Motivational Effects and Public Funding for Special Education
Bibliographic record
Abstract
Abstract In this chapter, we explore how education funding systems, inclusive of funding programs for general and special education, may affect whether and how students with disabilities receive special education and related services. And yet, funding should not affect a child with a disability’s opportunity to access public schooling or their learning. Federal law obligates states and local education agencies to provide—at no cost to students and parents—special education and related services to children with disabilities that are appropriate to their needs. Given the chasm between policy and practice, it is both necessary and important to understand how state policies for funding schools impact local decision making. We review the legal and regulatory frameworks that establish the requirement for public funding for special education and the existing research on motivational effects of programs designed to provide specific funding for special education. We then present new evidence about the connection between general education funding and special education identification rates. The chapter concludes with considerations for policymakers as they seek to develop and evaluate education finance systems that ensure students with disabilities equitable access to educational opportunities.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.022 | 0.001 |
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".