PolicyEngine / PolicyEngine/microcosm

CHIP enrollment targets are concept-mismatched: CMS total_chip_enrollment includes M-CHIP; model materializes separate CHIP only (20 states zero-support)

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Description

Finding (Build F, 2026-07-06)

The dense certified-lineage release failed its zero-support gate on exactly 20 cms_medicaid.month2024_12.state_enrollment.{state}.total_chip_enrollment@2024 targets: AK, CA, DC, HI, IL, KY, MD, ME, MI, MN, NC, ND, NE, NH, NM, OH, OK, SC, VT, WY.

That state list is not a sampling artifact (CA is in it, on a 337,704-household base). It corresponds to the Medicaid-expansion CHIP (M-CHIP) states: CMS's total_chip_enrollment counts M-CHIP + separate CHIP, while the model's materialized enrollment concept produces separate-CHIP-style membership only — so M-CHIP-dominated states materialize zero support for a positive target. A target-concept vs model-concept mismatch, not missing data.

Two consequences:

  1. The remaining ~30 states' CHIP targets are ALSO conceptually mixed (their totals include an M-CHIP share the model doesn't represent), so calibration over-pulls child weights there to hit an unreachable-by-concept total. The zero-support gate only catches the pure-M-CHIP extreme.
  2. Build F proceeded with a documented feed supersession (v6 = v5 minus exactly these 20 rows, sha 9f8edbb9...), which unblocks the gate but does not fix the concept.

Ask

Map the CHIP target family onto concepts the model actually materializes: either split CMS enrollment into M-CHIP vs separate-CHIP components at the ledger level (calibrating each against its true model concept), or add an M-CHIP-inclusive enrollment concept to the materialization. Related: #233 (Medicaid/CHIP spending targets), #170 (eligibility-to-enrollment diagnostics). Same disease as populace#320's capital-gains finding: targets and columns that encode program-structure concepts must be mapped explicitly, never assumed 1:1.

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 by tracing the CHIP target ledger, enrollment materialization, and calibration flow, then review related issues #233 and #170 for existing assumptions. Done means CMS M-CHIP and separate-CHIP targets are mapped to matching model concepts, rather than relying on the superseded feed that removes 20 rows.

Written by the indexing model from the issue text.

Assessment

Tech stack
python
Domain
data
Issue type
Feature
Difficulty
5/5
Estimated time
Over a week
Activity status
Quiet
Clarity
Needs clarification
Newbie friendliness
30/100

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