Investigating the impact of racial microaggressions on Black, racialized, and Indigenous students: a narrative synthesis
Bibliographic record
Abstract
Some US and Canadian policymakers have advocated removing anti-racism education and Critical Race Theory (CRT) within schools. The political discourse prioritizes the comfort of white teachers and students while ignoring the voices of Black, racialized, and Indigenous students. This article discusses a systematic review that examined the systemic impact of racial microaggressions on Black, racialized and Indigenous students in K-12 and postsecondary contexts. A systematic search of nine academic databases yielded 3,560 relevant articles, of which 150 met the inclusion criteria after a full-text review. The review found four themes and 13 subthemes related to students’ experiences with racial microaggressions at school. The findings contribute to a better understanding of power dynamics in education, which affects students’ experiences with racial microaggressions. The study highlights the need to re-evaluate the current political discourse on CRT and anti-racism education. It emphasizes the importance of addressing racial microaggressions in schools by dismantling white supremacy.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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".