When ethnic–racial discrimination from math teachers spills over and predicts the math adjustment of nondiscriminated adolescents: The mediating role of math classroom climate perceptions.
Bibliographic record
Abstract
= 1.49; 60% Black, 30% White, 9% other, 1% Asian; 49% female, 51% male) nested in 104 math classrooms, as math is a subject domain with pervasive ethnic-racial stereotypes about students' abilities and opportunities to succeed in class. Results illustrated that direct and vicarious ethnic-racial discrimination from math educators in the fall semester predicted worse math course grades, state-administered standardized test scores, and classroom engagement across the fall and spring semesters. Math classroom climate perceptions mediated the longitudinal relations between ethnic-racial discrimination and their math adjustment outcomes, and the role of ethnic-racial discrimination varied across different developmental stages of adolescence. Implications for the measurement of ethnic-racial discrimination in the classroom context and the social contagion linked to ethnic-racial disadvantage are discussed. (PsycInfo Database Record (c) 2024 APA, all rights reserved).
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".