PolicyEngine / PolicyEngine/microcosm

Build N epic: CD target surface + base rebuild bundle (quartet, assets, QRF fix, feed regen, gate hardening)

Open
#449 22 comments 0 reactions 0 assignees View on GitHub

Nobody has claimed this yet.

Dominant language
Python
Stars
0
Forks
4
Avg merge
1d 3h
Merged PRs (30d)
94

Description

Max greenlit (2026-07-17) the congressional-district target surface as the next build after the Build M certification: "yes do it."

What

Turn on --include-congressional-district-targets for the next certified US build (Build N), expanding the calibration surface from the national+state class (~5,667 compiled targets in Build M) to the full geographic feed surface: the v8 Ledger feed carries 23,968 congressional-district facts alongside 11,191 state and 2,101 national — a ~30k-target-class surface.

Mechanics already in place

  • The builder flag exists and is opt-in-off; the compile path translates CD facts via --congressional-district-vintage-crosswalk (source vintage → current districts) and hard-requires household.congressional_district_geoid on the support frame — which the Build M frame already carries (export parity tracks it at +2.3% drift).
  • gate_congressional_district_targets currently records False in build manifests; Build N flips it to a gated surface.

Work items

  1. Crosswalk provenance: pin the source-to-119th crosswalk artifact (sha-pinned input, #288 alignment); the checkpoint identity and materialization-cache context already carry its sha.
  2. Preflight sizing (no solve): compile the CD-included registry, run the #436 preflight zero-support/support-expressibility pass over the 57k sparse selection — CD cells are exactly where a frozen sparse support goes thin (the Build G #299 exclusion class). Expect a batch of per-cell reviewed exclusions or a reselection decision; adjudicate BEFORE burning a run (the campaign's attempt-9/10/11 lesson, now tooled).
  3. Solve-cost calibration: ~5.4× more constraint rows; measure a bounded-epoch dense probe before committing the full ladder. Loss-weighting review for the CD family (11k state rows already dominate counts; 24k CD rows will need family-level weighting the same way state rows got it).
  4. Gate adjudication pass: within-10% and zero-support baselines will move on a 30k surface; set expectations from the probe, not Build M's 90.2%.
  5. Scorecard: report Build N vs Build M on the shared national+state subset AND the CD surface separately, so the flip decision compares like with like.

Sequencing

After the Build M cert (policyengine.py#475) lands. Interacts with the geography-ladder/ACS lane (#288, Build L plan): the CD vintage story should be settled once and shared between calibration targets and the geography assignment.

Contributor guide

Open the contributing guide

First steps

  1. Read the whole issue, then the project's contributing guide.
  2. Comment on the issue to say you are picking it up — it saves two people doing the same work.
  3. Fork the repository and make your change on a branch.
  4. Open a pull request that references the issue number.

Research direction

Start with the Build M certification reference at policyengine.py#475, then inspect the existing congressional-district builder flag and the #436 preflight flow. Review the #288 crosswalk alignment and #299 exclusion precedent before compiling the CD-included registry. Done means a provenance-pinned crosswalk, preflight findings, bounded solve-cost and weighting measurements, gate expectations, and shared-subset plus CD scorecards.

Written by the indexing model from the issue text.

Assessment

Tech stack
python
Domain
build-system, data-engineering, machine-learning
Issue type
Feature
Difficulty
5/5
Estimated time
Over a week
Activity status
Quiet
Clarity
Mostly clear
Newbie friendliness
25/100

Get new issues in your inbox

A short digest of beginner-friendly GitHub issues.