G3 Participation Diagnostics

Diagnostic analysis of Grade 3 participation rates and subgroup (IEP / ELL) consistency across Reading, Writing, and Math.

Section 1 — Per-Subject Participation Rates

pctFullyParticipating_* = share of registered students who fully completed each subject's assessment.

2024–25 — % fully participating, percentile distribution

N = schools in the bin from the previous break to this one (e.g. N at p1 = bottom 1% of schools). "Read % (adj)" uses pctFullyParticipating_ReadAdj: numerator = coalesce(cntFullyParticipating_Read, 0), denominator = max(cntStudents_Read, cntStudents_Math) — Math-only registered schools contribute 0% rather than null, so n = 3,162 vs 3,116 for the original.

School-level distributions — all years

Average registered count per subject per year

Identical lines confirm a shared registration list across subjects.

Section 2 — IEP (Special Needs) Cross-Subject Consistency (2024–25)

Overall school suppression (2024–25, English G3)

IEP count availability by subject (among results-provided schools)

Shows how often IEP counts are missing for one subject but not others. ✓ = non-null count, — = suppressed/absent.

IEP%: spread across R / W / M

schools have non-suppressed IEP counts for all 3 subjects. (%) have identical IEP% across all 3 subjects.

IEP%: Reading vs Math scatter

Points on the diagonal = identical IEP% in Reading and Math. Colour = spread bucket.

Section 3 — ELL Cross-Subject Consistency (2024–25)

ELL count availability by subject (among results-provided schools)

ELL%: spread across R / W / M

schools have non-suppressed ELL counts for all 3 subjects. (%) have identical ELL% across all 3 subjects.

ELL%: Reading vs Math scatter

Denominator for all rates: registered students (cntStudents_*) — the count enrolled for each subject's assessment. Absent = registered but did not write; Exempt = formally exempted before the assessment.

Absent %, Exempt % and Below L1 % of registered students — province, all years

Each line is one subject. Panels show absent, exempt, and below-Level 1 rates as a share of registered students. Below L1 = students who fully participated (wrote the assessment) but whose work could not be assigned a level.

Province-wide raw counts — registered, fully participating, absent, exempt

Section 5 — The 2021–22 → 2022–23 Participation Jump

FP% rose sharply between 2021–22 and 2022–23 — the first post-COVID return to normal assessment conditions. This section asks: Was the jump broad-based or concentrated in certain schools? And did bringing more students back into the assessed pool push L3/L4% down?

Breadth of the jump — distribution of school-level ΔFP% (2022→2023)

Each bar counts schools in a 2 pp bin. A tight distribution near zero = few schools changed; a spread-out distribution = the jump was widespread.

Was it driven by low-participation schools?

x = FP% in 2021–22, y = change from 2021–22 to 2022–23. Schools with near-zero 2022 FP% had only room to rise.

Did higher participation depress L3/L4%?

If the jump brought in lower-performing students who had been previously absent or exempt, schools with bigger ΔFP should show more L3/L4 compression (negative association). Each dot is a school; regression line added.