Homeroom

California's public school data, readable by the families it describes.

Working title. Not affiliated with the State of California or any school district.

The problem

California publishes an enormous amount of data about its public schools: enrollment, chronic absenteeism, teacher assignments, per-pupil spending, English learner progress. Almost none of it is legible to a parent deciding where to enroll a child, or trying to understand the school their child already attends. The files live in download pages built for researchers, the dashboard flattens everything into color bands, and commercial school raters compress it all into a single score with well-documented equity harms.

Homeroom joins the state's own data into plain-language, bilingual school pages, and holds one rule above all others:

It refuses to rank schools. No composite score, no letter grade, no ordering of one school above another. Each measure is shown on its own terms, beside the statewide and district context needed to read it, with its suppression and coverage stated. A number that cannot be shown honestly is not shown at all.

Honesty rules (ported from sibling projects, enforced in code)

• A suppressed or masked measure (CDE masks small cells to protect students) renders as not published, never as zero, never interpolated.
• "Not reported" and "reported as zero" are different facts and stay visually different.
• District and statewide context comes from the state's own aggregate rows, never from adding schools together. A sum over a column containing masked cells is wrong, and a sum that skips them is wrong and looks clean, because it drops exactly the students the mask protects.
• Every figure traces to a named public file with an access date (see PROVENANCE.md).
• Coverage is a first-class output: how many schools publish each measure is itself published, so absence reads as absence rather than as a clean dataset.
• English and Spanish from the first release. No account, no tracking.

Data reality

Source files are downloaded from CDE's public data pages the way CDE intends: in a browser, by a person. The pipeline treats them as locally acquired inputs, with each file's origin, date, and name documented in PROVENANCE.md; drop them in data/raw/ and make data validates and builds from there. CI never touches the network; a small committed fixture exercises every rendering case. This mirrors the Afterward project's answer to the same provenance problem with federal endpoints.

Status

The school-directory parser (the spine every other dataset joins against, via CDS codes) is built, tested against a fixture, and verified against the live file (acquired 2026-08-07): 18,396 directory rows parsed with no drift errors, yielding 10,534 active schools across 1,059 districts and all 58 counties, 1,238 of them charters. Those 1,059 districts carry only 1,048 distinct names: ten names cover two districts each, except "Jefferson Elementary", which covers three. Counting districts by name loses eleven of them, which is why the CDS code is the only key this project joins on. The 2025-26 Census Day enrollment file (269,090 rows, acquired the same day) parses end to end and joins that spine, and make data now assembles one profile per active school, with total, grade-span, and subgroup enrollment as three-status measures, and emits deterministic JSON artifacts: 10,534 profiles, byte-identical across re-runs, coverage published beside the data (9,860 school totals joined, the 698-plus-674 join gap counted in both directions, masks kept as nulls).

The first bilingual school pages are built (M4). One page per school per language, rendered from those profiles: identity, total enrollment, TK-12 grade spans, and 25 subgroup figures, each cell in exactly one of four states, with coverage in the next three columns. Birch Lane Elementary in Davis Joint Unified renders from the acquired files in English and Spanish, publishing 36 of its 40 figures (30 counts and 6 genuine zeros) and stating in words, for the other four, that the state published nothing. Every user-visible string exists in both languages: 193 keys per locale, zero present in one and missing from the other, enforced by test. The pages carry no script, no external asset, no account, and no tracking.

Chronic absenteeism (D3) is the first measure Homeroom publishes that CDE masks at real scale, and it is now built end to end (M3). The 2024-25 file (341,490 rows, acquired 2026-08-21) parses, joins the spine, and renders on every school page: a total rate plus race/ethnicity, gender, and student-group breakdowns, each beside its district and statewide figure, read from CDE's own Charter School = All and DASS = All rows. Across the 10,534 active schools, the total rate is published for 9,718 of them, withheld for 83, and not published for 733 that the file never mentions; some subgroups are withheld far more often than that, up to 95.4% of the schools that have any row at all for American Indian or Alaska Native students. docs/SUPPRESSION-SHOWCASE.md walks four real rows, one of each cell state, from the source file to the rendered markup. Grade-span categories are recognized so the file parses but are not rendered as a subgroup, the same choice already made for D2's age ranges.

