Everything on the main page comes from documents the district has already published. Nothing here uses student records, and nothing here could — student-level data is protected and was never public. This page states exactly how each figure was produced and where it is soft.
Capacity and projection figures are parsed directly from the projection tables in RSP's March 2026 Enrollment Analysis (slides 49–52). As a check, the parsed East feeder rows reproduce the table in the 22 June BOE deck exactly — Corinth 609/638/643/655/674 and Highlands 255/245/244/244/242. These numbers are the district's, unaltered.
RSP renders every map in the report from one GIS base template. We tested this by isolating the
purple district-boundary outline on nine separate map pages and cross-correlating them against a
reference page across a range of vertical and horizontal shifts. Every page returned a best
alignment at dy=0, dx=0.
Because the pages are pixel-registered, the elementary boundary map (slide 9) and the median home value map (slide 31) can be overlaid directly. No projection, warping, or control-point fitting is involved, so no georeferencing error is introduced.
Legend swatch colours were sampled for the five assessor value bands and all 34 school fill colours. Every pixel in the map panel was assigned to its nearest legend colour within a fixed tolerance; unmatched pixels (roads, labels, parks, water) were discarded. School masks were cleaned by morphological closing, hole filling, clipping to the eastern strip, and keeping the dominant connected component. Results were validated by checking that each school's centroid falls in its correct real-world position relative to the others — all eight do.
Limitation. These figures are the share of land area in each value band. They are not household counts and not student counts. They describe housing stock composition, which is what RSP's map depicts. A household-weighted version would require the district's parcel data.
RSP publishes a student density heat map (slide 85) with a continuous colour ramp. We sampled that ramp and inverted it to recover relative density per pixel, then integrated density within each attendance area.
Across schools, the ratio of known enrollment to integrated density varies (roughly 0.04–0.19), because the heat surface is kernel-smoothed. So we do not use it to predict enrollment. We use it only to apportion students within a single school, calibrated so that the school's total equals RSP's own published figure. Under that calibration the unknown scaling factor cancels out.
Limitation. Kernel smoothing spreads density across boundaries, so apportionment near an edge is less reliable than in the interior. Figures are rounded and presented with a tilde throughout.
Corinth Elementary sits at 83rd Street and Mission Road, so the school's own map marker locates the street. We isolated the dark maroon elementary-school markers on slide 9 and found the one inside the Corinth zone: it sits 32% of the way down from the zone's northern edge. The published proposal makes 83rd Street the northern boundary, so we model that as removing the northern 32% of the attendance area.
Limitation. This is a calibration from a map marker, not a survey. The published maps do not include a coordinate grid. If the district states the actual figure, we will use theirs and correct this page.
If any figure here is wrong we want to know, and we will publish the correction with the same prominence as the original claim. The district can settle most of these questions by releasing data it already holds.