UNE PROCÉDURE EN DIFFICULTÉ: A BLUEPRINT FOR RESOLVING “SPECIAL” EDUCATION DISPUTES THROUGH A QUASI-INQUISITORIAL ADMINISTRATIVE PROCESS
Bibliographic record
Abstract
In this essay, disability practitioner and scholar Stephen Rosenbaum proposes a radical change in the United States administrative adversarial adjudicatory process for resolution of “special” education disputes between educators and students with disabilities, looking for inspiration in part to Canada and the Commonwealth’s use of an inquisitorial approach. Typically, the dispute is over whether the students—termed “les enfants en difficulté” in French-speaking Canada—are receiving an appropriate array of instructional interventions and services. Adversarial adjudication has had many critics over the years. Asking a judge to weigh the parent (or student’s) preferred options under the U.S. Individuals with Disabilities Education Act [IDEA] against those of the school administration may not be the optimal method for designating a pupil’s educational program—nor a good use of time and money. The author’s blueprint calls for replacing the IDEA due process hearing with another model in instances where the family and school authorities disagree about the components of a student’s instructional program. Under current law, the hearing is typically conducted by an administrative jurist in which the parties present evidence, expert testimony and argument, if they have been unable to resolve their disagreement at a school-based team meeting, mediation or some other informal conference. In the proposal presented here, disagreements would instead be reviewed by a “special master” whose expertise is in education or disability rather than law. Through a process of problem-solving or “active adjudication,” the master (or “independent educational reviewer”) would attempt to quickly resolve the dispute over appropriate placement, instructional strategies and/or services. The master could hold a conference, conduct a hearing or brief investigation, receive more documents, consult with experts or correspond in some other mode with the parties. The master’s determination would be subject to judicial review in limited circumstances.
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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 | 0.275 | 0.205 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.023 | 0.134 |
| Scholarly communication | 0.030 | 0.044 |
| Open science | 0.009 | 0.027 |
| Research integrity | 0.031 | 0.055 |
| Insufficient payload (model declined to judge) | 0.006 | 0.005 |
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".