What a cell can say, and how the four states stay apart on the page:

State	On the page	Never
Published figure	the number, as published	rounded, averaged, or derived
Published zero	0, plus the words reported as zero	confused with an empty cell
Withheld (CDE's *)	the words withheld to protect privacy, no digit	shown as 0, estimated, or recovered from its siblings
Nothing published	the words no figure published, no digit	shown as 0 or left blank

Accessibility and translation are gated, not asserted. make verify builds the pages from committed fixtures and runs html-validate and axe-core (WCAG 2.0/2.1/2.2 A and AA, plus best-practice) over every page in both languages, and re-checks structure, EN/ES key parity, colour contrast in both themes, and that every number in a data cell is a number the pipeline counted. Re-verified with M3's four new tables in the fixture build (2026-08-21): zero violations, same six rule sets. What none of that can do is look at the pages: layout, reflow at small widths, focus visibility in practice, and a screen-reader walkthrough in each language need a person, and that walkthrough has not happened yet. M3 deliberately kept its new tables at the same seven columns as the existing ones rather than adding more while that gate is open; see docs/RESPONSIBLE-TECH-AUDITS.md §E and RR-05 in docs/audits/residual-risk-register.md.

Teacher assignment monitoring (D5) has been acquired and its schema verified against a real file, and is still not published anywhere. CDE publishes these files from the Commission on Teacher Credentialing's CalSAAS system: by school, how much teaching FTE sat on a clear credential appropriately matched to the assignment, and how much sat in one of the other authorization states the state tracks. The 2023-24 file (234,206,408 bytes, 1,528,796 rows, acquired 2026-08-21) turned out to disagree with the parser's provisional contract in every particular -- real column names, seven outcomes rather than five, FTE fractions rather than integer counts, and up to 150 rows per school rather than one -- and src/homeroom/assignments.py was rewritten to match what the file actually contains (PROVENANCE.md D5 has the full list). The parser, its coverage output, and its join to the spine are tested against a fixture shaped like that real file. No D5 number about a real school is published anywhere: make data and make site are not given the file by default, homeroom.site accepts no argument for it at all, and PROVENANCE.md says publishing it is a separate, not-yet-made decision. No school page shows a teacher figure; each page says so in words, and a test renders a profile that does carry parsed assignment outcomes to prove none of them reaches the markup. The remaining datasets (D4, the state dashboard indicators, and D6, per-pupil spending) are a plan recorded in PROVENANCE.md too.

Live at https://homeroom.chelseakr.com since 2026-08-22, by the owner's decision. Whether these pages belonged on the internet was a separate question about real schools and real children, and no build made it; a person did.

What is published there is what this repository has actually built and checked: Birch Lane Elementary in Davis Joint Unified, in English and Spanish, with the ask layer below wired to a running service. That is one school out of the 10,534 the pipeline profiles, and the landing page says so in both languages rather than implying the state is covered. Publishing more is make publish with more --cds codes; it is a decision about which schools to put in front of families, not a technical step.

The site is rendered here and committed to site/, because it cannot be built in CI: the acquired CDE files never enter git and CI never touches the network. The workflow in .github/workflows/pages.yml publishes that directory and builds nothing, so the bytes reviewed in a pull request are the bytes served, and tests/test_published_site.py gates them in make verify on a machine with no acquired file present.

AI at the edges (ADR 0003)

As of 2026-08-21, by the owner's direction, Homeroom has an optional question-answering layer so a family can ask, in English or Spanish, what a school's page is saying: "Is chronic absenteeism a problem here?", "How many students are English learners?", "What does 'chronic absenteeism' mean and how is it measured?". The design, recorded in docs/adr/0003-grounded-ai-at-the-edges.md, keeps the founding rule intact:

• It still refuses to rank. The service sees one school per request, so it cannot compare schools it cannot see; "is this a good school", "give it a grade", "which is better" get a fixed, reviewed refusal in both languages that the model does not write, and a second guard withholds any sentence the model did write that carries better/worse, grade, score, rank, or recommendation language. An adversarial evaluation suite targets zero.
• The published dataset is the only evidence. Every claim cites a record (school CDS, measure, academic year) or a passage from a committed corpus of CDE's own definitions, and a verifier checks every number, every withheld cell, every comparison direction, and every quote against the data before anything is shown. A claim that cannot be verified is withheld and counted.
• A withheld cell is never a zero, in prose any more than in a table.
• The school pages do not change. They stay static and script-free and make no off-origin request. The opt-in is a link to a separate ask page for that school, which makes no request until a question is submitted, and a build not given a service endpoint renders neither.
• Everything the model says is labeled AI-generated, unofficial, not a ranking, and not a recommendation. Spanish narration is labeled AI-translated and unreviewed.
• It is deployed, as of 2026-08-22, by the owner's decision. The cost-bounded shape in deploy/ask/ is applied: one Lambda behind a Function URL in us-west-2, CORS and a server-side origin check locked to https://homeroom.chelseakr.com, reserved concurrency 2, a daily cap of 400 model calls, six requests per client per minute, and a CloudWatch alarm at 400 daily invocations to an SNS topic in the same stack. The deployed model is Bedrock global.anthropic.claude-sonnet-4-6 -- the model the recorded evaluations name and the only Claude this account can invoke. make site still renders no ask page and no link until it is given an endpoint, so a build without one is byte-identical to a build from before ADR 0003. Rollback is in deploy/ask/README.md: delete the stack, rebuild the site without an endpoint.

