Outside the brackets: Why school administrators fail to see gendered harassment within an antibullying law
Bibliographic record
Abstract
Abstract Much of school bullying involves students policing the gender roles and sexuality of other students. The proliferation of antibullying laws presents an opportunity to formally punish and mark gendered harassment as unacceptable. However, when this form of peer policing involves girls, administrators often consider it to fall outside the purview of the law. We use bracketing theory to understand how middle school administrators in New Jersey assess whether student behavior violates a statewide harassment, intimidation, and bullying law. We find that, according to administrators, violations require relational asymmetry between an aggressor and victim: an imbalance of power and disproportionate participation. Administrators rarely see gendered harassment as bullying because of the relational stereotypes they attach to girl students, which often preclude interpretations of relational asymmetry. We discuss how gender beliefs among administrators and “bracketing failures” explain the ways antibullying laws allow hegemonic beliefs about gender and sexuality to remain untroubled.
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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 | 0.010 | 0.022 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".