The corpus › Formula Component

FSFP Gifted Identification and Units

$54m, and the only one of the six that buys staff rather than pupils. Two per-pupil amounts and three kinds of unit, where a unit is a headcount entitlement priced at a salary-like figure. 87% of the program is unit funding. verified

formula-component/fsfp-gifted-units · 3 nodes point here · 2 corrections

The parameters are prices, not rates, which puts this component in a different family Contents

$85,776 a coordinator unit, $89,378 a K-8 intervention specialist, $80,974 a 9-12 one. Those are salary assumptions, so they belong with the staffing costs inside the base cost build-up and will move when those are refreshed — not with the weights, which are dimensionless multipliers of a base cost. Nothing else among the six behaves that way, so this is the one component a salary refresh moves directly. inference

The units are clamped, and the clamps are the policy Contents

A district that identifies no gifted pupils at all still draws 0.5 + 0.3 + 0.3 units — $93,993 before its state share. Gifted is the one categorical with a floor rather than a proportion. verified

Two denominators, one line apart Contents

Identification is $24 per K-6 pupil; referral is $2.50 per enrolled pupil. Adjacent rows in the same sheet, different bases, and neither name says so. verified

Professional development is a hard-coded zero Contents

[F3] is carried by the sheet as a value rather than a formula and is zero for every district. Like targeted assistance’s supplemental tier, it is a funded line at zero rather than an absent one — the column exists, the arithmetic sums it, and a future biennium can fill it without changing anything else. verified

What this repository computed Contents

Not what Ohio publishes. Figures derived here from committed fixtures, each one citing the test that reproduces it.

That is defensible and it is invisible. Units buy people, and half a coordinator is already the smallest thing a small district can be funded for. But 370 districts sit on the coordinator floor — three-fifths of Ohio — so for most of the state that line is a minimum rather than a measurement, and a district’s gifted total looks like a payment for gifted pupils while being substantially a payment for existing. 88 districts draw every one of their three unit entitlements at the floor. verified

The cap binds too, at the other end Contents

Eight coordinator units is reached at 26,400 enrolled pupils, and three districts are there. Columbus and Cleveland are funded for eight coordinators however many pupils they have; Cleveland’s enrollment earns 9.33. A floor and a cap on the same line means the middle of the distribution is the only place the ratio actually operates. verified

Identification rates do vary with wealth Contents

Gifted funding scales off identified FTE, so it depends on how many children a district identifies — a district practice as much as a pupil population.

identified share of enrollment, by quintile      Q1      Q5     ratio
ordered by valuation per pupil                10.1%   19.0%     1.9x
ordered by economically disadvantaged %       25.0%    8.6%     2.9x

Both gradients are monotone across all five quintiles. Poverty is much the stronger axis — r = −0.67 against r = +0.35 for property wealth — which is not what the question as posed expected, and is the more uncomfortable of the two answers. verified crates/project/tests/questions_the_corpus_left_open.rs

Why is not established, and three explanations fit Contents

The underlying distribution of the trait may genuinely differ; identification practice may differ, since screening costs money and staff; or the instruments used to identify may differ in what they measure. This data separates none of them and the corpus should not pick one. What it can say is that a funding stream keyed to identification pays most where identification is highest, and that is where poverty is lowest. open the mechanism, not the pattern

