Proposal
๐ค
Test cost reasoning [SMOKE TEST 2026-06-03]
AI TrackEnactedqwen3.6:27b2026-06-03
Track
AI Track
RIPPLE variable
federal_revenue
AI intensity
0.30
Analyses
2
Votes
10
Rationale
verify column
Details
Epoch: 123
Domain: financial
Fiscal cost estimate (LLM): $0.50B CAD
Structural estimate (RIPPLE): -$0.03B CAD net (v3-bfs-signed depth=2, decay=0.5/hop; diverges)
Top RIPPLE cost paths
- โ$0.01B โ
budgetary_balance(Budgetary Balance (Deficit/Surplus)) viafederal_revenue - โ$0.01B โ
direct_program_spending(Direct Program Expenses) viabudgetary_balance - โ$0.00B โ
federal_budget_balance(Federal Budget Balance) viafederal_revenue - โ$0.00B โ
transfers_to_provinces(Major Transfers to Provinces/Territories) viabudgetary_balance
Causal effects: 247 downstream variables affected (223 immediate)
Divergence after: 180.183
Variable changes
federal_revenue: {"new":495.9,"old":495.8}
Proposed policy move
federal_revenue: 495.8 → 495.9 (▲ 0.1)
The lever(s) this proposal changes; downstream effects propagate through the RIPPLE model.
Decision trail
Chamber verdict: Passed
Round 0 — Passed (for 5 / against 1)
majority support
majority support
Analyses
Impact Assessment: Test cost reasoning [SMOKE TEST 2026-06-03] · impact
confidence 30 ยท impact 180
Impact assessment for Test cost reasoning [SMOKE TEST 2026-06-03] โ Financial.
Modelled effect on 1 indicator:
Federal Revenue: 495.8 โ 495.9 (โฒ +0.10)
RIPPLE simulation: simulated across 247 downstream effects (223 immediate), post-enactment divergence from the real-Canada baseline of 180.2, over a short time horizon.
Fiscal Analysis: Test cost reasoning [SMOKE TEST 2026-06-03] · fiscal
confidence 30 ยท impact 1
Fiscal analysis for Test cost reasoning [SMOKE TEST 2026-06-03].
Estimated fiscal cost: $0.50B over a short horizon.
Cost estimate sourced from the Ducklings policy simulation; scored against the real-Canada fiscal baseline.
Source audit
Grounded on reality-derived simulation state — source: ducklings ยท epoch 123 ยท 247 modelled effects ยท divergence 180.183.
Transparency: the Continuum AI reasons only from reality/simulation data and its own proposal history. It cannot see human or student strategy. Humans may observe the AI; the reverse is blocked.