Native Americans and Science: Enhancing Participation of Native Americans in the Science and Technology Workforce through Culturally Responsive Science Education
Bibliographic record
Abstract
A major issue that directly affects the participation of Native Americans in the science and technology workforce is the lack of preparation in science and math. This lack of preparation has many causes, but one of the most strategically important issues is the lack of culturally relevant curricula that engage Native American students in learning science in personal, social and culturally meaningful ways. This essay explores the needs, issues, research, and development of culturally responsive science education for Native American learners. A curriculum model created by the author at the Institute of American Indian Arts in Santa Fe, New Mexico, from 1974 to 1994 based on Native American cultural orientations is explored as a case study as one example of how to engage Native American students in science learning and become more prepared to participate in science and technology-related professions. As such, it presents a methodology for how trans-systemic work might be approached in building conceptual bridges between Indigenous and Western views of science.
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 | 0.726 | 0.834 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.010 |
| Science and technology studies | 0.363 | 0.019 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.164 |
| 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; both teacher heads agree on what is shown here.
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".