Cultural models of education and academic performance for Native American and European American students
Bibliographic record
Abstract
We examined the role of cultural representations of self (i.e., interdependence and independence) and positive relationships (i.e., trust for teachers) in academic performance (i.e., self-reported grades) for Native American ( N = 41) and European American ( N = 49) high school students. The Native American students endorsed marginally more interdependent representation of self and marginally less trust for teachers than did the European American students. While interdependent representations of self and trust for teachers were positively related for the Native American students, neither cultural representations of self were related to trust for teachers for the European American students. However, with respect to academic performance, interdependent representations of self and trust for teachers were positively related to academic performance for the Native American students. Conversely, independent and interdependent representations of self were positively related to academic performance for the European American students, but trust for teachers was not associated with academic performance. Finally, as predicted, culturally congruent representations of self predicted academic performance. Specifically, trust for teachers and interdependent representations of self positively predicted academic performance for Native American students, whereas only independent representations of self predicted academic performance for European American students. Implications for culturally congruent models of education are discussed.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".