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1. 1
   What you seePVAAS growth — ELA/Literature

   100.00

   the state's PVAAS growth index for English/literature — whether the school's students grew as much as expected (the state's value-added score, on its own scale).

   vs. peers

   —

   vs. citywide

   85th percentile

   unit

   index (publisher's scale)

   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.

   Citywide percentile, reconstructed right now

   Among 286 default-included schools with a value for this metric, year, and subgroup, this school has a higher value than 200 and ties 85. Midrank rule: (200 + 85/2) / (286 − 1) = 0.851.Stored: 0.851. ✓ matches

   How percentiles are computed · How peer groups are chosen

   This school has no peer group (its filtered universe had fewer than 5 candidate schools), so no peer percentile.

   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: PVAAS growth — ELA/Literature

3. 3
   The stored cellThe stored cell

   table

   philly_school_year_metrics

   value

   100

   denominator

   null (not published)

   suppressed

   false

   citywide_percentile

   0.8509

   comparison_group_percentile

   null

   source_load_id

   e032c169-8d6b-41ae-acc1-d1662894df3e

   Evidence: data model overview

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

   source id

   futurereadypa_performance_2022-23

   file URL

   https://futurereadypa.org/home/getdatafile?id=44

   SHA-256 of the file read

   81fdf381405cc672abedc15bd58df21600418ca60df5c72dcf5e865581afb79dCopy hash

   bytes

   4,888,926

   year covered

   2022-23

   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, 2022-23

   Pennsylvania Department of Education (Future Ready PA Index). Same structure as the 2024-25 file.

   format

   XLSX (wide)

   join key

   AUN + Schl → ULCS

   landing page

   https://futurereadypa.org/Home/DataFiles

   • Same as 2024-25.
6. 6
   How it was checkedChecks: 0 passed, 1 not run

   • ○ not runBase case against the state file not yet run for this metric (the loader is shared with keystone_algebra_proficiency, whose SDP-side base case passed)
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).

   • The state publishes no student counts for most measures, so served cells carry no denominator.

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