← All proof trees · THOMAS HOLME SCHOOL

1. 1
   What you seeWithheld by the publisher

   The publisher suppressed this cell (too few students to report). The site stores it as suppressed and never as zero.

   vs. peers

   —

   vs. citywide

   —

   unit

   percent

   direction

   higher is better

2. 2
   How it was computedvalue = the state's published percentage for the school × subgroup, as-is

   1. Read the state's wide-format datafile: one row per Pennsylvania school, one column per measure × subgroup (e.g. PercentPersistentAttendance_Black).
   2. Keep Philadelphia rows by mapping the state's AUN + Schl codes to the district's ULCS code through the Master School List.
   3. Unpivot each recognized measure × subgroup column into one served cell; state suppression codes ('IS', '--', '*') are stored as suppressed.

   Note: stored percentiles are computed by a batch script after loads; a difference from the live reconstruction means a newer load changed the comparison set and the batch has not been re-run.

   Evidence: metric tree: Keystone Algebra I proficiency

3. 3
   The stored cellThe stored cell

   table

   philly_school_year_metrics

   value

   null

   denominator

   null (not published)

   suppressed

   true

   citywide_percentile

   null

   comparison_group_percentile

   null

   source_load_id

   8ba7d9e6-a94a-4a6f-9e9b-ceb2707d43de

   Evidence: data model overview

4. 4
   The load that wrote itWritten on 2026-09-08 by futurereadypa_performance.ts

   source id

   futurereadypa_performance_2024-25

   file URL

   https://futurereadypa.org/home/getdatafile?id=60

   SHA-256 of the file read

   a16ffc40e7d1851d5ac83dd63d8ca5348ead064e029bade593a0182ed085bc92Copy hash

   bytes

   5,113,152

   year covered

   2024-25

   code commit

   c19ea6ec845c65bcc40eb49644be1c7e67b05f25

   To confirm you have the same file: download it from the URL above, then run shasum -a 256 <downloaded file> Copy command — the output should equal the hash above. If the publisher has since replaced the file, the hashes will differ, which is itself useful to know.

   Evidence: loader script · first-fetch findings for this file · source registry

5. 5
   The publisher's fileFuture Ready PA Index datafile, 2024-25

   Pennsylvania Department of Education (Future Ready PA Index). The state's school-level accountability indicators for every public school in Pennsylvania — test proficiency, growth (PVAAS), persistent attendance, graduation — by subgroup.

   format

   XLSX (wide: one column per measure × subgroup)

   join key

   AUN + Schl (state IDs), mapped to ULCS via the Master School List

   landing page

   https://futurereadypa.org/Home/DataFiles

   • The chronic-absenteeism column exists in the file but is empty for individual Philadelphia schools; the state reports persistent attendance instead.
   • Publishes no student counts for the attendance measure.
   • Its 90%-attendance figure does not match the district's for the same schools (see the cross-publisher check).
6. 6
   How it was checkedChecks: 1 passed, 1 flagged

   • ✓ passedBase case (district file, 2024-25): 54 of 54 unsuppressed cells match
   • ⚠ flaggedCross-publisher sanity check (state vs district)

   Checked at ±1: 0 mismatches, 0 cells served but absent from the file, 0 in the file but not served (ALL, acct, latest year).

   Evidence: Base case (district file, 2024-25) · Cross-publisher sanity check (state vs district)

7. 7
   Assumptions & caveatsAssumptions and caveats

   • The state's AUN + Schl → ULCS mapping from the 2024-25 Master School List is correct. State rows for schools not in that directory — district schools that closed before 2024-25 — are not loaded, so every year of state data is a survivor-only panel; cyber charters have their own AUNs and are outside the district's directory.
   • Where two directory schools share a state code (a school and its Continuation Academy), the state's single row belongs to the main school (deterministic rule; the full absenteeism QA lists every shared code).

   • Served from both the district's file (district-run schools) and the state's file (all schools); check the load record on a cell to see which.

   Algorithms involved: Reading the state's wide-format datafile, Citywide and peer-group percentiles, Peer groups: 40 nearest neighbors on demographics