Teacher Education Students’ Implicit Racial Attitudes and Interpersonal Attribution of Racialized Student Behavior
Bibliographic record
Abstract
Teachers have been shown to hold lower behavioral expectations for Black students than for their White peers, and the mechanism underlying this may be teachers’ implicit attitudes about their Black students based on causal attributions. This study examined this connection, predicting that teacher education students (TES) who scored higher on the racial implicit bias test would attribute internal causality and controllability to explain challenging behaviors in the classroom more frequently for Black students than for White students. 233 teacher education students completed the racial bias section of the Implicit Assessment Test and a set of questions assessing causal attribution based on four vignettes depicting student misbehaviors in a classroom setting. We found that regardless of implicit bias, TES were more likely to believe that Black students had an internal locus of causality and controllability than their White counterparts when presented with similar instances of challenging behavior. These results support the need for teacher preparation programs to address how these internal beliefs of teacher education students affect what they learn about managing their expectations around students’ behavioral regulation and to what they attribute these behaviors.
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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 | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".