Properties Contents

NameGifted identification and units
Calculation
F1=K-6 enrolled ADM×$24.00×state shareidentificationF2=enrolled ADM×$2.50×state sharereferralF3=professional developmentcarried as a value; zero for every districtcoordinator units=clamp⁡(enrolled ADM3300, 0.5, 8)specialist K-8 units=max⁡(gifted K-8 FTE140, 0.3)specialist 9-12 units=max⁡(gifted 9-12 FTE140, 0.3)unit funding=(coordinator units×$85,776+specialist K-8 units×$89,378+specialist 9-12 units×$80,974)×state shareF=F1+F2+F3+unit fundinggifted\begin{aligned} F_1 &= \text{K-6 enrolled ADM} \times \$24.00 \times \text{state share} && \text{identification} \\ F_2 &= \text{enrolled ADM} \times \$2.50 \times \text{state share} && \text{referral} \\ F_3 &= \text{professional development} && \text{carried as a value; zero for every district} \\ \text{coordinator units} &= \operatorname{clamp}\biggl( \frac{\text{enrolled ADM}}{3300},\ 0.5,\ 8 \biggr) \\ \text{specialist K-8 units} &= \max\biggl( \frac{\text{gifted K-8 FTE}}{140},\ 0.3 \biggr) \\ \text{specialist 9-12 units} &= \max\biggl( \frac{\text{gifted 9-12 FTE}}{140},\ 0.3 \biggr) \\ \text{unit funding} &= (\text{coordinator units} \times \$85{,}776 + \text{specialist K-8 units} \times \$89{,}378 \\ &\quad + \text{specialist 9-12 units} \times \$80{,}974) \times \text{state share} \\ F &= F_1 + F_2 + F_3 + \text{unit funding} && \text{gifted} \end{aligned}
Statutory basisR.C. 3317.022(A)(6) and R.C. 3317.051. This node cited R.C. 3317.053, which does not exist — the second wrong citation the statute audit turned up, after the DPIA node's R.C. 3317.029.

Codified, in two places. R.C. 3317.022(A)(6)(a) states identification as "$24 X the district's enrolled ADM for grades kindergarten through six X the district's state share percentage" and referral at $2.50, then hands unit funding to R.C. 3317.051 — which carries all three prices, $85,776, $89,378 and $80,974, exactly as transcribed. The floors and the cap sit with the prices in permanent law rather than in the budget bill, so the worry that "the two change on different cycles" does not arise. verified ohio-laws
CalculatorNot a standalone crate. Reproduced for all 609 districts in crates/project/tests/the_remaining_categoricals.rs, including the floors and the cap; carried in crates/project::panel::Gifted.

Where this appears on the site Contents

The pages outside the corpus that link here, and the section of each the link sits in.

Cleveland MunicipalIn “The categorical half, in its six parts”. The same link is on all 609 pages like this one.
Change the formulaIn “What these levers hold fixed, and one thing they deliberately do not”.
Change the formula — who it reachesIn “What the reach view holds fixed, and one thing it deliberately does not”.

What this node used to say Contents

The corpus is not rewritten to have always been right. Each entry is a claim this node carried, what replaced it, and the thing that settled it.

Correction 1 of 2

It said

Whether gifted identification rates vary with district wealth was recorded as “exactly the kind of question this decomposition makes askable and the corpus has not asked”.

It says

It is asked and answered, from data the panel already held. Because the program scales off identified FTE, the answer makes identification a district practice that funding rewards rather than a pupil population it measures.

Settled by

The identification rates already carried in the district panel, crossed against valuation per pupil.

What else it touched

Does not change the component’s arithmetic. It changes what a gifted-funding total can be read as evidence of.

Correction 2 of 2

It said

Whether identification rates vary with wealth was recorded as “exactly the kind of question this decomposition makes askable and the corpus has not asked.”

It says

They do, and poverty is much the stronger axis. Identified share of enrollment runs 10.1% to 19.0% across valuation quintiles (1.9x) and 25.0% to 8.6% across economically disadvantaged quintiles (2.9x), monotone in both — r = −0.67 on poverty against r = +0.35 on property wealth.

Settled by

crates/project/tests/questions_the_corpus_left_open.rs, over data the panel already held.

What else it touched

The question as posed expected property wealth to be the axis, and it is the weaker one. A funding stream keyed to identification pays most where identification is highest, and that is where poverty is lowest. Why is not established — trait distribution, screening capacity and instrument differences all fit, and this data separates none of them.