Safford Unified School District No. 1 V. Redding and the Future of School Strip Searches
Bibliographic record
Abstract
Each year in America an unknown number of children in primary and secondary schools are strip searched by teachers and/or school administrators, forced to remove pants and shirts down to their underwear and sometimes forced to expose their breasts and genitals. In Safford Unified School District No. 1 v. Redding, 129 S.Ct. 2633 (29), the Supreme Court weighed in on the issue, finding that school officials violated the child’s Fourth Amendment rights during a strip search but reversing the Ninth Circuit and awarding the school officials qualified immunity not withstanding the ineptitude of the investigation. The Court purported to apply Fourth Amendment rules enunciated a quarter century ago in New Jersey v. T.L.O. However, T.L.O. was hardly opaque and neither is the Court’s decision in Redding. The Court resolved little, including the most basic issue involving definition of a strip search occurs, except to recognize that a strip search by school officials is an extraordinary intrusion on basic rights and should be reserved for those cases when the object sought threatens the life or health of children. This article defines strip searches, recognizing that the definition differs for boys and girls and proposes a basic rule that school strip searches are unreasonable absent a clearly defined school policy and set of procedures.
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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 | 0.006 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.010 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.017 | 0.009 |
| Insufficient payload (model declined to judge) | 0.005 | 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".