinal": 0,
      "source_id": "AI_021",
      "expected_date": "2026-05-01",
      "observed_date": "2026-05-01"
    },
    {
      "kind": "llm_pre_event",
      "label": "Cumulative AI-driven layoffs cross 100K in 2026",
      "source": "https://layoffs.fyi/ — community-tracked layoff database. Bloomberg labor coverage. Recent Block ~4K cuts (Feb 2026) precedent (per IND_021).",
      "status": "pending",
      "weight": 0.4,
      "ordinal": 1,
      "source_id": null,
      "confidence": 0.55,
      "source_url": "https://layoffs.fyi/",
      "expected_date": "2026-09-15",
      "research_origin": "training",
      "expected_date_range": {
        "to": "2026-12-31",
        "from": "2026-06-01"
      },
      "measurement_criterion": "layoffs.fyi tracking shows ≥100,000 layoffs in 2026 explicitly cite AI automation/restructuring as primary driver"
    },
    {
      "kind": "llm_pre_event",
      "label": "First named F500 cuts ≥30% of legal/marketing/finance workforce",
      "source": "SEC 8-K filings, Bloomberg, Reuters",
      "status": "pending",
      "weight": 0.4,
      "ordinal": 2,
      "source_id": null,
      "confidence": 0.45,
      "expected_date": "2026-11-14",
      "research_origin": "training",
 
... (truncated)