Unequal and Increasingly Unfair: How Federal Policy Creates Disparities in Special Education Funding
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The formula used to allocate federal funding to states for special education is one of IDEA's most critical components. The formula serves as the primary mechanism for dividing available federal dollars among states and represents policy makers’ intent to equalize educational opportunities for students with disabilities nationwide. In this study, we evaluate the distribution of IDEA Part B funding in the wake of changes to the formula that were instituted at the law's 1997 reauthorization. We find that the revised formula generates large and concerning disparities among states in federal special education dollars. On average, states with proportionally larger populations of children and children living in poverty, children identified for special education, and non-White and Black children receive fewer federal dollars per capita.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it