Commit Graph

6 Commits

Author SHA1 Message Date
Fabio 316c4e563c Documentation: accurate README + full /docs tree
The README described intent; the repo is now real. Rewrote it to reflect
what actually exists — 17,506 validated files across four entity types,
the deterministic pipeline, the commands — and added the /docs tree:

  government-as-code.md  the philosophy: git primitives -> government
  data-model.md          entity types, IDs, file format, the tree, determinism
  sources.md             where every fact comes from, and how current
  roadmap.md             done / next / later, honest about what isn't built
  contributing.md        the disciplines, and how to add a source

Plus data/sources/sources.yaml — the machine-readable source registry.

Every count, path, and source claim is grounded in the current tree, not
the aspirational brief. Internal links verified; validation still clean.

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
2026-07-04 08:38:06 -04:00
Fabio 5b0712c31f Add elections + demographics layer: candidates and jurisdictions
Two new entity types, built deterministically from the raw exports:

  Candidate (2,494)     — 2026 federal candidates as files under
                          us/states/<st>/candidates/, with office,
                          district, party, incumbent/challenger stance,
                          campaign committee, FEC id.

  Jurisdiction (3,494)  — demographic nodes carrying ACS 2023 data:
                          3,131 counties (deduped from 3,231 mixed-format
                          fips keys) + 363 congressional districts.

This completes the county skeleton nationwide: every US county is now a
browsable node with population, income, poverty, race, education and
housing — even where no officeholders are mapped yet. In Florida the
county index.md merges into the existing dir and reports its officeholder
count alongside demographics (St. Lucie: 33 officeholders + ACS profile).

build.py now reads seven raw inputs in one deterministic pass
(byte-identical on rerun). The mirror now answers: who holds power, who
runs this institution, who is running, and what each place is made of.

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
2026-07-03 23:35:00 -04:00
Fabio 6b3249ecc0 Raw exports: FEC candidates + ACS demographics
Three new source datasets from Atlas, committed as-is before any build:

  fec_candidates.jsonl  2,494  2026 federal candidates (officeholders.fec_data)
  acs_county.jsonl      3,231  Census ACS 2023 by county (~100 dup keys to dedupe)
  acs_cd.jsonl            363  Census ACS 2023 by congressional district

A new axis for the mirror: who is running (candidates) and the
demographics of each place (ACS). Keyed on fec_id / state+district /
county_fips — no person links yet. Raw first; the build into Candidate
and Jurisdiction entities follows.

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
2026-07-03 23:30:05 -04:00
Fabio d6874ca8a6 Close the institutional gap: bodies, committees, leadership
The seat data answered 'who represents this place?' but not 'who runs
this institution?' — the Speaker of the House existed only as the rep
for LA-4. This adds the missing axis of institutional power.

New Body entities (233): the U.S. House, U.S. Senate, Executive Office,
49 committees, 181 subcommittees — each with its leadership.

Federal people (532/542) enriched with bioguide IDs, leadership roles,
and committee seats, reconciled from congress-legislators by name.
Mike Johnson is now Speaker of the House, not just LA-4.

Sources ingested directly into the repo (repo-canonical): Atlas
supplied bodies/leadership/committee_memberships via congress-legislators,
committed raw in data/. build.py supersedes convert_officeholders.py and
reads all four inputs in one deterministic pass (byte-identical on rerun).

The 10 unenriched federal records are a finding, not a bug: vacancies,
the President, and ~5 seats where Atlas's roster disagrees with the
authoritative current roster — model-vs-reality discrepancies to surface.

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
2026-07-03 20:51:07 -04:00
Fabio 1545fcf5ca Raw JSONL to structured tree: 11,285 entity files
One record, one file. The jurisdiction tree is now real:

  us/people/                          542 federal
  us/states/<xx>/people/            7,561 state
  us/states/fl/counties/<c>/people/ 1,058 county
  .../municipalities/<m>/people/    2,124 municipal (67 FL counties)

Each file is OKF markdown + YAML frontmatter: fixed key order,
field-level source provenance, Atlas UUIDs for round-tripping,
deterministic paths and slugs. Converter passes the determinism
test: two runs, byte-identical tree.

Generated by scripts/convert_officeholders.py from
data/officeholders-v2.jsonl (unchanged).

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
2026-07-03 18:08:31 -04:00
Fabio 710405d710 Raw Atlas export: officeholders v2 (11,285 records)
The only surviving copy of the dataset after the DB loss on
10.0.0.116 — committed as-is, before any transformation.
Federal (536), state (7,560), county (1,057), municipal (2,118)
current officeholders. Source: Atlas via /depot/exports,
generated 2026-07-03.

Raw first, refined later: the conversion into structured entity
files will itself be a visible diff.

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
2026-07-03 17:31:05 -04:00