Working for Social Justice in Rural Schools: A Model for Science Education, 10(28)
Bibliographic record
Abstract
One-third of all U.S. school children attend school in rural settings. Rural schools are much poorer than urban America, with most of the poorest counties in the United States located in rural areas. Equity is a concern not only in terms of race, class, gender, disability, and sexual orientation, but also in terms of being geographically located in a rural area. Rural teachers are often not certified in their teaching areas, with one in four rural science teachers lacking in academic preparation or certification. This article describes the K20 Oklahoma Science Initiative for Rural Schools that targets low-income, rural schools serving diverse populations in Oklahoma. The K20 Initiative helps reduce the professional, cultural, and social isolation and lack of professional development in rural schools. The objectives of the initiative are to improve teacher quality and student success through three research-based strategies which are described in the article.
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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 | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.015 | 0.022 |
| Scholarly communication | 0.013 | 0.007 |
| Open science | 0.002 | 0.011 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.015 | 0.002 |
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".