Toward a Discussion of Issues Associated With Speech—Language Pathologists' Dismissal Practices in Public School Settings
Bibliographic record
Abstract
Guidelines for dismissal of a student who has been receiving educational interventions are available from both the American Speech-Language-Hearing Association (ASHA) Ad Hoc Committee on Admission/Discharge Criteria and from the Individuals with Disabilities Education Act (IDEA). Yet as speech—language pathologists (SLPs) in the schools enroll students and subsequently make decisions about the students' dismissal, many questions remain, especially in regard to children having persistent communication difficulties. A thorough review of the decision-making process for dismissal is one aspect of SLPs' training and serves as the foundation for decisions about when intervention should end. IDEA guidelines differ in many respects from the guidelines set forth by ASHA.There is no research that clarifies how these differing guidelines are reconciled when SLPs begin working in the schools, but the authors have anecdotal information from their experiences and from colleagues in South Carolina. An introduction to some of the other factors that may affect dismissal decisions is included. Current practice patterns and considerations for the future of speech—language services in the schools are discussed.
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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 | 0.075 | 0.113 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.033 | 0.030 |
| Scholarly communication | 0.023 | 0.019 |
| Open science | 0.006 | 0.012 |
| Research integrity | 0.022 | 0.024 |
| Insufficient payload (model declined to judge) | 0.003 | 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".