f037c50736
- Project scope document (v0.1): objectives, data sources, key metrics, phases - Phase 1 implementation plan: IPEDS, IRS 990, BLS CPI-U acquisition for UD - CLAUDE.md: project context and conventions Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
67 lines
3.4 KiB
Markdown
67 lines
3.4 KiB
Markdown
# Admin Analytics
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University administrative cost benchmarking project using public data (IRS 990, IPEDS, BLS CPI-U). **First iteration is scoped to the University of Delaware only.** Peer/AAU/multi-institution comparisons are planned for a later iteration.
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## Project status
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Currently in planning. Phase 1 (Data Acquisition) is planned but not yet built. See `phase1_plan.md` for the full implementation plan and `administrative_analytics_scope_v0.1.md` for project scope.
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## Architecture
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- **Language:** Python
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- **Database:** DuckDB for Phase 1 (single-file, zero-config). Migrate to PostgreSQL in Phase 3 when the dashboard needs concurrent access.
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- **Package manager:** uv
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- **CLI framework:** typer or click (TBD)
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- **Testing:** pytest
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## Data sources
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| Source | Format | What we extract |
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|--------|--------|-----------------|
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| IRS 990 bulk XML | XML (versioned schemas) | Filing financials, Part VII compensation, Schedule J detailed compensation |
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| IPEDS | CSV bulk downloads | Institution directory (HD), finance by function (F1A/F2), staffing (S/SAL), enrollment (EF) |
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| BLS CPI-U | Flat file or API | Consumer Price Index for inflation-adjusted compensation analysis |
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| Admin office web pages (stretch) | HTML scraping | Staff directory headcounts |
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## Key concepts
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- **University of Delaware** is the sole target institution for the first iteration. UD's IPEDS UNITID is the anchor for all IPEDS queries.
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- **UD is a public university** and does not file an IRS 990. However, the **University of Delaware Foundation** (a separate nonprofit) does file a 990 — this is the source for executive compensation (Schedule J) and philanthropic data.
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- **UNITID** is the canonical institution identifier (from IPEDS). All cross-source linking flows through UNITID.
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- **EIN** links to IRS 990 filings. For the first iteration, only UD Foundation EIN(s) are needed. A broader UNITID-to-EIN crosswalk will be built when expanding to peer institutions.
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- IRS 990 XML schemas change across tax years. Use the Master Concordance File or IRSx library to handle XPath variations.
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- IPEDS variable names change across years. Always parse the accompanying data dictionary; never hardcode variable names.
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## Planned project structure
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```
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src/admin_analytics/
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config.py
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cli.py
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db/ # DuckDB schema and connection
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irs990/ # 990 download, XML parsing, Schedule J extraction, university filtering
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ipeds/ # IPEDS download, dictionary parsing, finance/HR/enrollment loading
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bls/ # CPI-U fetcher and loader
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scraper/ # Stretch: admin office headcount scraper
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data/raw/ # Downloaded files (gitignored)
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tests/
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fixtures/ # Sample XML/CSV files for tests
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```
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## Build & run
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Not yet implemented. When built, the CLI will support:
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```
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admin-analytics ingest ipeds --year-range 2005-2024
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admin-analytics ingest irs990 --year-range 2005-2024
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admin-analytics ingest cpi
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admin-analytics ingest all
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```
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## Conventions
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- Raw data tables are prefixed with `raw_` (e.g., `raw_institution`, `raw_990_schedule_j`)
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- Downloaded files go in `data/raw/` and are gitignored
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- IPEDS variables are mapped to canonical column names at ingest time; raw CSVs stay on disk for reprocessing
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- First iteration filters all data to UD/UD Foundation only. Design parsers to accept institution filters so they can scale to multi-institution in a later iteration
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- 990 downloads are filtered by EIN from index files to avoid downloading the full archive (hundreds of GB)
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