Eliminating the Racial Disparity in Classroom Exclusionary Discipline
Bibliographic record
Abstract
Advocates call for schools with high suspension rates to receive technical assistance in adopting “proven-effective” systematic supports. Such supports include teacher professional development. This call is justified given evidence that good teaching matters. But what types of professional development should be funded? Increasingly, research points to the promise of programs that are sustained, rigorous, and focused on teachers’ interactions with students. The current study tests whether a professional development program with these three characteristics helped change teachers’ use of exclusionary discipline practices—especially with their African American students. Exclusionary discipline is when a classroom teacher sends a student to the administrators’ office for perceived misbehavior. Administrators then typically assign a consequence, usually in the form of suspension (in-school or out-of school). The My Teaching Partner-Secondary (MTP-S) aims to improve teachers’ interactions with their students when implementing instruction and managing behavior. MTP-S helps teachers offer clear routines, implement consistent rules, and monitor behavior in a proactive way. The program also supports teachers in developing warm, respectful relationships that recognize students’ needs for autonomy and leadership. Teachers are paired with a coach for an entire school year (sustained approach), they regularly reflect on videorecordings of their classroom instruction and carefully observe how they interact with students, and they apply the validated Classroom Assessment Scoring System (CLASS-S) to improve the quality of their interactions (rigorous approach). In the current study, a randomized controlled trial found that teachers receiving MTP-S relied less on exclusionary discipline compared to the control teachers. Specifically, MTP-S teachers issued fewer exclusionary discipline referrals to their African American students. This is the first study to show that programs like MTP-S that focus on teacher-student interactions in a sustained manner using a rigorous approach can actually reduce the disproportionate use of exclusionary discipline with African American students. More broadly, the findings offer policymakers direction in identifying types of professional development programs that have promise for reducing the racial discipline gap.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".