Remove randomness from country package #1439
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Move stochastic variable generation to data package. Variables now read pre-computed values from datasets for deterministic, reproducible calculations. Changes: - would_claim_pc, would_claim_uc, would_claim_child_benefit, child_benefit_opts_out, would_evade_tv_licence_fee, household_owns_tv, main_residential_property_purchased_is_first_home, is_disabled_for_benefits: Remove formulas, use default_value - would_claim_marriage_allowance: New variable for take-up decision - marriage_allowance: Use would_claim_marriage_allowance instead of random() - attends_private_school: Use pre-generated random draw from dataset - is_higher_earner: Use age as deterministic tie-breaker instead of random() 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
4 tasks
Tests verify: - Default values work correctly in policy calculator mode - Variables can be explicitly overridden in situations - is_higher_earner uses deterministic tie-breaking (older wins) - Calculations are deterministic across multiple runs 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
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Summary
is_higher_earneruses age as deterministic tie-breaker instead of random noiseChanges
would_claim_pcdefault_value = Truewould_claim_ucdefault_value = Truewould_claim_child_benefitdefault_value = Truechild_benefit_opts_outdefault_value = Falsewould_evade_tv_licence_feedefault_value = Falsehousehold_owns_tvdefault_value = Truemain_residential_property_purchased_is_first_homedefault_value = Falseis_disabled_for_benefitsdefault_value = Falsewould_claim_marriage_allowancemarriage_allowancewould_claim_marriage_allowanceinstead ofrandom()attends_private_schoolis_higher_earnerRelated PRs
Test plan
🤖 Generated with Claude Code