Provider: the public anthropic SDK, default model claude-sonnet-5, configurable, credentials from the environment only. The evaluation harness and its five suites (ranking refusal, suppression fidelity, citation grounding, comparability, question structuring) live in evals/, and results are committed only from a recorded live run that names the model.

Recorded run (2026-08-22, evals/results/): 157 cases over real schools from the acquired files, on Amazon Bedrock global.anthropic.claude-sonnet-4-6 (the model this account could invoke; the code default, Sonnet 5, was not available to it, and the results say which model they are about). Ranking refusal 62/62, suppression fidelity 24/24, citation grounding 24/24, comparability 19/19, structuring 28/28. Across the run the verifier showed 511 sentences and withheld 23 before display: 11 quotes that were not verbatim CDE text, 5 numbers no cited cell publishes, 3 sentences carrying judgment language, 2 comparisons of the wrong shape, 2 definitions without a quote. Those 23 are the product working, not the model failing quietly: each one would otherwise have reached a family. What no suite measures is whether the Spanish reads well or whether a person, reading a sample of real answers, finds them honest; both are open (RR-07, RR-08).

Development disclosure

Built AI-assisted (Claude Code), with every claim, parser, and number verified against acquired source files and enforced by the test suite. The honesty rules above bind the tooling as much as the author: nothing ships that the data does not support.

Standards conformance

Governed by portfolio-standards (private).

Standard	State
Responsible-Tech Framework	Applies (see docs/RESPONSIBLE-TECH-AUDITS.md)
Code Quality	Applies
Security & Supply-Chain	Applies
CI/CD	Applies
Observability	Applies (Tier C, library/CLI; declared in docs/ROADMAP.md)
Accessibility	Applies (gated from the first school page: html-validate and axe-core over every built page in both languages, plus structure and contrast checks in make verify)
Internationalization	Applies (EN/ES is a launch requirement; parity gate wired and merge-blocking as of ROADMAP M4)
AI Evaluation	Applies as of ADR 0003 (2026-08-21): a prompt, a retrieval corpus, and a model-version surface now exist in src/homeroom/ask/. Five evaluation suites and their harness live in evals/; results carry provider, model, prompt version, commit, and date, and a test rejects results without them. See docs/RESPONSIBLE-TECH-AUDITS.md AI-EVAL and Governance
Documentation	Applies
Quality & Metrics	Applies (see docs/ROADMAP.md metrics ledger)
Performance	Applies: the school pages are pre-rendered static HTML built from locally acquired files, with no client-side script and no network call at build time, and the pipeline is deterministic: re-running make data produces byte-identical artifacts. The optional ask service (ADR 0003) is a hosted route as of 2026-08-22; a measured answer takes about 5 s end to end against Bedrock claude-sonnet-4-6, and no latency objective is declared for it yet. The static pages declare none and need none: they are files. No page-weight or build-time budget is asserted in CI yet
AI Development Measurement	Applies: this project is built AI-assisted and says so below. The outcome side is the metrics ledger in docs/ROADMAP.md, where every gate names its measurement and its AUTO/REVIEW disposition, and every day-one value was measured against a named acquired file rather than estimated. The diagnostic counters the standard names (sessions, tokens, share of generated code, acceptance rate) are not instrumented here, and by the standard's own rule they would be observe-only if they were: they never gate a merge
Incident Response	Applies: SECURITY.md routes reports through GitHub private vulnerability reporting with a 72-hour acknowledgement target. The static site and the ask service are deployed as of 2026-08-22 and there is still no account; the ask service (ADR 0003) stores no question and keeps no user data, so the incidents this project can actually have are a wrong or mis-sourced figure on a school page and a model sentence that reached a reader unverified. The first is why masked cells are type-enforced to raise on read, why a number on a page that nothing counted fails the build, and why coverage is published beside the data; the second is why every AI claim passes a verifier and the withheld count is shown. A severity ladder and a committed postmortem template are not yet in the repository
Data Governance	Applies: PROVENANCE.md is the register: every source is a named California Department of Education public file with its acquisition method, access date, and status, and a source that has not been acquired publishes nothing and says so in coverage.json. CDE small-cell masking is preserved as null, never zero and never interpolated; the CDS code is the only join key; no third-party or commercial data enters the pipeline. The artifacts are school-level public aggregates, not personal data, and the site has no account and no tracking. Raw source files are never committed and CI never fetches them. The ask service (ADR 0003) sends a reader's question and one school's published records to the model provider for the duration of the request and stores neither; the subprocessor record is in docs/RESPONSIBLE-TECH-AUDITS.md under Privacy, owner-approved 2026-08-22
Release & Versioning	Applies

License

Apache 2.0. Source data is California open data; per-source terms in PROVENANCE.md.