Indigenous students’ experiences with racial microaggressions in Taiwan / <i>Experiencias de estudiantes indígenas con microagresiones raciales en Taiwán</i>
Bibliographic record
Abstract
Prior research has demonstrated that Black, Indigenous and People of Colour (BIPOC) experience racial microaggressions in educational settings. This study investigates how racial microaggressions against Indigenous students in K–16 educational settings in Taiwan occur and how they compare to what students experience in the United States and Canada. The research team interviewed 21 college-aged Indigenous students in 2021; participants described their interactions with peers and teachers or faculty, experiences utilizing school resources and perception of learning environments in school (K–12) and on campus. The analysis revealed that Indigenous students experience racial microaggressions at three levels: (1) interpersonal context, i.e., facing jealous accusations in class, hearing racist comments and encountering stereotypes and negative beliefs; (2) anti-Indigenous pedagogical practices, i.e., teachers or faculty misunderstand Indigenous cultures or treat Indigenous students as cultural symbols or spokespersons; and (3) systemic exclusion, i.e., the absence of Indigenous cultures in curricula and academic affairs.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.004 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| 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".